Defer asset_seeder resume until GC interval elapses

Only resume the asset scanner when the needs_gc time condition is
satisfied, preventing the scanner from restarting between rapid
successive prompt executions.

Amp-Thread-ID: https://ampcode.com/threads/T-019cc637-2352-7139-b753-47c19f43b55c
Co-authored-by: Amp <amp@ampcode.com>

.coderabbit.yaml

@@ -0,0 +1,127 @@
+# yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json
+language: "en-US"
+early_access: false
+tone_instructions: "Only comment on issues introduced by this PR's changes. Do not flag pre-existing problems in moved, re-indented, or reformatted code."
+
+reviews:
+  profile: "chill"
+  request_changes_workflow: false
+  high_level_summary: false
+  poem: false
+  review_status: false
+  review_details: false
+  commit_status: true
+  collapse_walkthrough: true
+  changed_files_summary: false
+  sequence_diagrams: false
+  estimate_code_review_effort: false
+  assess_linked_issues: false
+  related_issues: false
+  related_prs: false
+  suggested_labels: false
+  auto_apply_labels: false
+  suggested_reviewers: false
+  auto_assign_reviewers: false
+  in_progress_fortune: false
+  enable_prompt_for_ai_agents: true
+
+  path_filters:
+    - "!comfy_api_nodes/apis/**"
+    - "!**/generated/*.pyi"
+    - "!.ci/**"
+    - "!script_examples/**"
+    - "!**/__pycache__/**"
+    - "!**/*.ipynb"
+    - "!**/*.png"
+    - "!**/*.bat"
+
+  path_instructions:
+    - path: "**"
+      instructions: |
+        IMPORTANT: Only comment on issues directly introduced by this PR's code changes.
+        Do NOT flag pre-existing issues in code that was merely moved, re-indented,
+        de-indented, or reformatted without logic changes. If code appears in the diff
+        only due to whitespace or structural reformatting (e.g., removing a `with:` block),
+        treat it as unchanged. Contributors should not feel obligated to address
+        pre-existing issues outside the scope of their contribution.
+    - path: "comfy/**"
+      instructions: |
+        Core ML/diffusion engine. Focus on:
+        - Backward compatibility (breaking changes affect all custom nodes)
+        - Memory management and GPU resource handling
+        - Performance implications in hot paths
+        - Thread safety for concurrent execution
+    - path: "comfy_api_nodes/**"
+      instructions: |
+        Third-party API integration nodes. Focus on:
+        - No hardcoded API keys or secrets
+        - Proper error handling for API failures (timeouts, rate limits, auth errors)
+        - Correct Pydantic model usage
+        - Security of user data passed to external APIs
+    - path: "comfy_extras/**"
+      instructions: |
+        Community-contributed extra nodes. Focus on:
+        - Consistency with node patterns (INPUT_TYPES, RETURN_TYPES, FUNCTION, CATEGORY)
+        - No breaking changes to existing node interfaces
+    - path: "comfy_execution/**"
+      instructions: |
+        Execution engine (graph execution, caching, jobs). Focus on:
+        - Caching correctness
+        - Concurrent execution safety
+        - Graph validation edge cases
+    - path: "nodes.py"
+      instructions: |
+        Core node definitions (2500+ lines). Focus on:
+        - Backward compatibility of NODE_CLASS_MAPPINGS
+        - Consistency of INPUT_TYPES return format
+    - path: "alembic_db/**"
+      instructions: |
+        Database migrations. Focus on:
+        - Migration safety and rollback support
+        - Data preservation during schema changes
+
+  auto_review:
+    enabled: true
+    auto_incremental_review: true
+    drafts: false
+    ignore_title_keywords:
+      - "WIP"
+      - "DO NOT REVIEW"
+      - "DO NOT MERGE"
+
+  finishing_touches:
+    docstrings:
+      enabled: false
+    unit_tests:
+      enabled: false
+
+  tools:
+    ruff:
+      enabled: false
+    pylint:
+      enabled: false
+    flake8:
+      enabled: false
+    gitleaks:
+      enabled: true
+    shellcheck:
+      enabled: false
+    markdownlint:
+      enabled: false
+    yamllint:
+      enabled: false
+    languagetool:
+      enabled: false
+    github-checks:
+      enabled: true
+      timeout_ms: 90000
+    ast-grep:
+      essential_rules: true
+
+chat:
+  auto_reply: true
+
+knowledge_base:
+  opt_out: false
+  learnings:
+    scope: "auto"

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -16,7 +16,7 @@ body:
 
         ## Very Important
 
-        Please make sure that you post ALL your ComfyUI logs in the bug report. A bug report without logs will likely be ignored.
+        Please make sure that you post ALL your ComfyUI logs in the bug report **even if there is no crash**. Just paste everything. The startup log (everything before "To see the GUI go to: ...") contains critical information to developers trying to help. For a performance issue or crash, paste everything from "got prompt" to the end, including the crash. More is better - always. A bug report without logs will likely be ignored.
   - type: checkboxes
     id: custom-nodes-test
     attributes:

.gitignore

@@ -11,7 +11,7 @@ extra_model_paths.yaml
 /.vs
 .vscode/
 .idea/
-venv/
+venv*/
 .venv/
 /web/extensions/*
 !/web/extensions/logging.js.example

README.md

@@ -189,8 +189,6 @@ The portable above currently comes with python 3.13 and pytorch cuda 13.0. Updat
 
 [Experimental portable for AMD GPUs](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_amd.7z)
 
-[Portable with pytorch cuda 12.8 and python 3.12](https://github.com/comfyanonymous/ComfyUI/releases/latest/download/ComfyUI_windows_portable_nvidia_cu128.7z).
-
 [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).
 
 #### How do I share models between another UI and ComfyUI?
@@ -229,9 +227,9 @@ AMD users can install rocm and pytorch with pip if you don't have it already ins
 
 ```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.1```
 
-This is the command to install the nightly with ROCm 7.1 which might have some performance improvements:
+This is the command to install the nightly with ROCm 7.2 which might have some performance improvements:
 
-```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.1```
+```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.2```
 
 
 ### AMD GPUs (Experimental: Windows and Linux), RDNA 3, 3.5 and 4 only.

alembic_db/versions/0002_merge_to_asset_references.py

@@ -0,0 +1,267 @@
+"""
+Merge AssetInfo and AssetCacheState into unified asset_references table.
+
+This migration drops old tables and creates the new unified schema.
+All existing data is discarded.
+
+Revision ID: 0002_merge_to_asset_references
+Revises: 0001_assets
+Create Date: 2025-02-11
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+revision = "0002_merge_to_asset_references"
+down_revision = "0001_assets"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    # Drop old tables (order matters due to FK constraints)
+    op.drop_index("ix_asset_info_meta_key_val_bool", table_name="asset_info_meta")
+    op.drop_index("ix_asset_info_meta_key_val_num", table_name="asset_info_meta")
+    op.drop_index("ix_asset_info_meta_key_val_str", table_name="asset_info_meta")
+    op.drop_index("ix_asset_info_meta_key", table_name="asset_info_meta")
+    op.drop_table("asset_info_meta")
+
+    op.drop_index("ix_asset_info_tags_asset_info_id", table_name="asset_info_tags")
+    op.drop_index("ix_asset_info_tags_tag_name", table_name="asset_info_tags")
+    op.drop_table("asset_info_tags")
+
+    op.drop_index("ix_asset_cache_state_asset_id", table_name="asset_cache_state")
+    op.drop_index("ix_asset_cache_state_file_path", table_name="asset_cache_state")
+    op.drop_table("asset_cache_state")
+
+    op.drop_index("ix_assets_info_owner_name", table_name="assets_info")
+    op.drop_index("ix_assets_info_last_access_time", table_name="assets_info")
+    op.drop_index("ix_assets_info_created_at", table_name="assets_info")
+    op.drop_index("ix_assets_info_name", table_name="assets_info")
+    op.drop_index("ix_assets_info_asset_id", table_name="assets_info")
+    op.drop_index("ix_assets_info_owner_id", table_name="assets_info")
+    op.drop_table("assets_info")
+
+    # Truncate assets table (cascades handled by dropping dependent tables first)
+    op.execute("DELETE FROM assets")
+
+    # Create asset_references table
+    op.create_table(
+        "asset_references",
+        sa.Column("id", sa.String(length=36), primary_key=True),
+        sa.Column(
+            "asset_id",
+            sa.String(length=36),
+            sa.ForeignKey("assets.id", ondelete="CASCADE"),
+            nullable=False,
+        ),
+        sa.Column("file_path", sa.Text(), nullable=True),
+        sa.Column("mtime_ns", sa.BigInteger(), nullable=True),
+        sa.Column(
+            "needs_verify",
+            sa.Boolean(),
+            nullable=False,
+            server_default=sa.text("false"),
+        ),
+        sa.Column(
+            "is_missing", sa.Boolean(), nullable=False, server_default=sa.text("false")
+        ),
+        sa.Column("enrichment_level", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("owner_id", sa.String(length=128), nullable=False, server_default=""),
+        sa.Column("name", sa.String(length=512), nullable=False),
+        sa.Column(
+            "preview_id",
+            sa.String(length=36),
+            sa.ForeignKey("assets.id", ondelete="SET NULL"),
+            nullable=True,
+        ),
+        sa.Column("user_metadata", sa.JSON(), nullable=True),
+        sa.Column("created_at", sa.DateTime(timezone=False), nullable=False),
+        sa.Column("updated_at", sa.DateTime(timezone=False), nullable=False),
+        sa.Column("last_access_time", sa.DateTime(timezone=False), nullable=False),
+        sa.Column("deleted_at", sa.DateTime(timezone=False), nullable=True),
+        sa.CheckConstraint(
+            "(mtime_ns IS NULL) OR (mtime_ns >= 0)", name="ck_ar_mtime_nonneg"
+        ),
+        sa.CheckConstraint(
+            "enrichment_level >= 0 AND enrichment_level <= 2",
+            name="ck_ar_enrichment_level_range",
+        ),
+    )
+    op.create_index(
+        "uq_asset_references_file_path", "asset_references", ["file_path"], unique=True
+    )
+    op.create_index("ix_asset_references_asset_id", "asset_references", ["asset_id"])
+    op.create_index("ix_asset_references_owner_id", "asset_references", ["owner_id"])
+    op.create_index("ix_asset_references_name", "asset_references", ["name"])
+    op.create_index("ix_asset_references_is_missing", "asset_references", ["is_missing"])
+    op.create_index(
+        "ix_asset_references_enrichment_level", "asset_references", ["enrichment_level"]
+    )
+    op.create_index("ix_asset_references_created_at", "asset_references", ["created_at"])
+    op.create_index(
+        "ix_asset_references_last_access_time", "asset_references", ["last_access_time"]
+    )
+    op.create_index(
+        "ix_asset_references_owner_name", "asset_references", ["owner_id", "name"]
+    )
+    op.create_index("ix_asset_references_deleted_at", "asset_references", ["deleted_at"])
+
+    # Create asset_reference_tags table
+    op.create_table(
+        "asset_reference_tags",
+        sa.Column(
+            "asset_reference_id",
+            sa.String(length=36),
+            sa.ForeignKey("asset_references.id", ondelete="CASCADE"),
+            nullable=False,
+        ),
+        sa.Column(
+            "tag_name",
+            sa.String(length=512),
+            sa.ForeignKey("tags.name", ondelete="RESTRICT"),
+            nullable=False,
+        ),
+        sa.Column(
+            "origin", sa.String(length=32), nullable=False, server_default="manual"
+        ),
+        sa.Column("added_at", sa.DateTime(timezone=False), nullable=False),
+        sa.PrimaryKeyConstraint(
+            "asset_reference_id", "tag_name", name="pk_asset_reference_tags"
+        ),
+    )
+    op.create_index(
+        "ix_asset_reference_tags_tag_name", "asset_reference_tags", ["tag_name"]
+    )
+    op.create_index(
+        "ix_asset_reference_tags_asset_reference_id",
+        "asset_reference_tags",
+        ["asset_reference_id"],
+    )
+
+    # Create asset_reference_meta table
+    op.create_table(
+        "asset_reference_meta",
+        sa.Column(
+            "asset_reference_id",
+            sa.String(length=36),
+            sa.ForeignKey("asset_references.id", ondelete="CASCADE"),
+            nullable=False,
+        ),
+        sa.Column("key", sa.String(length=256), nullable=False),
+        sa.Column("ordinal", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("val_str", sa.String(length=2048), nullable=True),
+        sa.Column("val_num", sa.Numeric(38, 10), nullable=True),
+        sa.Column("val_bool", sa.Boolean(), nullable=True),
+        sa.Column("val_json", sa.JSON(), nullable=True),
+        sa.PrimaryKeyConstraint(
+            "asset_reference_id", "key", "ordinal", name="pk_asset_reference_meta"
+        ),
+    )
+    op.create_index("ix_asset_reference_meta_key", "asset_reference_meta", ["key"])
+    op.create_index(
+        "ix_asset_reference_meta_key_val_str", "asset_reference_meta", ["key", "val_str"]
+    )
+    op.create_index(
+        "ix_asset_reference_meta_key_val_num", "asset_reference_meta", ["key", "val_num"]
+    )
+    op.create_index(
+        "ix_asset_reference_meta_key_val_bool",
+        "asset_reference_meta",
+        ["key", "val_bool"],
+    )
+
+
+def downgrade() -> None:
+    """Reverse 0002_merge_to_asset_references: drop new tables, recreate old schema.
+
+    NOTE: Data is not recoverable. The upgrade discards all rows from the old
+    tables and truncates assets. After downgrade the old schema will be empty.
+    A filesystem rescan will repopulate data once the older code is running.
+    """
+    # Drop new tables (order matters due to FK constraints)
+    op.drop_index("ix_asset_reference_meta_key_val_bool", table_name="asset_reference_meta")
+    op.drop_index("ix_asset_reference_meta_key_val_num", table_name="asset_reference_meta")
+    op.drop_index("ix_asset_reference_meta_key_val_str", table_name="asset_reference_meta")
+    op.drop_index("ix_asset_reference_meta_key", table_name="asset_reference_meta")
+    op.drop_table("asset_reference_meta")
+
+    op.drop_index("ix_asset_reference_tags_asset_reference_id", table_name="asset_reference_tags")
+    op.drop_index("ix_asset_reference_tags_tag_name", table_name="asset_reference_tags")
+    op.drop_table("asset_reference_tags")
+
+    op.drop_index("ix_asset_references_deleted_at", table_name="asset_references")
+    op.drop_index("ix_asset_references_owner_name", table_name="asset_references")
+    op.drop_index("ix_asset_references_last_access_time", table_name="asset_references")
+    op.drop_index("ix_asset_references_created_at", table_name="asset_references")
+    op.drop_index("ix_asset_references_enrichment_level", table_name="asset_references")
+    op.drop_index("ix_asset_references_is_missing", table_name="asset_references")
+    op.drop_index("ix_asset_references_name", table_name="asset_references")
+    op.drop_index("ix_asset_references_owner_id", table_name="asset_references")
+    op.drop_index("ix_asset_references_asset_id", table_name="asset_references")
+    op.drop_index("uq_asset_references_file_path", table_name="asset_references")
+    op.drop_table("asset_references")
+
+    # Truncate assets (upgrade deleted all rows; downgrade starts fresh too)
+    op.execute("DELETE FROM assets")
+
+    # Recreate old tables from 0001_assets schema
+    op.create_table(
+        "assets_info",
+        sa.Column("id", sa.String(length=36), primary_key=True),
+        sa.Column("owner_id", sa.String(length=128), nullable=False, server_default=""),
+        sa.Column("name", sa.String(length=512), nullable=False),
+        sa.Column("asset_id", sa.String(length=36), sa.ForeignKey("assets.id", ondelete="RESTRICT"), nullable=False),
+        sa.Column("preview_id", sa.String(length=36), sa.ForeignKey("assets.id", ondelete="SET NULL"), nullable=True),
+        sa.Column("user_metadata", sa.JSON(), nullable=True),
+        sa.Column("created_at", sa.DateTime(timezone=False), nullable=False),
+        sa.Column("updated_at", sa.DateTime(timezone=False), nullable=False),
+        sa.Column("last_access_time", sa.DateTime(timezone=False), nullable=False),
+        sa.UniqueConstraint("asset_id", "owner_id", "name", name="uq_assets_info_asset_owner_name"),
+    )
+    op.create_index("ix_assets_info_owner_id", "assets_info", ["owner_id"])
+    op.create_index("ix_assets_info_asset_id", "assets_info", ["asset_id"])
+    op.create_index("ix_assets_info_name", "assets_info", ["name"])
+    op.create_index("ix_assets_info_created_at", "assets_info", ["created_at"])
+    op.create_index("ix_assets_info_last_access_time", "assets_info", ["last_access_time"])
+    op.create_index("ix_assets_info_owner_name", "assets_info", ["owner_id", "name"])
+
+    op.create_table(
+        "asset_cache_state",
+        sa.Column("id", sa.Integer(), primary_key=True, autoincrement=True),
+        sa.Column("asset_id", sa.String(length=36), sa.ForeignKey("assets.id", ondelete="CASCADE"), nullable=False),
+        sa.Column("file_path", sa.Text(), nullable=False),
+        sa.Column("mtime_ns", sa.BigInteger(), nullable=True),
+        sa.Column("needs_verify", sa.Boolean(), nullable=False, server_default=sa.text("false")),
+        sa.CheckConstraint("(mtime_ns IS NULL) OR (mtime_ns >= 0)", name="ck_acs_mtime_nonneg"),
+        sa.UniqueConstraint("file_path", name="uq_asset_cache_state_file_path"),
+    )
+    op.create_index("ix_asset_cache_state_file_path", "asset_cache_state", ["file_path"])
+    op.create_index("ix_asset_cache_state_asset_id", "asset_cache_state", ["asset_id"])
+
+    op.create_table(
+        "asset_info_tags",
+        sa.Column("asset_info_id", sa.String(length=36), sa.ForeignKey("assets_info.id", ondelete="CASCADE"), nullable=False),
+        sa.Column("tag_name", sa.String(length=512), sa.ForeignKey("tags.name", ondelete="RESTRICT"), nullable=False),
+        sa.Column("origin", sa.String(length=32), nullable=False, server_default="manual"),
+        sa.Column("added_at", sa.DateTime(timezone=False), nullable=False),
+        sa.PrimaryKeyConstraint("asset_info_id", "tag_name", name="pk_asset_info_tags"),
+    )
+    op.create_index("ix_asset_info_tags_tag_name", "asset_info_tags", ["tag_name"])
+    op.create_index("ix_asset_info_tags_asset_info_id", "asset_info_tags", ["asset_info_id"])
+
+    op.create_table(
+        "asset_info_meta",
+        sa.Column("asset_info_id", sa.String(length=36), sa.ForeignKey("assets_info.id", ondelete="CASCADE"), nullable=False),
+        sa.Column("key", sa.String(length=256), nullable=False),
+        sa.Column("ordinal", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("val_str", sa.String(length=2048), nullable=True),
+        sa.Column("val_num", sa.Numeric(38, 10), nullable=True),
+        sa.Column("val_bool", sa.Boolean(), nullable=True),
+        sa.Column("val_json", sa.JSON(), nullable=True),
+        sa.PrimaryKeyConstraint("asset_info_id", "key", "ordinal", name="pk_asset_info_meta"),
+    )
+    op.create_index("ix_asset_info_meta_key", "asset_info_meta", ["key"])
+    op.create_index("ix_asset_info_meta_key_val_str", "asset_info_meta", ["key", "val_str"])
+    op.create_index("ix_asset_info_meta_key_val_num", "asset_info_meta", ["key", "val_num"])
+    op.create_index("ix_asset_info_meta_key_val_bool", "asset_info_meta", ["key", "val_bool"])

app/assets/api/schemas_in.py

@@ -1,6 +1,8 @@
 import json
+from dataclasses import dataclass
 from typing import Any, Literal
 
+from app.assets.helpers import validate_blake3_hash
 from pydantic import (
     BaseModel,
     ConfigDict,
@@ -10,6 +12,41 @@ from pydantic import (
     model_validator,
 )
 
+
+class UploadError(Exception):
+    """Error during upload parsing with HTTP status and code."""
+
+    def __init__(self, status: int, code: str, message: str):
+        super().__init__(message)
+        self.status = status
+        self.code = code
+        self.message = message
+
+
+class AssetValidationError(Exception):
+    """Validation error in asset processing (invalid tags, metadata, etc.)."""
+
+    def __init__(self, code: str, message: str):
+        super().__init__(message)
+        self.code = code
+        self.message = message
+
+
+@dataclass
+class ParsedUpload:
+    """Result of parsing a multipart upload request."""
+
+    file_present: bool
+    file_written: int
+    file_client_name: str | None
+    tmp_path: str | None
+    tags_raw: list[str]
+    provided_name: str | None
+    user_metadata_raw: str | None
+    provided_hash: str | None
+    provided_hash_exists: bool | None
+
+
 class ListAssetsQuery(BaseModel):
     include_tags: list[str] = Field(default_factory=list)
     exclude_tags: list[str] = Field(default_factory=list)
@@ -21,7 +58,9 @@ class ListAssetsQuery(BaseModel):
     limit: conint(ge=1, le=500) = 20
     offset: conint(ge=0) = 0
 
-    sort: Literal["name", "created_at", "updated_at", "size", "last_access_time"] = "created_at"
+    sort: Literal["name", "created_at", "updated_at", "size", "last_access_time"] = (
+        "created_at"
+    )
     order: Literal["asc", "desc"] = "desc"
 
     @field_validator("include_tags", "exclude_tags", mode="before")
@@ -61,7 +100,7 @@ class UpdateAssetBody(BaseModel):
     user_metadata: dict[str, Any] | None = None
 
     @model_validator(mode="after")
-    def _at_least_one(self):
+    def _validate_at_least_one_field(self):
         if self.name is None and self.user_metadata is None:
             raise ValueError("Provide at least one of: name, user_metadata.")
         return self
@@ -78,19 +117,11 @@ class CreateFromHashBody(BaseModel):
     @field_validator("hash")
     @classmethod
     def _require_blake3(cls, v):
-        s = (v or "").strip().lower()
-        if ":" not in s:
-            raise ValueError("hash must be 'blake3:<hex>'")
-        algo, digest = s.split(":", 1)
-        if algo != "blake3":
-            raise ValueError("only canonical 'blake3:<hex>' is accepted here")
-        if not digest or any(c for c in digest if c not in "0123456789abcdef"):
-            raise ValueError("hash digest must be lowercase hex")
-        return s
+        return validate_blake3_hash(v or "")
 
     @field_validator("tags", mode="before")
     @classmethod
-    def _tags_norm(cls, v):
+    def _normalize_tags_field(cls, v):
         if v is None:
             return []
         if isinstance(v, list):
@@ -154,15 +185,16 @@ class TagsRemove(TagsAdd):
 
 class UploadAssetSpec(BaseModel):
     """Upload Asset operation.
+
     - tags: ordered; first is root ('models'|'input'|'output');
-            if root == 'models', second must be a valid category from folder_paths.folder_names_and_paths
+            if root == 'models', second must be a valid category
     - name: display name
     - user_metadata: arbitrary JSON object (optional)
-    - hash: optional canonical 'blake3:<hex>' provided by the client for validation / fast-path
+    - hash: optional canonical 'blake3:<hex>' for validation / fast-path
 
-    Files created via this endpoint are stored on disk using the **content hash** as the filename stem
-    and the original extension is preserved when available.
+    Files are stored using the content hash as filename stem.
     """
+
     model_config = ConfigDict(extra="ignore", str_strip_whitespace=True)
 
     tags: list[str] = Field(..., min_length=1)
@@ -175,17 +207,10 @@ class UploadAssetSpec(BaseModel):
     def _parse_hash(cls, v):
         if v is None:
             return None
-        s = str(v).strip().lower()
+        s = str(v).strip()
         if not s:
             return None
-        if ":" not in s:
-            raise ValueError("hash must be 'blake3:<hex>'")
-        algo, digest = s.split(":", 1)
-        if algo != "blake3":
-            raise ValueError("only canonical 'blake3:<hex>' is accepted here")
-        if not digest or any(c for c in digest if c not in "0123456789abcdef"):
-            raise ValueError("hash digest must be lowercase hex")
-        return f"{algo}:{digest}"
+        return validate_blake3_hash(s)
 
     @field_validator("tags", mode="before")
     @classmethod
@@ -260,5 +285,7 @@ class UploadAssetSpec(BaseModel):
             raise ValueError("first tag must be one of: models, input, output")
         if root == "models":
             if len(self.tags) < 2:
-                raise ValueError("models uploads require a category tag as the second tag")
+                raise ValueError(
+                    "models uploads require a category tag as the second tag"
+                )
         return self

app/assets/api/schemas_out.py

@@ -19,7 +19,7 @@ class AssetSummary(BaseModel):
     model_config = ConfigDict(from_attributes=True)
 
     @field_serializer("created_at", "updated_at", "last_access_time")
-    def _ser_dt(self, v: datetime | None, _info):
+    def _serialize_datetime(self, v: datetime | None, _info):
         return v.isoformat() if v else None
 
 
@@ -40,7 +40,7 @@ class AssetUpdated(BaseModel):
     model_config = ConfigDict(from_attributes=True)
 
     @field_serializer("updated_at")
-    def _ser_updated(self, v: datetime | None, _info):
+    def _serialize_updated_at(self, v: datetime | None, _info):
         return v.isoformat() if v else None
 
 
@@ -59,7 +59,7 @@ class AssetDetail(BaseModel):
     model_config = ConfigDict(from_attributes=True)
 
     @field_serializer("created_at", "last_access_time")
-    def _ser_dt(self, v: datetime | None, _info):
+    def _serialize_datetime(self, v: datetime | None, _info):
         return v.isoformat() if v else None
 
 

app/assets/api/upload.py

@@ -0,0 +1,171 @@
+import logging
+import os
+import uuid
+from typing import Callable
+
+from aiohttp import web
+
+import folder_paths
+from app.assets.api.schemas_in import ParsedUpload, UploadError
+from app.assets.helpers import validate_blake3_hash
+
+
+def normalize_and_validate_hash(s: str) -> str:
+    """Validate and normalize a hash string.
+
+    Returns canonical 'blake3:<hex>' or raises UploadError.
+    """
+    try:
+        return validate_blake3_hash(s)
+    except ValueError:
+        raise UploadError(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'")
+
+
+async def parse_multipart_upload(
+    request: web.Request,
+    check_hash_exists: Callable[[str], bool],
+) -> ParsedUpload:
+    """
+    Parse a multipart/form-data upload request.
+
+    Args:
+        request: The aiohttp request
+        check_hash_exists: Callable(hash_str) -> bool to check if a hash exists
+
+    Returns:
+        ParsedUpload with parsed fields and temp file path
+
+    Raises:
+        UploadError: On validation or I/O errors
+    """
+    if not (request.content_type or "").lower().startswith("multipart/"):
+        raise UploadError(
+            415, "UNSUPPORTED_MEDIA_TYPE", "Use multipart/form-data for uploads."
+        )
+
+    reader = await request.multipart()
+
+    file_present = False
+    file_client_name: str | None = None
+    tags_raw: list[str] = []
+    provided_name: str | None = None
+    user_metadata_raw: str | None = None
+    provided_hash: str | None = None
+    provided_hash_exists: bool | None = None
+
+    file_written = 0
+    tmp_path: str | None = None
+
+    while True:
+        field = await reader.next()
+        if field is None:
+            break
+
+        fname = getattr(field, "name", "") or ""
+
+        if fname == "hash":
+            try:
+                s = ((await field.text()) or "").strip().lower()
+            except Exception:
+                raise UploadError(
+                    400, "INVALID_HASH", "hash must be like 'blake3:<hex>'"
+                )
+
+            if s:
+                provided_hash = normalize_and_validate_hash(s)
+                try:
+                    provided_hash_exists = check_hash_exists(provided_hash)
+                except Exception as e:
+                    logging.error(
+                        "check_hash_exists failed for hash=%s: %s", provided_hash, e
+                    )
+                    raise UploadError(
+                        500,
+                        "HASH_CHECK_FAILED",
+                        "Backend error while checking asset hash.",
+                    )
+
+        elif fname == "file":
+            file_present = True
+            file_client_name = (field.filename or "").strip()
+
+            if provided_hash and provided_hash_exists is True:
+                # Hash exists - drain file but don't write to disk
+                try:
+                    while True:
+                        chunk = await field.read_chunk(8 * 1024 * 1024)
+                        if not chunk:
+                            break
+                        file_written += len(chunk)
+                except Exception:
+                    raise UploadError(
+                        500, "UPLOAD_IO_ERROR", "Failed to receive uploaded file."
+                    )
+                continue
+
+            uploads_root = os.path.join(folder_paths.get_temp_directory(), "uploads")
+            unique_dir = os.path.join(uploads_root, uuid.uuid4().hex)
+            os.makedirs(unique_dir, exist_ok=True)
+            tmp_path = os.path.join(unique_dir, ".upload.part")
+
+            try:
+                with open(tmp_path, "wb") as f:
+                    while True:
+                        chunk = await field.read_chunk(8 * 1024 * 1024)
+                        if not chunk:
+                            break
+                        f.write(chunk)
+                        file_written += len(chunk)
+            except Exception:
+                delete_temp_file_if_exists(tmp_path)
+                raise UploadError(
+                    500, "UPLOAD_IO_ERROR", "Failed to receive and store uploaded file."
+                )
+
+        elif fname == "tags":
+            tags_raw.append((await field.text()) or "")
+        elif fname == "name":
+            provided_name = (await field.text()) or None
+        elif fname == "user_metadata":
+            user_metadata_raw = (await field.text()) or None
+
+    if not file_present and not (provided_hash and provided_hash_exists):
+        raise UploadError(
+            400, "MISSING_FILE", "Form must include a 'file' part or a known 'hash'."
+        )
+
+    if (
+        file_present
+        and file_written == 0
+        and not (provided_hash and provided_hash_exists)
+    ):
+        delete_temp_file_if_exists(tmp_path)
+        raise UploadError(400, "EMPTY_UPLOAD", "Uploaded file is empty.")
+
+    return ParsedUpload(
+        file_present=file_present,
+        file_written=file_written,
+        file_client_name=file_client_name,
+        tmp_path=tmp_path,
+        tags_raw=tags_raw,
+        provided_name=provided_name,
+        user_metadata_raw=user_metadata_raw,
+        provided_hash=provided_hash,
+        provided_hash_exists=provided_hash_exists,
+    )
+
+
+def delete_temp_file_if_exists(tmp_path: str | None) -> None:
+    """Safely remove a temp file and its parent directory if empty."""
+    if tmp_path:
+        try:
+            if os.path.exists(tmp_path):
+                os.remove(tmp_path)
+        except OSError as e:
+            logging.debug("Failed to delete temp file %s: %s", tmp_path, e)
+        try:
+            parent = os.path.dirname(tmp_path)
+            if parent and os.path.isdir(parent):
+                os.rmdir(parent)  # only succeeds if empty
+        except OSError:
+            pass

app/assets/database/bulk_ops.py

@@ -1,204 +0,0 @@
-import os
-import uuid
-import sqlalchemy
-from typing import Iterable
-from sqlalchemy.orm import Session
-from sqlalchemy.dialects import sqlite
-
-from app.assets.helpers import utcnow
-from app.assets.database.models import Asset, AssetCacheState, AssetInfo, AssetInfoTag, AssetInfoMeta
-
-MAX_BIND_PARAMS = 800
-
-def _chunk_rows(rows: list[dict], cols_per_row: int, max_bind_params: int) -> Iterable[list[dict]]:
-    if not rows:
-        return []
-    rows_per_stmt = max(1, max_bind_params // max(1, cols_per_row))
-    for i in range(0, len(rows), rows_per_stmt):
-        yield rows[i:i + rows_per_stmt]
-
-def _iter_chunks(seq, n: int):
-    for i in range(0, len(seq), n):
-        yield seq[i:i + n]
-
-def _rows_per_stmt(cols: int) -> int:
-    return max(1, MAX_BIND_PARAMS // max(1, cols))
-
-
-def seed_from_paths_batch(
-    session: Session,
-    *,
-    specs: list[dict],
-    owner_id: str = "",
-) -> dict:
-    """Each spec is a dict with keys:
-      - abs_path: str
-      - size_bytes: int
-      - mtime_ns: int
-      - info_name: str
-      - tags: list[str]
-      - fname: Optional[str]
-    """
-    if not specs:
-        return {"inserted_infos": 0, "won_states": 0, "lost_states": 0}
-
-    now = utcnow()
-    asset_rows: list[dict] = []
-    state_rows: list[dict] = []
-    path_to_asset: dict[str, str] = {}
-    asset_to_info: dict[str, dict] = {}  # asset_id -> prepared info row
-    path_list: list[str] = []
-
-    for sp in specs:
-        ap = os.path.abspath(sp["abs_path"])
-        aid = str(uuid.uuid4())
-        iid = str(uuid.uuid4())
-        path_list.append(ap)
-        path_to_asset[ap] = aid
-
-        asset_rows.append(
-            {
-                "id": aid,
-                "hash": None,
-                "size_bytes": sp["size_bytes"],
-                "mime_type": None,
-                "created_at": now,
-            }
-        )
-        state_rows.append(
-            {
-                "asset_id": aid,
-                "file_path": ap,
-                "mtime_ns": sp["mtime_ns"],
-            }
-        )
-        asset_to_info[aid] = {
-            "id": iid,
-            "owner_id": owner_id,
-            "name": sp["info_name"],
-            "asset_id": aid,
-            "preview_id": None,
-            "user_metadata": {"filename": sp["fname"]} if sp["fname"] else None,
-            "created_at": now,
-            "updated_at": now,
-            "last_access_time": now,
-            "_tags": sp["tags"],
-            "_filename": sp["fname"],
-        }
-
-    # insert all seed Assets (hash=NULL)
-    ins_asset = sqlite.insert(Asset)
-    for chunk in _iter_chunks(asset_rows, _rows_per_stmt(5)):
-        session.execute(ins_asset, chunk)
-
-    # try to claim AssetCacheState (file_path)
-    # Insert with ON CONFLICT DO NOTHING, then query to find which paths were actually inserted
-    ins_state = (
-        sqlite.insert(AssetCacheState)
-        .on_conflict_do_nothing(index_elements=[AssetCacheState.file_path])
-    )
-    for chunk in _iter_chunks(state_rows, _rows_per_stmt(3)):
-        session.execute(ins_state, chunk)
-
-    # Query to find which of our paths won (were actually inserted)
-    winners_by_path: set[str] = set()
-    for chunk in _iter_chunks(path_list, MAX_BIND_PARAMS):
-        result = session.execute(
-            sqlalchemy.select(AssetCacheState.file_path)
-            .where(AssetCacheState.file_path.in_(chunk))
-            .where(AssetCacheState.asset_id.in_([path_to_asset[p] for p in chunk]))
-        )
-        winners_by_path.update(result.scalars().all())
-
-    all_paths_set = set(path_list)
-    losers_by_path = all_paths_set - winners_by_path
-    lost_assets = [path_to_asset[p] for p in losers_by_path]
-    if lost_assets:  # losers get their Asset removed
-        for id_chunk in _iter_chunks(lost_assets, MAX_BIND_PARAMS):
-            session.execute(sqlalchemy.delete(Asset).where(Asset.id.in_(id_chunk)))
-
-    if not winners_by_path:
-        return {"inserted_infos": 0, "won_states": 0, "lost_states": len(losers_by_path)}
-
-    # insert AssetInfo only for winners
-    # Insert with ON CONFLICT DO NOTHING, then query to find which were actually inserted
-    winner_info_rows = [asset_to_info[path_to_asset[p]] for p in winners_by_path]
-    ins_info = (
-        sqlite.insert(AssetInfo)
-        .on_conflict_do_nothing(index_elements=[AssetInfo.asset_id, AssetInfo.owner_id, AssetInfo.name])
-    )
-    for chunk in _iter_chunks(winner_info_rows, _rows_per_stmt(9)):
-        session.execute(ins_info, chunk)
-
-    # Query to find which info rows were actually inserted (by matching our generated IDs)
-    all_info_ids = [row["id"] for row in winner_info_rows]
-    inserted_info_ids: set[str] = set()
-    for chunk in _iter_chunks(all_info_ids, MAX_BIND_PARAMS):
-        result = session.execute(
-            sqlalchemy.select(AssetInfo.id).where(AssetInfo.id.in_(chunk))
-        )
-        inserted_info_ids.update(result.scalars().all())
-
-    # build and insert tag + meta rows for the AssetInfo
-    tag_rows: list[dict] = []
-    meta_rows: list[dict] = []
-    if inserted_info_ids:
-        for row in winner_info_rows:
-            iid = row["id"]
-            if iid not in inserted_info_ids:
-                continue
-            for t in row["_tags"]:
-                tag_rows.append({
-                    "asset_info_id": iid,
-                    "tag_name": t,
-                    "origin": "automatic",
-                    "added_at": now,
-                })
-            if row["_filename"]:
-                meta_rows.append(
-                    {
-                        "asset_info_id": iid,
-                        "key": "filename",
-                        "ordinal": 0,
-                        "val_str": row["_filename"],
-                        "val_num": None,
-                        "val_bool": None,
-                        "val_json": None,
-                    }
-                )
-
-    bulk_insert_tags_and_meta(session, tag_rows=tag_rows, meta_rows=meta_rows, max_bind_params=MAX_BIND_PARAMS)
-    return {
-        "inserted_infos": len(inserted_info_ids),
-        "won_states": len(winners_by_path),
-        "lost_states": len(losers_by_path),
-    }
-
-
-def bulk_insert_tags_and_meta(
-    session: Session,
-    *,
-    tag_rows: list[dict],
-    meta_rows: list[dict],
-    max_bind_params: int,
-) -> None:
-    """Batch insert into asset_info_tags and asset_info_meta with ON CONFLICT DO NOTHING.
-    - tag_rows keys: asset_info_id, tag_name, origin, added_at
-    - meta_rows keys: asset_info_id, key, ordinal, val_str, val_num, val_bool, val_json
-    """
-    if tag_rows:
-        ins_links = (
-            sqlite.insert(AssetInfoTag)
-            .on_conflict_do_nothing(index_elements=[AssetInfoTag.asset_info_id, AssetInfoTag.tag_name])
-        )
-        for chunk in _chunk_rows(tag_rows, cols_per_row=4, max_bind_params=max_bind_params):
-            session.execute(ins_links, chunk)
-    if meta_rows:
-        ins_meta = (
-            sqlite.insert(AssetInfoMeta)
-            .on_conflict_do_nothing(
-                index_elements=[AssetInfoMeta.asset_info_id, AssetInfoMeta.key, AssetInfoMeta.ordinal]
-            )
-        )
-        for chunk in _chunk_rows(meta_rows, cols_per_row=7, max_bind_params=max_bind_params):
-            session.execute(ins_meta, chunk)

app/assets/database/models.py

@@ -2,8 +2,8 @@ from __future__ import annotations
 
 import uuid
 from datetime import datetime
-
 from typing import Any
+
 from sqlalchemy import (
     JSON,
     BigInteger,
@@ -16,102 +16,102 @@ from sqlalchemy import (
     Numeric,
     String,
     Text,
-    UniqueConstraint,
 )
 from sqlalchemy.orm import Mapped, foreign, mapped_column, relationship
 
-from app.assets.helpers import utcnow
-from app.database.models import to_dict, Base
+from app.assets.helpers import get_utc_now
+from app.database.models import Base
 
 
 class Asset(Base):
     __tablename__ = "assets"
 
-    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
+    id: Mapped[str] = mapped_column(
+        String(36), primary_key=True, default=lambda: str(uuid.uuid4())
+    )
     hash: Mapped[str | None] = mapped_column(String(256), nullable=True)
     size_bytes: Mapped[int] = mapped_column(BigInteger, nullable=False, default=0)
     mime_type: Mapped[str | None] = mapped_column(String(255))
     created_at: Mapped[datetime] = mapped_column(
-        DateTime(timezone=False), nullable=False, default=utcnow
+        DateTime(timezone=False), nullable=False, default=get_utc_now
     )
 
-    infos: Mapped[list[AssetInfo]] = relationship(
-        "AssetInfo",
+    references: Mapped[list[AssetReference]] = relationship(
+        "AssetReference",
         back_populates="asset",
-        primaryjoin=lambda: Asset.id == foreign(AssetInfo.asset_id),
-        foreign_keys=lambda: [AssetInfo.asset_id],
+        primaryjoin=lambda: Asset.id == foreign(AssetReference.asset_id),
+        foreign_keys=lambda: [AssetReference.asset_id],
         cascade="all,delete-orphan",
         passive_deletes=True,
     )
 
-    preview_of: Mapped[list[AssetInfo]] = relationship(
-        "AssetInfo",
+    preview_of: Mapped[list[AssetReference]] = relationship(
+        "AssetReference",
         back_populates="preview_asset",
-        primaryjoin=lambda: Asset.id == foreign(AssetInfo.preview_id),
-        foreign_keys=lambda: [AssetInfo.preview_id],
+        primaryjoin=lambda: Asset.id == foreign(AssetReference.preview_id),
+        foreign_keys=lambda: [AssetReference.preview_id],
         viewonly=True,
     )
 
-    cache_states: Mapped[list[AssetCacheState]] = relationship(
-        back_populates="asset",
-        cascade="all, delete-orphan",
-        passive_deletes=True,
-    )
-
     __table_args__ = (
         Index("uq_assets_hash", "hash", unique=True),
         Index("ix_assets_mime_type", "mime_type"),
         CheckConstraint("size_bytes >= 0", name="ck_assets_size_nonneg"),
     )
 
-    def to_dict(self, include_none: bool = False) -> dict[str, Any]:
-        return to_dict(self, include_none=include_none)
-
     def __repr__(self) -> str:
         return f"<Asset id={self.id} hash={(self.hash or '')[:12]}>"
 
 
-class AssetCacheState(Base):
-    __tablename__ = "asset_cache_state"
+class AssetReference(Base):
+    """Unified model combining file cache state and user-facing metadata.
 
-    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
-    asset_id: Mapped[str] = mapped_column(String(36), ForeignKey("assets.id", ondelete="CASCADE"), nullable=False)
-    file_path: Mapped[str] = mapped_column(Text, nullable=False)
-    mtime_ns: Mapped[int | None] = mapped_column(BigInteger, nullable=True)
-    needs_verify: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    Each row represents either:
+    - A filesystem reference (file_path is set) with cache state
+    - An API-created reference (file_path is NULL) without cache state
+    """
 
-    asset: Mapped[Asset] = relationship(back_populates="cache_states")
+    __tablename__ = "asset_references"
 
-    __table_args__ = (
-        Index("ix_asset_cache_state_file_path", "file_path"),
-        Index("ix_asset_cache_state_asset_id", "asset_id"),
-        CheckConstraint("(mtime_ns IS NULL) OR (mtime_ns >= 0)", name="ck_acs_mtime_nonneg"),
-        UniqueConstraint("file_path", name="uq_asset_cache_state_file_path"),
+    id: Mapped[str] = mapped_column(
+        String(36), primary_key=True, default=lambda: str(uuid.uuid4())
+    )
+    asset_id: Mapped[str] = mapped_column(
+        String(36), ForeignKey("assets.id", ondelete="CASCADE"), nullable=False
     )
 
-    def to_dict(self, include_none: bool = False) -> dict[str, Any]:
-        return to_dict(self, include_none=include_none)
+    # Cache state fields (from former AssetCacheState)
+    file_path: Mapped[str | None] = mapped_column(Text, nullable=True)
+    mtime_ns: Mapped[int | None] = mapped_column(BigInteger, nullable=True)
+    needs_verify: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    is_missing: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    enrichment_level: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
 
-    def __repr__(self) -> str:
-        return f"<AssetCacheState id={self.id} asset_id={self.asset_id} path={self.file_path!r}>"
-
-
-class AssetInfo(Base):
-    __tablename__ = "assets_info"
-
-    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
+    # Info fields (from former AssetInfo)
     owner_id: Mapped[str] = mapped_column(String(128), nullable=False, default="")
     name: Mapped[str] = mapped_column(String(512), nullable=False)
-    asset_id: Mapped[str] = mapped_column(String(36), ForeignKey("assets.id", ondelete="RESTRICT"), nullable=False)
-    preview_id: Mapped[str | None] = mapped_column(String(36), ForeignKey("assets.id", ondelete="SET NULL"))
-    user_metadata: Mapped[dict[str, Any] | None] = mapped_column(JSON(none_as_null=True))
-    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=False), nullable=False, default=utcnow)
-    updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=False), nullable=False, default=utcnow)
-    last_access_time: Mapped[datetime] = mapped_column(DateTime(timezone=False), nullable=False, default=utcnow)
+    preview_id: Mapped[str | None] = mapped_column(
+        String(36), ForeignKey("assets.id", ondelete="SET NULL")
+    )
+    user_metadata: Mapped[dict[str, Any] | None] = mapped_column(
+        JSON(none_as_null=True)
+    )
+    created_at: Mapped[datetime] = mapped_column(
+        DateTime(timezone=False), nullable=False, default=get_utc_now
+    )
+    updated_at: Mapped[datetime] = mapped_column(
+        DateTime(timezone=False), nullable=False, default=get_utc_now
+    )
+    last_access_time: Mapped[datetime] = mapped_column(
+        DateTime(timezone=False), nullable=False, default=get_utc_now
+    )
+    deleted_at: Mapped[datetime | None] = mapped_column(
+        DateTime(timezone=False), nullable=True, default=None
+    )
 
     asset: Mapped[Asset] = relationship(
         "Asset",
-        back_populates="infos",
+        back_populates="references",
         foreign_keys=[asset_id],
         lazy="selectin",
     )
@@ -121,51 +121,59 @@ class AssetInfo(Base):
         foreign_keys=[preview_id],
     )
 
-    metadata_entries: Mapped[list[AssetInfoMeta]] = relationship(
-        back_populates="asset_info",
+    metadata_entries: Mapped[list[AssetReferenceMeta]] = relationship(
+        back_populates="asset_reference",
         cascade="all,delete-orphan",
         passive_deletes=True,
     )
 
-    tag_links: Mapped[list[AssetInfoTag]] = relationship(
-        back_populates="asset_info",
+    tag_links: Mapped[list[AssetReferenceTag]] = relationship(
+        back_populates="asset_reference",
         cascade="all,delete-orphan",
         passive_deletes=True,
-        overlaps="tags,asset_infos",
+        overlaps="tags,asset_references",
     )
 
     tags: Mapped[list[Tag]] = relationship(
-        secondary="asset_info_tags",
-        back_populates="asset_infos",
+        secondary="asset_reference_tags",
+        back_populates="asset_references",
         lazy="selectin",
         viewonly=True,
-        overlaps="tag_links,asset_info_links,asset_infos,tag",
+        overlaps="tag_links,asset_reference_links,asset_references,tag",
     )
 
     __table_args__ = (
-        UniqueConstraint("asset_id", "owner_id", "name", name="uq_assets_info_asset_owner_name"),
-        Index("ix_assets_info_owner_name", "owner_id", "name"),
-        Index("ix_assets_info_owner_id", "owner_id"),
-        Index("ix_assets_info_asset_id", "asset_id"),
-        Index("ix_assets_info_name", "name"),
-        Index("ix_assets_info_created_at", "created_at"),
-        Index("ix_assets_info_last_access_time", "last_access_time"),
+        Index("uq_asset_references_file_path", "file_path", unique=True),
+        Index("ix_asset_references_asset_id", "asset_id"),
+        Index("ix_asset_references_owner_id", "owner_id"),
+        Index("ix_asset_references_name", "name"),
+        Index("ix_asset_references_is_missing", "is_missing"),
+        Index("ix_asset_references_enrichment_level", "enrichment_level"),
+        Index("ix_asset_references_created_at", "created_at"),
+        Index("ix_asset_references_last_access_time", "last_access_time"),
+        Index("ix_asset_references_deleted_at", "deleted_at"),
+        Index("ix_asset_references_owner_name", "owner_id", "name"),
+        CheckConstraint(
+            "(mtime_ns IS NULL) OR (mtime_ns >= 0)", name="ck_ar_mtime_nonneg"
+        ),
+        CheckConstraint(
+            "enrichment_level >= 0 AND enrichment_level <= 2",
+            name="ck_ar_enrichment_level_range",
+        ),
     )
 
-    def to_dict(self, include_none: bool = False) -> dict[str, Any]:
-        data = to_dict(self, include_none=include_none)
-        data["tags"] = [t.name for t in self.tags]
-        return data
-
     def __repr__(self) -> str:
-        return f"<AssetInfo id={self.id} name={self.name!r} asset_id={self.asset_id}>"
+        path_part = f" path={self.file_path!r}" if self.file_path else ""
+        return f"<AssetReference id={self.id} name={self.name!r}{path_part}>"
 
 
-class AssetInfoMeta(Base):
-    __tablename__ = "asset_info_meta"
+class AssetReferenceMeta(Base):
+    __tablename__ = "asset_reference_meta"
 
-    asset_info_id: Mapped[str] = mapped_column(
-        String(36), ForeignKey("assets_info.id", ondelete="CASCADE"), primary_key=True
+    asset_reference_id: Mapped[str] = mapped_column(
+        String(36),
+        ForeignKey("asset_references.id", ondelete="CASCADE"),
+        primary_key=True,
     )
     key: Mapped[str] = mapped_column(String(256), primary_key=True)
     ordinal: Mapped[int] = mapped_column(Integer, primary_key=True, default=0)
@@ -175,36 +183,40 @@ class AssetInfoMeta(Base):
     val_bool: Mapped[bool | None] = mapped_column(Boolean, nullable=True)
     val_json: Mapped[Any | None] = mapped_column(JSON(none_as_null=True), nullable=True)
 
-    asset_info: Mapped[AssetInfo] = relationship(back_populates="metadata_entries")
+    asset_reference: Mapped[AssetReference] = relationship(
+        back_populates="metadata_entries"
+    )
 
     __table_args__ = (
-        Index("ix_asset_info_meta_key", "key"),
-        Index("ix_asset_info_meta_key_val_str", "key", "val_str"),
-        Index("ix_asset_info_meta_key_val_num", "key", "val_num"),
-        Index("ix_asset_info_meta_key_val_bool", "key", "val_bool"),
+        Index("ix_asset_reference_meta_key", "key"),
+        Index("ix_asset_reference_meta_key_val_str", "key", "val_str"),
+        Index("ix_asset_reference_meta_key_val_num", "key", "val_num"),
+        Index("ix_asset_reference_meta_key_val_bool", "key", "val_bool"),
     )
 
 
-class AssetInfoTag(Base):
-    __tablename__ = "asset_info_tags"
+class AssetReferenceTag(Base):
+    __tablename__ = "asset_reference_tags"
 
-    asset_info_id: Mapped[str] = mapped_column(
-        String(36), ForeignKey("assets_info.id", ondelete="CASCADE"), primary_key=True
+    asset_reference_id: Mapped[str] = mapped_column(
+        String(36),
+        ForeignKey("asset_references.id", ondelete="CASCADE"),
+        primary_key=True,
     )
     tag_name: Mapped[str] = mapped_column(
         String(512), ForeignKey("tags.name", ondelete="RESTRICT"), primary_key=True
     )
     origin: Mapped[str] = mapped_column(String(32), nullable=False, default="manual")
     added_at: Mapped[datetime] = mapped_column(
-        DateTime(timezone=False), nullable=False, default=utcnow
+        DateTime(timezone=False), nullable=False, default=get_utc_now
     )
 
-    asset_info: Mapped[AssetInfo] = relationship(back_populates="tag_links")
-    tag: Mapped[Tag] = relationship(back_populates="asset_info_links")
+    asset_reference: Mapped[AssetReference] = relationship(back_populates="tag_links")
+    tag: Mapped[Tag] = relationship(back_populates="asset_reference_links")
 
     __table_args__ = (
-        Index("ix_asset_info_tags_tag_name", "tag_name"),
-        Index("ix_asset_info_tags_asset_info_id", "asset_info_id"),
+        Index("ix_asset_reference_tags_tag_name", "tag_name"),
+        Index("ix_asset_reference_tags_asset_reference_id", "asset_reference_id"),
     )
 
 
@@ -214,20 +226,18 @@ class Tag(Base):
     name: Mapped[str] = mapped_column(String(512), primary_key=True)
     tag_type: Mapped[str] = mapped_column(String(32), nullable=False, default="user")
 
-    asset_info_links: Mapped[list[AssetInfoTag]] = relationship(
+    asset_reference_links: Mapped[list[AssetReferenceTag]] = relationship(
         back_populates="tag",
-        overlaps="asset_infos,tags",
+        overlaps="asset_references,tags",
     )
-    asset_infos: Mapped[list[AssetInfo]] = relationship(
-        secondary="asset_info_tags",
+    asset_references: Mapped[list[AssetReference]] = relationship(
+        secondary="asset_reference_tags",
         back_populates="tags",
         viewonly=True,
-        overlaps="asset_info_links,tag_links,tags,asset_info",
+        overlaps="asset_reference_links,tag_links,tags,asset_reference",
     )
 
-    __table_args__ = (
-        Index("ix_tags_tag_type", "tag_type"),
-    )
+    __table_args__ = (Index("ix_tags_tag_type", "tag_type"),)
 
     def __repr__(self) -> str:
         return f"<Tag {self.name}>"

app/assets/database/queries.py

@@ -1,976 +0,0 @@
-import os
-import logging
-import sqlalchemy as sa
-from collections import defaultdict
-from datetime import datetime
-from typing import Iterable, Any
-from sqlalchemy import select, delete, exists, func
-from sqlalchemy.dialects import sqlite
-from sqlalchemy.exc import IntegrityError
-from sqlalchemy.orm import Session, contains_eager, noload
-from app.assets.database.models import Asset, AssetInfo, AssetCacheState, AssetInfoMeta, AssetInfoTag, Tag
-from app.assets.helpers import (
-    compute_relative_filename, escape_like_prefix, normalize_tags, project_kv, utcnow
-)
-from typing import Sequence
-
-
-def visible_owner_clause(owner_id: str) -> sa.sql.ClauseElement:
-    """Build owner visibility predicate for reads. Owner-less rows are visible to everyone."""
-    owner_id = (owner_id or "").strip()
-    if owner_id == "":
-        return AssetInfo.owner_id == ""
-    return AssetInfo.owner_id.in_(["", owner_id])
-
-
-def pick_best_live_path(states: Sequence[AssetCacheState]) -> str:
-    """
-    Return the best on-disk path among cache states:
-      1) Prefer a path that exists with needs_verify == False (already verified).
-      2) Otherwise, pick the first path that exists.
-      3) Otherwise return empty string.
-    """
-    alive = [s for s in states if getattr(s, "file_path", None) and os.path.isfile(s.file_path)]
-    if not alive:
-        return ""
-    for s in alive:
-        if not getattr(s, "needs_verify", False):
-            return s.file_path
-    return alive[0].file_path
-
-
-def apply_tag_filters(
-    stmt: sa.sql.Select,
-    include_tags: Sequence[str] | None = None,
-    exclude_tags: Sequence[str] | None = None,
-) -> sa.sql.Select:
-    """include_tags: every tag must be present; exclude_tags: none may be present."""
-    include_tags = normalize_tags(include_tags)
-    exclude_tags = normalize_tags(exclude_tags)
-
-    if include_tags:
-        for tag_name in include_tags:
-            stmt = stmt.where(
-                exists().where(
-                    (AssetInfoTag.asset_info_id == AssetInfo.id)
-                    & (AssetInfoTag.tag_name == tag_name)
-                )
-            )
-
-    if exclude_tags:
-        stmt = stmt.where(
-            ~exists().where(
-                (AssetInfoTag.asset_info_id == AssetInfo.id)
-                & (AssetInfoTag.tag_name.in_(exclude_tags))
-            )
-        )
-    return stmt
-
-
-def apply_metadata_filter(
-    stmt: sa.sql.Select,
-    metadata_filter: dict | None = None,
-) -> sa.sql.Select:
-    """Apply filters using asset_info_meta projection table."""
-    if not metadata_filter:
-        return stmt
-
-    def _exists_for_pred(key: str, *preds) -> sa.sql.ClauseElement:
-        return sa.exists().where(
-            AssetInfoMeta.asset_info_id == AssetInfo.id,
-            AssetInfoMeta.key == key,
-            *preds,
-        )
-
-    def _exists_clause_for_value(key: str, value) -> sa.sql.ClauseElement:
-        if value is None:
-            no_row_for_key = sa.not_(
-                sa.exists().where(
-                    AssetInfoMeta.asset_info_id == AssetInfo.id,
-                    AssetInfoMeta.key == key,
-                )
-            )
-            null_row = _exists_for_pred(
-                key,
-                AssetInfoMeta.val_json.is_(None),
-                AssetInfoMeta.val_str.is_(None),
-                AssetInfoMeta.val_num.is_(None),
-                AssetInfoMeta.val_bool.is_(None),
-            )
-            return sa.or_(no_row_for_key, null_row)
-
-        if isinstance(value, bool):
-            return _exists_for_pred(key, AssetInfoMeta.val_bool == bool(value))
-        if isinstance(value, (int, float)):
-            from decimal import Decimal
-            num = value if isinstance(value, Decimal) else Decimal(str(value))
-            return _exists_for_pred(key, AssetInfoMeta.val_num == num)
-        if isinstance(value, str):
-            return _exists_for_pred(key, AssetInfoMeta.val_str == value)
-        return _exists_for_pred(key, AssetInfoMeta.val_json == value)
-
-    for k, v in metadata_filter.items():
-        if isinstance(v, list):
-            ors = [_exists_clause_for_value(k, elem) for elem in v]
-            if ors:
-                stmt = stmt.where(sa.or_(*ors))
-        else:
-            stmt = stmt.where(_exists_clause_for_value(k, v))
-    return stmt
-
-
-def asset_exists_by_hash(
-    session: Session,
-    *,
-    asset_hash: str,
-) -> bool:
-    """
-    Check if an asset with a given hash exists in database.
-    """
-    row = (
-        session.execute(
-            select(sa.literal(True)).select_from(Asset).where(Asset.hash == asset_hash).limit(1)
-        )
-    ).first()
-    return row is not None
-
-
-def asset_info_exists_for_asset_id(
-    session: Session,
-    *,
-    asset_id: str,
-) -> bool:
-    q = (
-        select(sa.literal(True))
-        .select_from(AssetInfo)
-        .where(AssetInfo.asset_id == asset_id)
-        .limit(1)
-    )
-    return (session.execute(q)).first() is not None
-
-
-def get_asset_by_hash(
-    session: Session,
-    *,
-    asset_hash: str,
-) -> Asset | None:
-    return (
-        session.execute(select(Asset).where(Asset.hash == asset_hash).limit(1))
-    ).scalars().first()
-
-
-def get_asset_info_by_id(
-    session: Session,
-    *,
-    asset_info_id: str,
-) -> AssetInfo | None:
-    return session.get(AssetInfo, asset_info_id)
-
-
-def list_asset_infos_page(
-    session: Session,
-    owner_id: str = "",
-    include_tags: Sequence[str] | None = None,
-    exclude_tags: Sequence[str] | None = None,
-    name_contains: str | None = None,
-    metadata_filter: dict | None = None,
-    limit: int = 20,
-    offset: int = 0,
-    sort: str = "created_at",
-    order: str = "desc",
-) -> tuple[list[AssetInfo], dict[str, list[str]], int]:
-    base = (
-        select(AssetInfo)
-        .join(Asset, Asset.id == AssetInfo.asset_id)
-        .options(contains_eager(AssetInfo.asset), noload(AssetInfo.tags))
-        .where(visible_owner_clause(owner_id))
-    )
-
-    if name_contains:
-        escaped, esc = escape_like_prefix(name_contains)
-        base = base.where(AssetInfo.name.ilike(f"%{escaped}%", escape=esc))
-
-    base = apply_tag_filters(base, include_tags, exclude_tags)
-    base = apply_metadata_filter(base, metadata_filter)
-
-    sort = (sort or "created_at").lower()
-    order = (order or "desc").lower()
-    sort_map = {
-        "name": AssetInfo.name,
-        "created_at": AssetInfo.created_at,
-        "updated_at": AssetInfo.updated_at,
-        "last_access_time": AssetInfo.last_access_time,
-        "size": Asset.size_bytes,
-    }
-    sort_col = sort_map.get(sort, AssetInfo.created_at)
-    sort_exp = sort_col.desc() if order == "desc" else sort_col.asc()
-
-    base = base.order_by(sort_exp).limit(limit).offset(offset)
-
-    count_stmt = (
-        select(sa.func.count())
-        .select_from(AssetInfo)
-        .join(Asset, Asset.id == AssetInfo.asset_id)
-        .where(visible_owner_clause(owner_id))
-    )
-    if name_contains:
-        escaped, esc = escape_like_prefix(name_contains)
-        count_stmt = count_stmt.where(AssetInfo.name.ilike(f"%{escaped}%", escape=esc))
-    count_stmt = apply_tag_filters(count_stmt, include_tags, exclude_tags)
-    count_stmt = apply_metadata_filter(count_stmt, metadata_filter)
-
-    total = int((session.execute(count_stmt)).scalar_one() or 0)
-
-    infos = (session.execute(base)).unique().scalars().all()
-
-    id_list: list[str] = [i.id for i in infos]
-    tag_map: dict[str, list[str]] = defaultdict(list)
-    if id_list:
-        rows = session.execute(
-            select(AssetInfoTag.asset_info_id, Tag.name)
-            .join(Tag, Tag.name == AssetInfoTag.tag_name)
-            .where(AssetInfoTag.asset_info_id.in_(id_list))
-            .order_by(AssetInfoTag.added_at)
-        )
-        for aid, tag_name in rows.all():
-            tag_map[aid].append(tag_name)
-
-    return infos, tag_map, total
-
-
-def fetch_asset_info_asset_and_tags(
-    session: Session,
-    asset_info_id: str,
-    owner_id: str = "",
-) -> tuple[AssetInfo, Asset, list[str]] | None:
-    stmt = (
-        select(AssetInfo, Asset, Tag.name)
-        .join(Asset, Asset.id == AssetInfo.asset_id)
-        .join(AssetInfoTag, AssetInfoTag.asset_info_id == AssetInfo.id, isouter=True)
-        .join(Tag, Tag.name == AssetInfoTag.tag_name, isouter=True)
-        .where(
-            AssetInfo.id == asset_info_id,
-            visible_owner_clause(owner_id),
-        )
-        .options(noload(AssetInfo.tags))
-        .order_by(Tag.name.asc())
-    )
-
-    rows = (session.execute(stmt)).all()
-    if not rows:
-        return None
-
-    first_info, first_asset, _ = rows[0]
-    tags: list[str] = []
-    seen: set[str] = set()
-    for _info, _asset, tag_name in rows:
-        if tag_name and tag_name not in seen:
-            seen.add(tag_name)
-            tags.append(tag_name)
-    return first_info, first_asset, tags
-
-
-def fetch_asset_info_and_asset(
-    session: Session,
-    *,
-    asset_info_id: str,
-    owner_id: str = "",
-) -> tuple[AssetInfo, Asset] | None:
-    stmt = (
-        select(AssetInfo, Asset)
-        .join(Asset, Asset.id == AssetInfo.asset_id)
-        .where(
-            AssetInfo.id == asset_info_id,
-            visible_owner_clause(owner_id),
-        )
-        .limit(1)
-        .options(noload(AssetInfo.tags))
-    )
-    row = session.execute(stmt)
-    pair = row.first()
-    if not pair:
-        return None
-    return pair[0], pair[1]
-
-def list_cache_states_by_asset_id(
-    session: Session, *, asset_id: str
-) -> Sequence[AssetCacheState]:
-    return (
-        session.execute(
-            select(AssetCacheState)
-            .where(AssetCacheState.asset_id == asset_id)
-            .order_by(AssetCacheState.id.asc())
-        )
-    ).scalars().all()
-
-
-def touch_asset_info_by_id(
-    session: Session,
-    *,
-    asset_info_id: str,
-    ts: datetime | None = None,
-    only_if_newer: bool = True,
-) -> None:
-    ts = ts or utcnow()
-    stmt = sa.update(AssetInfo).where(AssetInfo.id == asset_info_id)
-    if only_if_newer:
-        stmt = stmt.where(
-            sa.or_(AssetInfo.last_access_time.is_(None), AssetInfo.last_access_time < ts)
-        )
-    session.execute(stmt.values(last_access_time=ts))
-
-
-def create_asset_info_for_existing_asset(
-    session: Session,
-    *,
-    asset_hash: str,
-    name: str,
-    user_metadata: dict | None = None,
-    tags: Sequence[str] | None = None,
-    tag_origin: str = "manual",
-    owner_id: str = "",
-) -> AssetInfo:
-    """Create or return an existing AssetInfo for an Asset identified by asset_hash."""
-    now = utcnow()
-    asset = get_asset_by_hash(session, asset_hash=asset_hash)
-    if not asset:
-        raise ValueError(f"Unknown asset hash {asset_hash}")
-
-    info = AssetInfo(
-        owner_id=owner_id,
-        name=name,
-        asset_id=asset.id,
-        preview_id=None,
-        created_at=now,
-        updated_at=now,
-        last_access_time=now,
-    )
-    try:
-        with session.begin_nested():
-            session.add(info)
-            session.flush()
-    except IntegrityError:
-        existing = (
-            session.execute(
-                select(AssetInfo)
-                .options(noload(AssetInfo.tags))
-                .where(
-                    AssetInfo.asset_id == asset.id,
-                    AssetInfo.name == name,
-                    AssetInfo.owner_id == owner_id,
-                )
-                .limit(1)
-            )
-        ).unique().scalars().first()
-        if not existing:
-            raise RuntimeError("AssetInfo upsert failed to find existing row after conflict.")
-        return existing
-
-    # metadata["filename"] hack
-    new_meta = dict(user_metadata or {})
-    computed_filename = None
-    try:
-        p = pick_best_live_path(list_cache_states_by_asset_id(session, asset_id=asset.id))
-        if p:
-            computed_filename = compute_relative_filename(p)
-    except Exception:
-        computed_filename = None
-    if computed_filename:
-        new_meta["filename"] = computed_filename
-    if new_meta:
-        replace_asset_info_metadata_projection(
-            session,
-            asset_info_id=info.id,
-            user_metadata=new_meta,
-        )
-
-    if tags is not None:
-        set_asset_info_tags(
-            session,
-            asset_info_id=info.id,
-            tags=tags,
-            origin=tag_origin,
-        )
-    return info
-
-
-def set_asset_info_tags(
-    session: Session,
-    *,
-    asset_info_id: str,
-    tags: Sequence[str],
-    origin: str = "manual",
-) -> dict:
-    desired = normalize_tags(tags)
-
-    current = set(
-        tag_name for (tag_name,) in (
-            session.execute(select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == asset_info_id))
-        ).all()
-    )
-
-    to_add = [t for t in desired if t not in current]
-    to_remove = [t for t in current if t not in desired]
-
-    if to_add:
-        ensure_tags_exist(session, to_add, tag_type="user")
-        session.add_all([
-            AssetInfoTag(asset_info_id=asset_info_id, tag_name=t, origin=origin, added_at=utcnow())
-            for t in to_add
-        ])
-        session.flush()
-
-    if to_remove:
-        session.execute(
-            delete(AssetInfoTag)
-            .where(AssetInfoTag.asset_info_id == asset_info_id, AssetInfoTag.tag_name.in_(to_remove))
-        )
-        session.flush()
-
-    return {"added": to_add, "removed": to_remove, "total": desired}
-
-
-def replace_asset_info_metadata_projection(
-    session: Session,
-    *,
-    asset_info_id: str,
-    user_metadata: dict | None = None,
-) -> None:
-    info = session.get(AssetInfo, asset_info_id)
-    if not info:
-        raise ValueError(f"AssetInfo {asset_info_id} not found")
-
-    info.user_metadata = user_metadata or {}
-    info.updated_at = utcnow()
-    session.flush()
-
-    session.execute(delete(AssetInfoMeta).where(AssetInfoMeta.asset_info_id == asset_info_id))
-    session.flush()
-
-    if not user_metadata:
-        return
-
-    rows: list[AssetInfoMeta] = []
-    for k, v in user_metadata.items():
-        for r in project_kv(k, v):
-            rows.append(
-                AssetInfoMeta(
-                    asset_info_id=asset_info_id,
-                    key=r["key"],
-                    ordinal=int(r["ordinal"]),
-                    val_str=r.get("val_str"),
-                    val_num=r.get("val_num"),
-                    val_bool=r.get("val_bool"),
-                    val_json=r.get("val_json"),
-                )
-            )
-    if rows:
-        session.add_all(rows)
-        session.flush()
-
-
-def ingest_fs_asset(
-    session: Session,
-    *,
-    asset_hash: str,
-    abs_path: str,
-    size_bytes: int,
-    mtime_ns: int,
-    mime_type: str | None = None,
-    info_name: str | None = None,
-    owner_id: str = "",
-    preview_id: str | None = None,
-    user_metadata: dict | None = None,
-    tags: Sequence[str] = (),
-    tag_origin: str = "manual",
-    require_existing_tags: bool = False,
-) -> dict:
-    """
-    Idempotently upsert:
-      - Asset by content hash (create if missing)
-      - AssetCacheState(file_path) pointing to asset_id
-      - Optionally AssetInfo + tag links and metadata projection
-    Returns flags and ids.
-    """
-    locator = os.path.abspath(abs_path)
-    now = utcnow()
-
-    if preview_id:
-        if not session.get(Asset, preview_id):
-            preview_id = None
-
-    out: dict[str, Any] = {
-        "asset_created": False,
-        "asset_updated": False,
-        "state_created": False,
-        "state_updated": False,
-        "asset_info_id": None,
-    }
-
-    # 1) Asset by hash
-    asset = (
-        session.execute(select(Asset).where(Asset.hash == asset_hash).limit(1))
-    ).scalars().first()
-    if not asset:
-        vals = {
-            "hash": asset_hash,
-            "size_bytes": int(size_bytes),
-            "mime_type": mime_type,
-            "created_at": now,
-        }
-        res = session.execute(
-            sqlite.insert(Asset)
-            .values(**vals)
-            .on_conflict_do_nothing(index_elements=[Asset.hash])
-        )
-        if int(res.rowcount or 0) > 0:
-            out["asset_created"] = True
-        asset = (
-            session.execute(
-                select(Asset).where(Asset.hash == asset_hash).limit(1)
-            )
-        ).scalars().first()
-        if not asset:
-            raise RuntimeError("Asset row not found after upsert.")
-    else:
-        changed = False
-        if asset.size_bytes != int(size_bytes) and int(size_bytes) > 0:
-            asset.size_bytes = int(size_bytes)
-            changed = True
-        if mime_type and asset.mime_type != mime_type:
-            asset.mime_type = mime_type
-            changed = True
-        if changed:
-            out["asset_updated"] = True
-
-    # 2) AssetCacheState upsert by file_path (unique)
-    vals = {
-        "asset_id": asset.id,
-        "file_path": locator,
-        "mtime_ns": int(mtime_ns),
-    }
-    ins = (
-        sqlite.insert(AssetCacheState)
-        .values(**vals)
-        .on_conflict_do_nothing(index_elements=[AssetCacheState.file_path])
-    )
-
-    res = session.execute(ins)
-    if int(res.rowcount or 0) > 0:
-        out["state_created"] = True
-    else:
-        upd = (
-            sa.update(AssetCacheState)
-            .where(AssetCacheState.file_path == locator)
-            .where(
-                sa.or_(
-                    AssetCacheState.asset_id != asset.id,
-                    AssetCacheState.mtime_ns.is_(None),
-                    AssetCacheState.mtime_ns != int(mtime_ns),
-                )
-            )
-            .values(asset_id=asset.id, mtime_ns=int(mtime_ns))
-        )
-        res2 = session.execute(upd)
-        if int(res2.rowcount or 0) > 0:
-            out["state_updated"] = True
-
-    # 3) Optional AssetInfo + tags + metadata
-    if info_name:
-        try:
-            with session.begin_nested():
-                info = AssetInfo(
-                    owner_id=owner_id,
-                    name=info_name,
-                    asset_id=asset.id,
-                    preview_id=preview_id,
-                    created_at=now,
-                    updated_at=now,
-                    last_access_time=now,
-                )
-                session.add(info)
-                session.flush()
-                out["asset_info_id"] = info.id
-        except IntegrityError:
-            pass
-
-        existing_info = (
-            session.execute(
-                select(AssetInfo)
-                .where(
-                    AssetInfo.asset_id == asset.id,
-                    AssetInfo.name == info_name,
-                    (AssetInfo.owner_id == owner_id),
-                )
-                .limit(1)
-            )
-        ).unique().scalar_one_or_none()
-        if not existing_info:
-            raise RuntimeError("Failed to update or insert AssetInfo.")
-
-        if preview_id and existing_info.preview_id != preview_id:
-            existing_info.preview_id = preview_id
-
-        existing_info.updated_at = now
-        if existing_info.last_access_time < now:
-            existing_info.last_access_time = now
-        session.flush()
-        out["asset_info_id"] = existing_info.id
-
-        norm = [t.strip().lower() for t in (tags or []) if (t or "").strip()]
-        if norm and out["asset_info_id"] is not None:
-            if not require_existing_tags:
-                ensure_tags_exist(session, norm, tag_type="user")
-
-            existing_tag_names = set(
-                name for (name,) in (session.execute(select(Tag.name).where(Tag.name.in_(norm)))).all()
-            )
-            missing = [t for t in norm if t not in existing_tag_names]
-            if missing and require_existing_tags:
-                raise ValueError(f"Unknown tags: {missing}")
-
-            existing_links = set(
-                tag_name
-                for (tag_name,) in (
-                    session.execute(
-                        select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == out["asset_info_id"])
-                    )
-                ).all()
-            )
-            to_add = [t for t in norm if t in existing_tag_names and t not in existing_links]
-            if to_add:
-                session.add_all(
-                    [
-                        AssetInfoTag(
-                            asset_info_id=out["asset_info_id"],
-                            tag_name=t,
-                            origin=tag_origin,
-                            added_at=now,
-                        )
-                        for t in to_add
-                    ]
-                )
-                session.flush()
-
-        # metadata["filename"] hack
-        if out["asset_info_id"] is not None:
-            primary_path = pick_best_live_path(list_cache_states_by_asset_id(session, asset_id=asset.id))
-            computed_filename = compute_relative_filename(primary_path) if primary_path else None
-
-            current_meta = existing_info.user_metadata or {}
-            new_meta = dict(current_meta)
-            if user_metadata is not None:
-                for k, v in user_metadata.items():
-                    new_meta[k] = v
-            if computed_filename:
-                new_meta["filename"] = computed_filename
-
-            if new_meta != current_meta:
-                replace_asset_info_metadata_projection(
-                    session,
-                    asset_info_id=out["asset_info_id"],
-                    user_metadata=new_meta,
-                )
-
-    try:
-        remove_missing_tag_for_asset_id(session, asset_id=asset.id)
-    except Exception:
-        logging.exception("Failed to clear 'missing' tag for asset %s", asset.id)
-    return out
-
-
-def update_asset_info_full(
-    session: Session,
-    *,
-    asset_info_id: str,
-    name: str | None = None,
-    tags: Sequence[str] | None = None,
-    user_metadata: dict | None = None,
-    tag_origin: str = "manual",
-    asset_info_row: Any = None,
-) -> AssetInfo:
-    if not asset_info_row:
-        info = session.get(AssetInfo, asset_info_id)
-        if not info:
-            raise ValueError(f"AssetInfo {asset_info_id} not found")
-    else:
-        info = asset_info_row
-
-    touched = False
-    if name is not None and name != info.name:
-        info.name = name
-        touched = True
-
-    computed_filename = None
-    try:
-        p = pick_best_live_path(list_cache_states_by_asset_id(session, asset_id=info.asset_id))
-        if p:
-            computed_filename = compute_relative_filename(p)
-    except Exception:
-        computed_filename = None
-
-    if user_metadata is not None:
-        new_meta = dict(user_metadata)
-        if computed_filename:
-            new_meta["filename"] = computed_filename
-        replace_asset_info_metadata_projection(
-            session, asset_info_id=asset_info_id, user_metadata=new_meta
-        )
-        touched = True
-    else:
-        if computed_filename:
-            current_meta = info.user_metadata or {}
-            if current_meta.get("filename") != computed_filename:
-                new_meta = dict(current_meta)
-                new_meta["filename"] = computed_filename
-                replace_asset_info_metadata_projection(
-                    session, asset_info_id=asset_info_id, user_metadata=new_meta
-                )
-                touched = True
-
-    if tags is not None:
-        set_asset_info_tags(
-            session,
-            asset_info_id=asset_info_id,
-            tags=tags,
-            origin=tag_origin,
-        )
-        touched = True
-
-    if touched and user_metadata is None:
-        info.updated_at = utcnow()
-        session.flush()
-
-    return info
-
-
-def delete_asset_info_by_id(
-    session: Session,
-    *,
-    asset_info_id: str,
-    owner_id: str,
-) -> bool:
-    stmt = sa.delete(AssetInfo).where(
-        AssetInfo.id == asset_info_id,
-        visible_owner_clause(owner_id),
-    )
-    return int((session.execute(stmt)).rowcount or 0) > 0
-
-
-def list_tags_with_usage(
-    session: Session,
-    prefix: str | None = None,
-    limit: int = 100,
-    offset: int = 0,
-    include_zero: bool = True,
-    order: str = "count_desc",
-    owner_id: str = "",
-) -> tuple[list[tuple[str, str, int]], int]:
-    counts_sq = (
-        select(
-            AssetInfoTag.tag_name.label("tag_name"),
-            func.count(AssetInfoTag.asset_info_id).label("cnt"),
-        )
-        .select_from(AssetInfoTag)
-        .join(AssetInfo, AssetInfo.id == AssetInfoTag.asset_info_id)
-        .where(visible_owner_clause(owner_id))
-        .group_by(AssetInfoTag.tag_name)
-        .subquery()
-    )
-
-    q = (
-        select(
-            Tag.name,
-            Tag.tag_type,
-            func.coalesce(counts_sq.c.cnt, 0).label("count"),
-        )
-        .select_from(Tag)
-        .join(counts_sq, counts_sq.c.tag_name == Tag.name, isouter=True)
-    )
-
-    if prefix:
-        escaped, esc = escape_like_prefix(prefix.strip().lower())
-        q = q.where(Tag.name.like(escaped + "%", escape=esc))
-
-    if not include_zero:
-        q = q.where(func.coalesce(counts_sq.c.cnt, 0) > 0)
-
-    if order == "name_asc":
-        q = q.order_by(Tag.name.asc())
-    else:
-        q = q.order_by(func.coalesce(counts_sq.c.cnt, 0).desc(), Tag.name.asc())
-
-    total_q = select(func.count()).select_from(Tag)
-    if prefix:
-        escaped, esc = escape_like_prefix(prefix.strip().lower())
-        total_q = total_q.where(Tag.name.like(escaped + "%", escape=esc))
-    if not include_zero:
-        total_q = total_q.where(
-            Tag.name.in_(select(AssetInfoTag.tag_name).group_by(AssetInfoTag.tag_name))
-        )
-
-    rows = (session.execute(q.limit(limit).offset(offset))).all()
-    total = (session.execute(total_q)).scalar_one()
-
-    rows_norm = [(name, ttype, int(count or 0)) for (name, ttype, count) in rows]
-    return rows_norm, int(total or 0)
-
-
-def ensure_tags_exist(session: Session, names: Iterable[str], tag_type: str = "user") -> None:
-    wanted = normalize_tags(list(names))
-    if not wanted:
-        return
-    rows = [{"name": n, "tag_type": tag_type} for n in list(dict.fromkeys(wanted))]
-    ins = (
-        sqlite.insert(Tag)
-        .values(rows)
-        .on_conflict_do_nothing(index_elements=[Tag.name])
-    )
-    session.execute(ins)
-
-
-def get_asset_tags(session: Session, *, asset_info_id: str) -> list[str]:
-    return [
-        tag_name for (tag_name,) in (
-            session.execute(
-                select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == asset_info_id)
-            )
-        ).all()
-    ]
-
-
-def add_tags_to_asset_info(
-    session: Session,
-    *,
-    asset_info_id: str,
-    tags: Sequence[str],
-    origin: str = "manual",
-    create_if_missing: bool = True,
-    asset_info_row: Any = None,
-) -> dict:
-    if not asset_info_row:
-        info = session.get(AssetInfo, asset_info_id)
-        if not info:
-            raise ValueError(f"AssetInfo {asset_info_id} not found")
-
-    norm = normalize_tags(tags)
-    if not norm:
-        total = get_asset_tags(session, asset_info_id=asset_info_id)
-        return {"added": [], "already_present": [], "total_tags": total}
-
-    if create_if_missing:
-        ensure_tags_exist(session, norm, tag_type="user")
-
-    current = {
-        tag_name
-        for (tag_name,) in (
-            session.execute(
-                sa.select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == asset_info_id)
-            )
-        ).all()
-    }
-
-    want = set(norm)
-    to_add = sorted(want - current)
-
-    if to_add:
-        with session.begin_nested() as nested:
-            try:
-                session.add_all(
-                    [
-                        AssetInfoTag(
-                            asset_info_id=asset_info_id,
-                            tag_name=t,
-                            origin=origin,
-                            added_at=utcnow(),
-                        )
-                        for t in to_add
-                    ]
-                )
-                session.flush()
-            except IntegrityError:
-                nested.rollback()
-
-    after = set(get_asset_tags(session, asset_info_id=asset_info_id))
-    return {
-        "added": sorted(((after - current) & want)),
-        "already_present": sorted(want & current),
-        "total_tags": sorted(after),
-    }
-
-
-def remove_tags_from_asset_info(
-    session: Session,
-    *,
-    asset_info_id: str,
-    tags: Sequence[str],
-) -> dict:
-    info = session.get(AssetInfo, asset_info_id)
-    if not info:
-        raise ValueError(f"AssetInfo {asset_info_id} not found")
-
-    norm = normalize_tags(tags)
-    if not norm:
-        total = get_asset_tags(session, asset_info_id=asset_info_id)
-        return {"removed": [], "not_present": [], "total_tags": total}
-
-    existing = {
-        tag_name
-        for (tag_name,) in (
-            session.execute(
-                sa.select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == asset_info_id)
-            )
-        ).all()
-    }
-
-    to_remove = sorted(set(t for t in norm if t in existing))
-    not_present = sorted(set(t for t in norm if t not in existing))
-
-    if to_remove:
-        session.execute(
-            delete(AssetInfoTag)
-            .where(
-                AssetInfoTag.asset_info_id == asset_info_id,
-                AssetInfoTag.tag_name.in_(to_remove),
-            )
-        )
-        session.flush()
-
-    total = get_asset_tags(session, asset_info_id=asset_info_id)
-    return {"removed": to_remove, "not_present": not_present, "total_tags": total}
-
-
-def remove_missing_tag_for_asset_id(
-    session: Session,
-    *,
-    asset_id: str,
-) -> None:
-    session.execute(
-        sa.delete(AssetInfoTag).where(
-            AssetInfoTag.asset_info_id.in_(sa.select(AssetInfo.id).where(AssetInfo.asset_id == asset_id)),
-            AssetInfoTag.tag_name == "missing",
-        )
-    )
-
-
-def set_asset_info_preview(
-    session: Session,
-    *,
-    asset_info_id: str,
-    preview_asset_id: str | None = None,
-) -> None:
-    """Set or clear preview_id and bump updated_at. Raises on unknown IDs."""
-    info = session.get(AssetInfo, asset_info_id)
-    if not info:
-        raise ValueError(f"AssetInfo {asset_info_id} not found")
-
-    if preview_asset_id is None:
-        info.preview_id = None
-    else:
-        # validate preview asset exists
-        if not session.get(Asset, preview_asset_id):
-            raise ValueError(f"Preview Asset {preview_asset_id} not found")
-        info.preview_id = preview_asset_id
-
-    info.updated_at = utcnow()
-    session.flush()

app/assets/database/queries/__init__.py

@@ -0,0 +1,121 @@
+from app.assets.database.queries.asset import (
+    asset_exists_by_hash,
+    bulk_insert_assets,
+    get_asset_by_hash,
+    get_existing_asset_ids,
+    reassign_asset_references,
+    update_asset_hash_and_mime,
+    upsert_asset,
+)
+from app.assets.database.queries.asset_reference import (
+    CacheStateRow,
+    UnenrichedReferenceRow,
+    bulk_insert_references_ignore_conflicts,
+    bulk_update_enrichment_level,
+    bulk_update_is_missing,
+    bulk_update_needs_verify,
+    convert_metadata_to_rows,
+    delete_assets_by_ids,
+    delete_orphaned_seed_asset,
+    delete_reference_by_id,
+    delete_references_by_ids,
+    fetch_reference_and_asset,
+    fetch_reference_asset_and_tags,
+    get_or_create_reference,
+    get_reference_by_file_path,
+    get_reference_by_id,
+    get_reference_with_owner_check,
+    get_reference_ids_by_ids,
+    get_references_by_paths_and_asset_ids,
+    get_references_for_prefixes,
+    get_unenriched_references,
+    get_unreferenced_unhashed_asset_ids,
+    insert_reference,
+    list_references_by_asset_id,
+    list_references_page,
+    mark_references_missing_outside_prefixes,
+    reference_exists_for_asset_id,
+    restore_references_by_paths,
+    set_reference_metadata,
+    set_reference_preview,
+    soft_delete_reference_by_id,
+    update_reference_access_time,
+    update_reference_name,
+    update_reference_timestamps,
+    update_reference_updated_at,
+    upsert_reference,
+)
+from app.assets.database.queries.tags import (
+    AddTagsResult,
+    RemoveTagsResult,
+    SetTagsResult,
+    add_missing_tag_for_asset_id,
+    add_tags_to_reference,
+    bulk_insert_tags_and_meta,
+    ensure_tags_exist,
+    get_reference_tags,
+    list_tags_with_usage,
+    remove_missing_tag_for_asset_id,
+    remove_tags_from_reference,
+    set_reference_tags,
+    validate_tags_exist,
+)
+
+__all__ = [
+    "AddTagsResult",
+    "CacheStateRow",
+    "RemoveTagsResult",
+    "SetTagsResult",
+    "UnenrichedReferenceRow",
+    "add_missing_tag_for_asset_id",
+    "add_tags_to_reference",
+    "asset_exists_by_hash",
+    "bulk_insert_assets",
+    "bulk_insert_references_ignore_conflicts",
+    "bulk_insert_tags_and_meta",
+    "bulk_update_enrichment_level",
+    "bulk_update_is_missing",
+    "bulk_update_needs_verify",
+    "convert_metadata_to_rows",
+    "delete_assets_by_ids",
+    "delete_orphaned_seed_asset",
+    "delete_reference_by_id",
+    "delete_references_by_ids",
+    "ensure_tags_exist",
+    "fetch_reference_and_asset",
+    "fetch_reference_asset_and_tags",
+    "get_asset_by_hash",
+    "get_existing_asset_ids",
+    "get_or_create_reference",
+    "get_reference_by_file_path",
+    "get_reference_by_id",
+    "get_reference_with_owner_check",
+    "get_reference_ids_by_ids",
+    "get_reference_tags",
+    "get_references_by_paths_and_asset_ids",
+    "get_references_for_prefixes",
+    "get_unenriched_references",
+    "get_unreferenced_unhashed_asset_ids",
+    "insert_reference",
+    "list_references_by_asset_id",
+    "list_references_page",
+    "list_tags_with_usage",
+    "mark_references_missing_outside_prefixes",
+    "reassign_asset_references",
+    "reference_exists_for_asset_id",
+    "remove_missing_tag_for_asset_id",
+    "remove_tags_from_reference",
+    "restore_references_by_paths",
+    "set_reference_metadata",
+    "set_reference_preview",
+    "soft_delete_reference_by_id",
+    "set_reference_tags",
+    "update_asset_hash_and_mime",
+    "update_reference_access_time",
+    "update_reference_name",
+    "update_reference_timestamps",
+    "update_reference_updated_at",
+    "upsert_asset",
+    "upsert_reference",
+    "validate_tags_exist",
+]

app/assets/database/queries/asset.py

@@ -0,0 +1,140 @@
+import sqlalchemy as sa
+from sqlalchemy import select
+from sqlalchemy.dialects import sqlite
+from sqlalchemy.orm import Session
+
+from app.assets.database.models import Asset, AssetReference
+from app.assets.database.queries.common import MAX_BIND_PARAMS, calculate_rows_per_statement, iter_chunks
+
+
+def asset_exists_by_hash(
+    session: Session,
+    asset_hash: str,
+) -> bool:
+    """
+    Check if an asset with a given hash exists in database.
+    """
+    row = (
+        session.execute(
+            select(sa.literal(True))
+            .select_from(Asset)
+            .where(Asset.hash == asset_hash)
+            .limit(1)
+        )
+    ).first()
+    return row is not None
+
+
+def get_asset_by_hash(
+    session: Session,
+    asset_hash: str,
+) -> Asset | None:
+    return (
+        (session.execute(select(Asset).where(Asset.hash == asset_hash).limit(1)))
+        .scalars()
+        .first()
+    )
+
+
+def upsert_asset(
+    session: Session,
+    asset_hash: str,
+    size_bytes: int,
+    mime_type: str | None = None,
+) -> tuple[Asset, bool, bool]:
+    """Upsert an Asset by hash. Returns (asset, created, updated)."""
+    vals = {"hash": asset_hash, "size_bytes": int(size_bytes)}
+    if mime_type:
+        vals["mime_type"] = mime_type
+
+    ins = (
+        sqlite.insert(Asset)
+        .values(**vals)
+        .on_conflict_do_nothing(index_elements=[Asset.hash])
+    )
+    res = session.execute(ins)
+    created = int(res.rowcount or 0) > 0
+
+    asset = (
+        session.execute(select(Asset).where(Asset.hash == asset_hash).limit(1))
+        .scalars()
+        .first()
+    )
+    if not asset:
+        raise RuntimeError("Asset row not found after upsert.")
+
+    updated = False
+    if not created:
+        changed = False
+        if asset.size_bytes != int(size_bytes) and int(size_bytes) > 0:
+            asset.size_bytes = int(size_bytes)
+            changed = True
+        if mime_type and asset.mime_type != mime_type:
+            asset.mime_type = mime_type
+            changed = True
+        if changed:
+            updated = True
+
+    return asset, created, updated
+
+
+def bulk_insert_assets(
+    session: Session,
+    rows: list[dict],
+) -> None:
+    """Bulk insert Asset rows with ON CONFLICT DO NOTHING on hash."""
+    if not rows:
+        return
+    ins = sqlite.insert(Asset).on_conflict_do_nothing(index_elements=[Asset.hash])
+    for chunk in iter_chunks(rows, calculate_rows_per_statement(5)):
+        session.execute(ins, chunk)
+
+
+def get_existing_asset_ids(
+    session: Session,
+    asset_ids: list[str],
+) -> set[str]:
+    """Return the subset of asset_ids that exist in the database."""
+    if not asset_ids:
+        return set()
+    found: set[str] = set()
+    for chunk in iter_chunks(asset_ids, MAX_BIND_PARAMS):
+        rows = session.execute(
+            select(Asset.id).where(Asset.id.in_(chunk))
+        ).fetchall()
+        found.update(row[0] for row in rows)
+    return found
+
+
+def update_asset_hash_and_mime(
+    session: Session,
+    asset_id: str,
+    asset_hash: str | None = None,
+    mime_type: str | None = None,
+) -> bool:
+    """Update asset hash and/or mime_type. Returns True if asset was found."""
+    asset = session.get(Asset, asset_id)
+    if not asset:
+        return False
+    if asset_hash is not None:
+        asset.hash = asset_hash
+    if mime_type is not None:
+        asset.mime_type = mime_type
+    return True
+
+
+def reassign_asset_references(
+    session: Session,
+    from_asset_id: str,
+    to_asset_id: str,
+    reference_id: str,
+) -> None:
+    """Reassign a reference from one asset to another.
+
+    Used when merging a stub asset into an existing asset with the same hash.
+    """
+    ref = session.get(AssetReference, reference_id)
+    if ref and ref.asset_id == from_asset_id:
+        ref.asset_id = to_asset_id
+
+    session.flush()

app/assets/database/queries/common.py

@@ -0,0 +1,54 @@
+"""Shared utilities for database query modules."""
+
+import os
+from typing import Iterable
+
+import sqlalchemy as sa
+
+from app.assets.database.models import AssetReference
+from app.assets.helpers import escape_sql_like_string
+
+MAX_BIND_PARAMS = 800
+
+
+def calculate_rows_per_statement(cols: int) -> int:
+    """Calculate how many rows can fit in one statement given column count."""
+    return max(1, MAX_BIND_PARAMS // max(1, cols))
+
+
+def iter_chunks(seq, n: int):
+    """Yield successive n-sized chunks from seq."""
+    for i in range(0, len(seq), n):
+        yield seq[i : i + n]
+
+
+def iter_row_chunks(rows: list[dict], cols_per_row: int) -> Iterable[list[dict]]:
+    """Yield chunks of rows sized to fit within bind param limits."""
+    if not rows:
+        return
+    yield from iter_chunks(rows, calculate_rows_per_statement(cols_per_row))
+
+
+def build_visible_owner_clause(owner_id: str) -> sa.sql.ClauseElement:
+    """Build owner visibility predicate for reads.
+
+    Owner-less rows are visible to everyone.
+    """
+    owner_id = (owner_id or "").strip()
+    if owner_id == "":
+        return AssetReference.owner_id == ""
+    return AssetReference.owner_id.in_(["", owner_id])
+
+
+def build_prefix_like_conditions(
+    prefixes: list[str],
+) -> list[sa.sql.ColumnElement]:
+    """Build LIKE conditions for matching file paths under directory prefixes."""
+    conds = []
+    for p in prefixes:
+        base = os.path.abspath(p)
+        if not base.endswith(os.sep):
+            base += os.sep
+        escaped, esc = escape_sql_like_string(base)
+        conds.append(AssetReference.file_path.like(escaped + "%", escape=esc))
+    return conds

app/assets/database/queries/tags.py

@@ -0,0 +1,356 @@
+from dataclasses import dataclass
+from typing import Iterable, Sequence
+
+import sqlalchemy as sa
+from sqlalchemy import delete, func, select
+from sqlalchemy.dialects import sqlite
+from sqlalchemy.exc import IntegrityError
+from sqlalchemy.orm import Session
+
+from app.assets.database.models import (
+    AssetReference,
+    AssetReferenceMeta,
+    AssetReferenceTag,
+    Tag,
+)
+from app.assets.database.queries.common import (
+    build_visible_owner_clause,
+    iter_row_chunks,
+)
+from app.assets.helpers import escape_sql_like_string, get_utc_now, normalize_tags
+
+
+@dataclass(frozen=True)
+class AddTagsResult:
+    added: list[str]
+    already_present: list[str]
+    total_tags: list[str]
+
+
+@dataclass(frozen=True)
+class RemoveTagsResult:
+    removed: list[str]
+    not_present: list[str]
+    total_tags: list[str]
+
+
+@dataclass(frozen=True)
+class SetTagsResult:
+    added: list[str]
+    removed: list[str]
+    total: list[str]
+
+
+def validate_tags_exist(session: Session, tags: list[str]) -> None:
+    """Raise ValueError if any of the given tag names do not exist."""
+    existing_tag_names = set(
+        name
+        for (name,) in session.execute(select(Tag.name).where(Tag.name.in_(tags))).all()
+    )
+    missing = [t for t in tags if t not in existing_tag_names]
+    if missing:
+        raise ValueError(f"Unknown tags: {missing}")
+
+
+def ensure_tags_exist(
+    session: Session, names: Iterable[str], tag_type: str = "user"
+) -> None:
+    wanted = normalize_tags(list(names))
+    if not wanted:
+        return
+    rows = [{"name": n, "tag_type": tag_type} for n in list(dict.fromkeys(wanted))]
+    ins = (
+        sqlite.insert(Tag)
+        .values(rows)
+        .on_conflict_do_nothing(index_elements=[Tag.name])
+    )
+    session.execute(ins)
+
+
+def get_reference_tags(session: Session, reference_id: str) -> list[str]:
+    return [
+        tag_name
+        for (tag_name,) in (
+            session.execute(
+                select(AssetReferenceTag.tag_name).where(
+                    AssetReferenceTag.asset_reference_id == reference_id
+                )
+            )
+        ).all()
+    ]
+
+
+def set_reference_tags(
+    session: Session,
+    reference_id: str,
+    tags: Sequence[str],
+    origin: str = "manual",
+) -> SetTagsResult:
+    desired = normalize_tags(tags)
+
+    current = set(get_reference_tags(session, reference_id))
+
+    to_add = [t for t in desired if t not in current]
+    to_remove = [t for t in current if t not in desired]
+
+    if to_add:
+        ensure_tags_exist(session, to_add, tag_type="user")
+        session.add_all(
+            [
+                AssetReferenceTag(
+                    asset_reference_id=reference_id,
+                    tag_name=t,
+                    origin=origin,
+                    added_at=get_utc_now(),
+                )
+                for t in to_add
+            ]
+        )
+        session.flush()
+
+    if to_remove:
+        session.execute(
+            delete(AssetReferenceTag).where(
+                AssetReferenceTag.asset_reference_id == reference_id,
+                AssetReferenceTag.tag_name.in_(to_remove),
+            )
+        )
+        session.flush()
+
+    return SetTagsResult(added=to_add, removed=to_remove, total=desired)
+
+
+def add_tags_to_reference(
+    session: Session,
+    reference_id: str,
+    tags: Sequence[str],
+    origin: str = "manual",
+    create_if_missing: bool = True,
+    reference_row: AssetReference | None = None,
+) -> AddTagsResult:
+    if not reference_row:
+        ref = session.get(AssetReference, reference_id)
+        if not ref:
+            raise ValueError(f"AssetReference {reference_id} not found")
+
+    norm = normalize_tags(tags)
+    if not norm:
+        total = get_reference_tags(session, reference_id=reference_id)
+        return AddTagsResult(added=[], already_present=[], total_tags=total)
+
+    if create_if_missing:
+        ensure_tags_exist(session, norm, tag_type="user")
+
+    current = set(get_reference_tags(session, reference_id))
+
+    want = set(norm)
+    to_add = sorted(want - current)
+
+    if to_add:
+        with session.begin_nested() as nested:
+            try:
+                session.add_all(
+                    [
+                        AssetReferenceTag(
+                            asset_reference_id=reference_id,
+                            tag_name=t,
+                            origin=origin,
+                            added_at=get_utc_now(),
+                        )
+                        for t in to_add
+                    ]
+                )
+                session.flush()
+            except IntegrityError:
+                nested.rollback()
+
+    after = set(get_reference_tags(session, reference_id=reference_id))
+    return AddTagsResult(
+        added=sorted(((after - current) & want)),
+        already_present=sorted(want & current),
+        total_tags=sorted(after),
+    )
+
+
+def remove_tags_from_reference(
+    session: Session,
+    reference_id: str,
+    tags: Sequence[str],
+) -> RemoveTagsResult:
+    ref = session.get(AssetReference, reference_id)
+    if not ref:
+        raise ValueError(f"AssetReference {reference_id} not found")
+
+    norm = normalize_tags(tags)
+    if not norm:
+        total = get_reference_tags(session, reference_id=reference_id)
+        return RemoveTagsResult(removed=[], not_present=[], total_tags=total)
+
+    existing = set(get_reference_tags(session, reference_id))
+
+    to_remove = sorted(set(t for t in norm if t in existing))
+    not_present = sorted(set(t for t in norm if t not in existing))
+
+    if to_remove:
+        session.execute(
+            delete(AssetReferenceTag).where(
+                AssetReferenceTag.asset_reference_id == reference_id,
+                AssetReferenceTag.tag_name.in_(to_remove),
+            )
+        )
+        session.flush()
+
+    total = get_reference_tags(session, reference_id=reference_id)
+    return RemoveTagsResult(removed=to_remove, not_present=not_present, total_tags=total)
+
+
+def add_missing_tag_for_asset_id(
+    session: Session,
+    asset_id: str,
+    origin: str = "automatic",
+) -> None:
+    select_rows = (
+        sa.select(
+            AssetReference.id.label("asset_reference_id"),
+            sa.literal("missing").label("tag_name"),
+            sa.literal(origin).label("origin"),
+            sa.literal(get_utc_now()).label("added_at"),
+        )
+        .where(AssetReference.asset_id == asset_id)
+        .where(
+            sa.not_(
+                sa.exists().where(
+                    (AssetReferenceTag.asset_reference_id == AssetReference.id)
+                    & (AssetReferenceTag.tag_name == "missing")
+                )
+            )
+        )
+    )
+    session.execute(
+        sqlite.insert(AssetReferenceTag)
+        .from_select(
+            ["asset_reference_id", "tag_name", "origin", "added_at"],
+            select_rows,
+        )
+        .on_conflict_do_nothing(
+            index_elements=[
+                AssetReferenceTag.asset_reference_id,
+                AssetReferenceTag.tag_name,
+            ]
+        )
+    )
+
+
+def remove_missing_tag_for_asset_id(
+    session: Session,
+    asset_id: str,
+) -> None:
+    session.execute(
+        sa.delete(AssetReferenceTag).where(
+            AssetReferenceTag.asset_reference_id.in_(
+                sa.select(AssetReference.id).where(AssetReference.asset_id == asset_id)
+            ),
+            AssetReferenceTag.tag_name == "missing",
+        )
+    )
+
+
+def list_tags_with_usage(
+    session: Session,
+    prefix: str | None = None,
+    limit: int = 100,
+    offset: int = 0,
+    include_zero: bool = True,
+    order: str = "count_desc",
+    owner_id: str = "",
+) -> tuple[list[tuple[str, str, int]], int]:
+    counts_sq = (
+        select(
+            AssetReferenceTag.tag_name.label("tag_name"),
+            func.count(AssetReferenceTag.asset_reference_id).label("cnt"),
+        )
+        .select_from(AssetReferenceTag)
+        .join(AssetReference, AssetReference.id == AssetReferenceTag.asset_reference_id)
+        .where(build_visible_owner_clause(owner_id))
+        .where(AssetReference.deleted_at.is_(None))
+        .group_by(AssetReferenceTag.tag_name)
+        .subquery()
+    )
+
+    q = (
+        select(
+            Tag.name,
+            Tag.tag_type,
+            func.coalesce(counts_sq.c.cnt, 0).label("count"),
+        )
+        .select_from(Tag)
+        .join(counts_sq, counts_sq.c.tag_name == Tag.name, isouter=True)
+    )
+
+    if prefix:
+        escaped, esc = escape_sql_like_string(prefix.strip().lower())
+        q = q.where(Tag.name.like(escaped + "%", escape=esc))
+
+    if not include_zero:
+        q = q.where(func.coalesce(counts_sq.c.cnt, 0) > 0)
+
+    if order == "name_asc":
+        q = q.order_by(Tag.name.asc())
+    else:
+        q = q.order_by(func.coalesce(counts_sq.c.cnt, 0).desc(), Tag.name.asc())
+
+    total_q = select(func.count()).select_from(Tag)
+    if prefix:
+        escaped, esc = escape_sql_like_string(prefix.strip().lower())
+        total_q = total_q.where(Tag.name.like(escaped + "%", escape=esc))
+    if not include_zero:
+        visible_tags_sq = (
+            select(AssetReferenceTag.tag_name)
+            .join(AssetReference, AssetReference.id == AssetReferenceTag.asset_reference_id)
+            .where(build_visible_owner_clause(owner_id))
+            .where(AssetReference.deleted_at.is_(None))
+            .group_by(AssetReferenceTag.tag_name)
+        )
+        total_q = total_q.where(Tag.name.in_(visible_tags_sq))
+
+    rows = (session.execute(q.limit(limit).offset(offset))).all()
+    total = (session.execute(total_q)).scalar_one()
+
+    rows_norm = [(name, ttype, int(count or 0)) for (name, ttype, count) in rows]
+    return rows_norm, int(total or 0)
+
+
+def bulk_insert_tags_and_meta(
+    session: Session,
+    tag_rows: list[dict],
+    meta_rows: list[dict],
+) -> None:
+    """Batch insert into asset_reference_tags and asset_reference_meta.
+
+    Uses ON CONFLICT DO NOTHING.
+
+    Args:
+        session: Database session
+        tag_rows: Dicts with: asset_reference_id, tag_name, origin, added_at
+        meta_rows: Dicts with: asset_reference_id, key, ordinal, val_*
+    """
+    if tag_rows:
+        ins_tags = sqlite.insert(AssetReferenceTag).on_conflict_do_nothing(
+            index_elements=[
+                AssetReferenceTag.asset_reference_id,
+                AssetReferenceTag.tag_name,
+            ]
+        )
+        for chunk in iter_row_chunks(tag_rows, cols_per_row=4):
+            session.execute(ins_tags, chunk)
+
+    if meta_rows:
+        ins_meta = sqlite.insert(AssetReferenceMeta).on_conflict_do_nothing(
+            index_elements=[
+                AssetReferenceMeta.asset_reference_id,
+                AssetReferenceMeta.key,
+                AssetReferenceMeta.ordinal,
+            ]
+        )
+        for chunk in iter_row_chunks(meta_rows, cols_per_row=7):
+            session.execute(ins_meta, chunk)

app/assets/database/tags.py

@@ -1,62 +0,0 @@
-from typing import Iterable
-
-import sqlalchemy
-from sqlalchemy.orm import Session
-from sqlalchemy.dialects import sqlite
-
-from app.assets.helpers import normalize_tags, utcnow
-from app.assets.database.models import Tag, AssetInfoTag, AssetInfo
-
-
-def ensure_tags_exist(session: Session, names: Iterable[str], tag_type: str = "user") -> None:
-    wanted = normalize_tags(list(names))
-    if not wanted:
-        return
-    rows = [{"name": n, "tag_type": tag_type} for n in list(dict.fromkeys(wanted))]
-    ins = (
-            sqlite.insert(Tag)
-            .values(rows)
-            .on_conflict_do_nothing(index_elements=[Tag.name])
-        )
-    return session.execute(ins)
-
-def add_missing_tag_for_asset_id(
-    session: Session,
-    *,
-    asset_id: str,
-    origin: str = "automatic",
-) -> None:
-    select_rows = (
-        sqlalchemy.select(
-            AssetInfo.id.label("asset_info_id"),
-            sqlalchemy.literal("missing").label("tag_name"),
-            sqlalchemy.literal(origin).label("origin"),
-            sqlalchemy.literal(utcnow()).label("added_at"),
-        )
-        .where(AssetInfo.asset_id == asset_id)
-        .where(
-            sqlalchemy.not_(
-                sqlalchemy.exists().where((AssetInfoTag.asset_info_id == AssetInfo.id) & (AssetInfoTag.tag_name == "missing"))
-            )
-        )
-    )
-    session.execute(
-        sqlite.insert(AssetInfoTag)
-        .from_select(
-            ["asset_info_id", "tag_name", "origin", "added_at"],
-            select_rows,
-        )
-        .on_conflict_do_nothing(index_elements=[AssetInfoTag.asset_info_id, AssetInfoTag.tag_name])
-    )
-
-def remove_missing_tag_for_asset_id(
-    session: Session,
-    *,
-    asset_id: str,
-) -> None:
-    session.execute(
-        sqlalchemy.delete(AssetInfoTag).where(
-            AssetInfoTag.asset_info_id.in_(sqlalchemy.select(AssetInfo.id).where(AssetInfo.asset_id == asset_id)),
-            AssetInfoTag.tag_name == "missing",
-        )
-    )

app/assets/hashing.py

@@ -1,75 +0,0 @@
-from blake3 import blake3
-from typing import IO
-import os
-import asyncio
-
-
-DEFAULT_CHUNK = 8 * 1024 *1024 # 8MB
-
-# NOTE: this allows hashing different representations of a file-like object
-def blake3_hash(
-    fp: str | IO[bytes],
-    chunk_size: int = DEFAULT_CHUNK,
-) -> str:
-    """
-    Returns a BLAKE3 hex digest for ``fp``, which may be:
-      - a filename (str/bytes) or PathLike
-      - an open binary file object
-    If ``fp`` is a file object, it must be opened in **binary** mode and support
-    ``read``, ``seek``, and ``tell``. The function will seek to the start before
-    reading and will attempt to restore the original position afterward.
-    """
-    # duck typing to check if input is a file-like object
-    if hasattr(fp, "read"):
-        return _hash_file_obj(fp, chunk_size)
-
-    with open(os.fspath(fp), "rb") as f:
-        return _hash_file_obj(f, chunk_size)
-
-
-async def blake3_hash_async(
-    fp: str | IO[bytes],
-    chunk_size: int = DEFAULT_CHUNK,
-) -> str:
-    """Async wrapper for ``blake3_hash_sync``.
-    Uses a worker thread so the event loop remains responsive.
-    """
-    # If it is a path, open inside the worker thread to keep I/O off the loop.
-    if hasattr(fp, "read"):
-        return await asyncio.to_thread(blake3_hash, fp, chunk_size)
-
-    def _worker() -> str:
-        with open(os.fspath(fp), "rb") as f:
-            return _hash_file_obj(f, chunk_size)
-
-    return await asyncio.to_thread(_worker)
-
-
-def _hash_file_obj(file_obj: IO, chunk_size: int = DEFAULT_CHUNK) -> str:
-    """
-    Hash an already-open binary file object by streaming in chunks.
-    - Seeks to the beginning before reading (if supported).
-    - Restores the original position afterward (if tell/seek are supported).
-    """
-    if chunk_size <= 0:
-        chunk_size = DEFAULT_CHUNK
-
-    # in case file object is already open and not at the beginning, track so can be restored after hashing
-    orig_pos = file_obj.tell()
-
-    try:
-        # seek to the beginning before reading
-        if orig_pos != 0:
-            file_obj.seek(0)
-
-        h = blake3()
-        while True:
-            chunk = file_obj.read(chunk_size)
-            if not chunk:
-                break
-            h.update(chunk)
-        return h.hexdigest()
-    finally:
-        # restore original position in file object, if needed
-        if orig_pos != 0:
-            file_obj.seek(orig_pos)

app/assets/helpers.py

@@ -1,226 +1,42 @@
-import contextlib
 import os
-from decimal import Decimal
-from aiohttp import web
 from datetime import datetime, timezone
-from pathlib import Path
-from typing import Literal, Any
-
-import folder_paths
+from typing import Sequence
 
 
-RootType = Literal["models", "input", "output"]
-ALLOWED_ROOTS: tuple[RootType, ...] = ("models", "input", "output")
-
-def get_query_dict(request: web.Request) -> dict[str, Any]:
+def select_best_live_path(states: Sequence) -> str:
     """
-    Gets a dictionary of query parameters from the request.
-
-    'request.query' is a MultiMapping[str], needs to be converted to a dictionary to be validated by Pydantic.
+    Return the best on-disk path among cache states:
+      1) Prefer a path that exists with needs_verify == False (already verified).
+      2) Otherwise, pick the first path that exists.
+      3) Otherwise return empty string.
     """
-    query_dict = {
-        key: request.query.getall(key) if len(request.query.getall(key)) > 1 else request.query.get(key)
-        for key in request.query.keys()
-    }
-    return query_dict
+    alive = [
+        s
+        for s in states
+        if getattr(s, "file_path", None) and os.path.isfile(s.file_path)
+    ]
+    if not alive:
+        return ""
+    for s in alive:
+        if not getattr(s, "needs_verify", False):
+            return s.file_path
+    return alive[0].file_path
 
-def list_tree(base_dir: str) -> list[str]:
-    out: list[str] = []
-    base_abs = os.path.abspath(base_dir)
-    if not os.path.isdir(base_abs):
-        return out
-    for dirpath, _subdirs, filenames in os.walk(base_abs, topdown=True, followlinks=False):
-        for name in filenames:
-            out.append(os.path.abspath(os.path.join(dirpath, name)))
-    return out
 
-def prefixes_for_root(root: RootType) -> list[str]:
-    if root == "models":
-        bases: list[str] = []
-        for _bucket, paths in get_comfy_models_folders():
-            bases.extend(paths)
-        return [os.path.abspath(p) for p in bases]
-    if root == "input":
-        return [os.path.abspath(folder_paths.get_input_directory())]
-    if root == "output":
-        return [os.path.abspath(folder_paths.get_output_directory())]
-    return []
+def escape_sql_like_string(s: str, escape: str = "!") -> tuple[str, str]:
+    """Escapes %, _ and the escape char in a LIKE prefix.
 
-def escape_like_prefix(s: str, escape: str = "!") -> tuple[str, str]:
-    """Escapes %, _ and the escape char itself in a LIKE prefix.
-    Returns (escaped_prefix, escape_char). Caller should append '%' and pass escape=escape_char to .like().
+    Returns (escaped_prefix, escape_char).
     """
     s = s.replace(escape, escape + escape)  # escape the escape char first
     s = s.replace("%", escape + "%").replace("_", escape + "_")  # escape LIKE wildcards
     return s, escape
 
-def fast_asset_file_check(
-    *,
-    mtime_db: int | None,
-    size_db: int | None,
-    stat_result: os.stat_result,
-) -> bool:
-    if mtime_db is None:
-        return False
-    actual_mtime_ns = getattr(stat_result, "st_mtime_ns", int(stat_result.st_mtime * 1_000_000_000))
-    if int(mtime_db) != int(actual_mtime_ns):
-        return False
-    sz = int(size_db or 0)
-    if sz > 0:
-        return int(stat_result.st_size) == sz
-    return True
 
-def utcnow() -> datetime:
+def get_utc_now() -> datetime:
     """Naive UTC timestamp (no tzinfo). We always treat DB datetimes as UTC."""
     return datetime.now(timezone.utc).replace(tzinfo=None)
 
-def get_comfy_models_folders() -> list[tuple[str, list[str]]]:
-    """Build a list of (folder_name, base_paths[]) categories that are configured for model locations.
-
-    We trust `folder_paths.folder_names_and_paths` and include a category if
-    *any* of its base paths lies under the Comfy `models_dir`.
-    """
-    targets: list[tuple[str, list[str]]] = []
-    models_root = os.path.abspath(folder_paths.models_dir)
-    for name, values in folder_paths.folder_names_and_paths.items():
-        paths, _exts = values[0], values[1]  # NOTE: this prevents nodepacks that hackily edit folder_... from breaking ComfyUI
-        if any(os.path.abspath(p).startswith(models_root + os.sep) for p in paths):
-            targets.append((name, paths))
-    return targets
-
-def resolve_destination_from_tags(tags: list[str]) -> tuple[str, list[str]]:
-    """Validates and maps tags -> (base_dir, subdirs_for_fs)"""
-    root = tags[0]
-    if root == "models":
-        if len(tags) < 2:
-            raise ValueError("at least two tags required for model asset")
-        try:
-            bases = folder_paths.folder_names_and_paths[tags[1]][0]
-        except KeyError:
-            raise ValueError(f"unknown model category '{tags[1]}'")
-        if not bases:
-            raise ValueError(f"no base path configured for category '{tags[1]}'")
-        base_dir = os.path.abspath(bases[0])
-        raw_subdirs = tags[2:]
-    else:
-        base_dir = os.path.abspath(
-            folder_paths.get_input_directory() if root == "input" else folder_paths.get_output_directory()
-        )
-        raw_subdirs = tags[1:]
-    for i in raw_subdirs:
-        if i in (".", ".."):
-            raise ValueError("invalid path component in tags")
-
-    return base_dir, raw_subdirs if raw_subdirs else []
-
-def ensure_within_base(candidate: str, base: str) -> None:
-    cand_abs = os.path.abspath(candidate)
-    base_abs = os.path.abspath(base)
-    try:
-        if os.path.commonpath([cand_abs, base_abs]) != base_abs:
-            raise ValueError("destination escapes base directory")
-    except Exception:
-        raise ValueError("invalid destination path")
-
-def compute_relative_filename(file_path: str) -> str | None:
-    """
-    Return the model's path relative to the last well-known folder (the model category),
-    using forward slashes, eg:
-      /.../models/checkpoints/flux/123/flux.safetensors -> "flux/123/flux.safetensors"
-      /.../models/text_encoders/clip_g.safetensors -> "clip_g.safetensors"
-
-    For non-model paths, returns None.
-    NOTE: this is a temporary helper, used only for initializing metadata["filename"] field.
-    """
-    try:
-        root_category, rel_path = get_relative_to_root_category_path_of_asset(file_path)
-    except ValueError:
-        return None
-
-    p = Path(rel_path)
-    parts = [seg for seg in p.parts if seg not in (".", "..", p.anchor)]
-    if not parts:
-        return None
-
-    if root_category == "models":
-        # parts[0] is the category ("checkpoints", "vae", etc) – drop it
-        inside = parts[1:] if len(parts) > 1 else [parts[0]]
-        return "/".join(inside)
-    return "/".join(parts)  # input/output: keep all parts
-
-def get_relative_to_root_category_path_of_asset(file_path: str) -> tuple[Literal["input", "output", "models"], str]:
-    """Given an absolute or relative file path, determine which root category the path belongs to:
-      - 'input' if the file resides under `folder_paths.get_input_directory()`
-      - 'output' if the file resides under `folder_paths.get_output_directory()`
-      - 'models' if the file resides under any base path of categories returned by `get_comfy_models_folders()`
-
-    Returns:
-        (root_category, relative_path_inside_that_root)
-        For 'models', the relative path is prefixed with the category name:
-            e.g. ('models', 'vae/test/sub/ae.safetensors')
-
-    Raises:
-        ValueError: if the path does not belong to input, output, or configured model bases.
-    """
-    fp_abs = os.path.abspath(file_path)
-
-    def _is_within(child: str, parent: str) -> bool:
-        try:
-            return os.path.commonpath([child, parent]) == parent
-        except Exception:
-            return False
-
-    def _rel(child: str, parent: str) -> str:
-        return os.path.relpath(os.path.join(os.sep, os.path.relpath(child, parent)), os.sep)
-
-    # 1) input
-    input_base = os.path.abspath(folder_paths.get_input_directory())
-    if _is_within(fp_abs, input_base):
-        return "input", _rel(fp_abs, input_base)
-
-    # 2) output
-    output_base = os.path.abspath(folder_paths.get_output_directory())
-    if _is_within(fp_abs, output_base):
-        return "output", _rel(fp_abs, output_base)
-
-    # 3) 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:
-            base_abs = os.path.abspath(b)
-            if not _is_within(fp_abs, base_abs):
-                continue
-            cand = (len(base_abs), bucket, _rel(fp_abs, base_abs))
-            if best is None or cand[0] > best[0]:
-                best = cand
-
-    if best is not None:
-        _, bucket, rel_inside = best
-        combined = os.path.join(bucket, rel_inside)
-        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}")
-
-def get_name_and_tags_from_asset_path(file_path: str) -> tuple[str, list[str]]:
-    """Return a tuple (name, tags) derived from a filesystem path.
-
-    Semantics:
-      - Root category is determined by `get_relative_to_root_category_path_of_asset`.
-      - The returned `name` is the base filename with extension from the relative path.
-      - The returned `tags` are:
-            [root_category] + parent folders of the relative path (in order)
-        For 'models', this means:
-            file '/.../ModelsDir/vae/test_tag/ae.safetensors'
-            -> root_category='models', some_path='vae/test_tag/ae.safetensors'
-            -> name='ae.safetensors', tags=['models', 'vae', 'test_tag']
-
-    Raises:
-        ValueError: if the path does not belong to input, output, or configured model bases.
-    """
-    root_category, some_path = get_relative_to_root_category_path_of_asset(file_path)
-    p = Path(some_path)
-    parent_parts = [part for part in p.parent.parts if part not in (".", "..", p.anchor)]
-    return p.name, list(dict.fromkeys(normalize_tags([root_category, *parent_parts])))
 
 def normalize_tags(tags: list[str] | None) -> list[str]:
     """
@@ -228,85 +44,22 @@ def normalize_tags(tags: list[str] | None) -> list[str]:
       - Stripping whitespace and converting to lowercase.
       - Removing duplicates.
     """
-    return [t.strip().lower() for t in (tags or []) if (t or "").strip()]
+    return list(dict.fromkeys(t.strip().lower() for t in (tags or []) if (t or "").strip()))
 
-def collect_models_files() -> list[str]:
-    out: list[str] = []
-    for folder_name, bases in get_comfy_models_folders():
-        rel_files = folder_paths.get_filename_list(folder_name) or []
-        for rel_path in rel_files:
-            abs_path = folder_paths.get_full_path(folder_name, rel_path)
-            if not abs_path:
-                continue
-            abs_path = os.path.abspath(abs_path)
-            allowed = False
-            for b in bases:
-                base_abs = os.path.abspath(b)
-                with contextlib.suppress(Exception):
-                    if os.path.commonpath([abs_path, base_abs]) == base_abs:
-                        allowed = True
-                        break
-            if allowed:
-                out.append(abs_path)
-    return out
 
-def is_scalar(v):
-    if v is None:
-        return True
-    if isinstance(v, bool):
-        return True
-    if isinstance(v, (int, float, Decimal, str)):
-        return True
-    return False
+def validate_blake3_hash(s: str) -> str:
+    """Validate and normalize a blake3 hash string.
 
-def project_kv(key: str, value):
+    Returns canonical 'blake3:<hex>' or raises ValueError.
     """
-    Turn a metadata key/value into typed projection rows.
-    Returns list[dict] with keys:
-      key, ordinal, and one of val_str / val_num / val_bool / val_json (others None)
-    """
-    rows: list[dict] = []
-
-    def _null_row(ordinal: int) -> dict:
-        return {
-            "key": key, "ordinal": ordinal,
-            "val_str": None, "val_num": None, "val_bool": None, "val_json": None
-        }
-
-    if value is None:
-        rows.append(_null_row(0))
-        return rows
-
-    if is_scalar(value):
-        if isinstance(value, bool):
-            rows.append({"key": key, "ordinal": 0, "val_bool": bool(value)})
-        elif isinstance(value, (int, float, Decimal)):
-            num = value if isinstance(value, Decimal) else Decimal(str(value))
-            rows.append({"key": key, "ordinal": 0, "val_num": num})
-        elif isinstance(value, str):
-            rows.append({"key": key, "ordinal": 0, "val_str": value})
-        else:
-            rows.append({"key": key, "ordinal": 0, "val_json": value})
-        return rows
-
-    if isinstance(value, list):
-        if all(is_scalar(x) for x in value):
-            for i, x in enumerate(value):
-                if x is None:
-                    rows.append(_null_row(i))
-                elif isinstance(x, bool):
-                    rows.append({"key": key, "ordinal": i, "val_bool": bool(x)})
-                elif isinstance(x, (int, float, Decimal)):
-                    num = x if isinstance(x, Decimal) else Decimal(str(x))
-                    rows.append({"key": key, "ordinal": i, "val_num": num})
-                elif isinstance(x, str):
-                    rows.append({"key": key, "ordinal": i, "val_str": x})
-                else:
-                    rows.append({"key": key, "ordinal": i, "val_json": x})
-            return rows
-        for i, x in enumerate(value):
-            rows.append({"key": key, "ordinal": i, "val_json": x})
-        return rows
-
-    rows.append({"key": key, "ordinal": 0, "val_json": value})
-    return rows
+    s = s.strip().lower()
+    if not s or ":" not in s:
+        raise ValueError("hash must be 'blake3:<hex>'")
+    algo, digest = s.split(":", 1)
+    if (
+        algo != "blake3"
+        or len(digest) != 64
+        or any(c for c in digest if c not in "0123456789abcdef")
+    ):
+        raise ValueError("hash must be 'blake3:<hex>'")
+    return f"{algo}:{digest}"

app/assets/manager.py

@@ -1,516 +0,0 @@
-import os
-import mimetypes
-import contextlib
-from typing import Sequence
-
-from app.database.db import create_session
-from app.assets.api import schemas_out, schemas_in
-from app.assets.database.queries import (
-    asset_exists_by_hash,
-    asset_info_exists_for_asset_id,
-    get_asset_by_hash,
-    get_asset_info_by_id,
-    fetch_asset_info_asset_and_tags,
-    fetch_asset_info_and_asset,
-    create_asset_info_for_existing_asset,
-    touch_asset_info_by_id,
-    update_asset_info_full,
-    delete_asset_info_by_id,
-    list_cache_states_by_asset_id,
-    list_asset_infos_page,
-    list_tags_with_usage,
-    get_asset_tags,
-    add_tags_to_asset_info,
-    remove_tags_from_asset_info,
-    pick_best_live_path,
-    ingest_fs_asset,
-    set_asset_info_preview,
-)
-from app.assets.helpers import resolve_destination_from_tags, ensure_within_base
-from app.assets.database.models import Asset
-
-
-def _safe_sort_field(requested: str | None) -> str:
-    if not requested:
-        return "created_at"
-    v = requested.lower()
-    if v in {"name", "created_at", "updated_at", "size", "last_access_time"}:
-        return v
-    return "created_at"
-
-
-def _get_size_mtime_ns(path: str) -> tuple[int, int]:
-    st = os.stat(path, follow_symlinks=True)
-    return st.st_size, getattr(st, "st_mtime_ns", int(st.st_mtime * 1_000_000_000))
-
-
-def _safe_filename(name: str | None, fallback: str) -> str:
-    n = os.path.basename((name or "").strip() or fallback)
-    if n:
-        return n
-    return fallback
-
-
-def asset_exists(*, asset_hash: str) -> bool:
-    """
-    Check if an asset with a given hash exists in database.
-    """
-    with create_session() as session:
-        return asset_exists_by_hash(session, asset_hash=asset_hash)
-
-
-def list_assets(
-    *,
-    include_tags: Sequence[str] | None = None,
-    exclude_tags: Sequence[str] | None = None,
-    name_contains: str | None = None,
-    metadata_filter: dict | None = None,
-    limit: int = 20,
-    offset: int = 0,
-    sort: str = "created_at",
-    order: str = "desc",
-    owner_id: str = "",
-) -> schemas_out.AssetsList:
-    sort = _safe_sort_field(sort)
-    order = "desc" if (order or "desc").lower() not in {"asc", "desc"} else order.lower()
-
-    with create_session() as session:
-        infos, tag_map, total = list_asset_infos_page(
-            session,
-            owner_id=owner_id,
-            include_tags=include_tags,
-            exclude_tags=exclude_tags,
-            name_contains=name_contains,
-            metadata_filter=metadata_filter,
-            limit=limit,
-            offset=offset,
-            sort=sort,
-            order=order,
-        )
-
-    summaries: list[schemas_out.AssetSummary] = []
-    for info in infos:
-        asset = info.asset
-        tags = tag_map.get(info.id, [])
-        summaries.append(
-            schemas_out.AssetSummary(
-                id=info.id,
-                name=info.name,
-                asset_hash=asset.hash if asset else None,
-                size=int(asset.size_bytes) if asset else None,
-                mime_type=asset.mime_type if asset else None,
-                tags=tags,
-                created_at=info.created_at,
-                updated_at=info.updated_at,
-                last_access_time=info.last_access_time,
-            )
-        )
-
-    return schemas_out.AssetsList(
-        assets=summaries,
-        total=total,
-        has_more=(offset + len(summaries)) < total,
-    )
-
-
-def get_asset(
-    *,
-    asset_info_id: str,
-    owner_id: str = "",
-) -> schemas_out.AssetDetail:
-    with create_session() as session:
-        res = fetch_asset_info_asset_and_tags(session, asset_info_id=asset_info_id, owner_id=owner_id)
-        if not res:
-            raise ValueError(f"AssetInfo {asset_info_id} not found")
-        info, asset, tag_names = res
-        preview_id = info.preview_id
-
-    return schemas_out.AssetDetail(
-        id=info.id,
-        name=info.name,
-        asset_hash=asset.hash if asset else None,
-        size=int(asset.size_bytes) if asset and asset.size_bytes is not None else None,
-        mime_type=asset.mime_type if asset else None,
-        tags=tag_names,
-        user_metadata=info.user_metadata or {},
-        preview_id=preview_id,
-        created_at=info.created_at,
-        last_access_time=info.last_access_time,
-    )
-
-
-def resolve_asset_content_for_download(
-    *,
-    asset_info_id: str,
-    owner_id: str = "",
-) -> tuple[str, str, str]:
-    with create_session() as session:
-        pair = fetch_asset_info_and_asset(session, asset_info_id=asset_info_id, owner_id=owner_id)
-        if not pair:
-            raise ValueError(f"AssetInfo {asset_info_id} not found")
-
-        info, asset = pair
-        states = list_cache_states_by_asset_id(session, asset_id=asset.id)
-        abs_path = pick_best_live_path(states)
-        if not abs_path:
-            raise FileNotFoundError
-
-        touch_asset_info_by_id(session, asset_info_id=asset_info_id)
-        session.commit()
-
-        ctype = asset.mime_type or mimetypes.guess_type(info.name or abs_path)[0] or "application/octet-stream"
-        download_name = info.name or os.path.basename(abs_path)
-        return abs_path, ctype, download_name
-
-
-def upload_asset_from_temp_path(
-    spec: schemas_in.UploadAssetSpec,
-    *,
-    temp_path: str,
-    client_filename: str | None = None,
-    owner_id: str = "",
-    expected_asset_hash: str | None = None,
-) -> schemas_out.AssetCreated:
-    """
-    Create new asset or update existing asset from a temporary file path.
-    """
-    try:
-        # NOTE: blake3 is not required right now, so this will fail if blake3 is not installed in local environment
-        import app.assets.hashing as hashing
-        digest = hashing.blake3_hash(temp_path)
-    except Exception as e:
-        raise RuntimeError(f"failed to hash uploaded file: {e}")
-    asset_hash = "blake3:" + digest
-
-    if expected_asset_hash and asset_hash != expected_asset_hash.strip().lower():
-        raise ValueError("HASH_MISMATCH")
-
-    with create_session() as session:
-        existing = get_asset_by_hash(session, asset_hash=asset_hash)
-        if existing is not None:
-            with contextlib.suppress(Exception):
-                if temp_path and os.path.exists(temp_path):
-                    os.remove(temp_path)
-
-            display_name = _safe_filename(spec.name or (client_filename or ""), fallback=digest)
-            info = create_asset_info_for_existing_asset(
-                session,
-                asset_hash=asset_hash,
-                name=display_name,
-                user_metadata=spec.user_metadata or {},
-                tags=spec.tags or [],
-                tag_origin="manual",
-                owner_id=owner_id,
-            )
-            tag_names = get_asset_tags(session, asset_info_id=info.id)
-            session.commit()
-
-            return schemas_out.AssetCreated(
-                id=info.id,
-                name=info.name,
-                asset_hash=existing.hash,
-                size=int(existing.size_bytes) if existing.size_bytes is not None else None,
-                mime_type=existing.mime_type,
-                tags=tag_names,
-                user_metadata=info.user_metadata or {},
-                preview_id=info.preview_id,
-                created_at=info.created_at,
-                last_access_time=info.last_access_time,
-                created_new=False,
-            )
-
-    base_dir, subdirs = resolve_destination_from_tags(spec.tags)
-    dest_dir = os.path.join(base_dir, *subdirs) if subdirs else base_dir
-    os.makedirs(dest_dir, exist_ok=True)
-
-    src_for_ext = (client_filename or spec.name or "").strip()
-    _ext = os.path.splitext(os.path.basename(src_for_ext))[1] if src_for_ext else ""
-    ext = _ext if 0 < len(_ext) <= 16 else ""
-    hashed_basename = f"{digest}{ext}"
-    dest_abs = os.path.abspath(os.path.join(dest_dir, hashed_basename))
-    ensure_within_base(dest_abs, base_dir)
-
-    content_type = (
-        mimetypes.guess_type(os.path.basename(src_for_ext), strict=False)[0]
-        or mimetypes.guess_type(hashed_basename, strict=False)[0]
-        or "application/octet-stream"
-    )
-
-    try:
-        os.replace(temp_path, dest_abs)
-    except Exception as e:
-        raise RuntimeError(f"failed to move uploaded file into place: {e}")
-
-    try:
-        size_bytes, mtime_ns = _get_size_mtime_ns(dest_abs)
-    except OSError as e:
-        raise RuntimeError(f"failed to stat destination file: {e}")
-
-    with create_session() as session:
-        result = ingest_fs_asset(
-            session,
-            asset_hash=asset_hash,
-            abs_path=dest_abs,
-            size_bytes=size_bytes,
-            mtime_ns=mtime_ns,
-            mime_type=content_type,
-            info_name=_safe_filename(spec.name or (client_filename or ""), fallback=digest),
-            owner_id=owner_id,
-            preview_id=None,
-            user_metadata=spec.user_metadata or {},
-            tags=spec.tags,
-            tag_origin="manual",
-            require_existing_tags=False,
-        )
-        info_id = result["asset_info_id"]
-        if not info_id:
-            raise RuntimeError("failed to create asset metadata")
-
-        pair = fetch_asset_info_and_asset(session, asset_info_id=info_id, owner_id=owner_id)
-        if not pair:
-            raise RuntimeError("inconsistent DB state after ingest")
-        info, asset = pair
-        tag_names = get_asset_tags(session, asset_info_id=info.id)
-        created_result = schemas_out.AssetCreated(
-            id=info.id,
-            name=info.name,
-            asset_hash=asset.hash,
-            size=int(asset.size_bytes),
-            mime_type=asset.mime_type,
-            tags=tag_names,
-            user_metadata=info.user_metadata or {},
-            preview_id=info.preview_id,
-            created_at=info.created_at,
-            last_access_time=info.last_access_time,
-            created_new=result["asset_created"],
-        )
-        session.commit()
-
-    return created_result
-
-
-def update_asset(
-    *,
-    asset_info_id: str,
-    name: str | None = None,
-    tags: list[str] | None = None,
-    user_metadata: dict | None = None,
-    owner_id: str = "",
-) -> schemas_out.AssetUpdated:
-    with create_session() as session:
-        info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
-        if not info_row:
-            raise ValueError(f"AssetInfo {asset_info_id} not found")
-        if info_row.owner_id and info_row.owner_id != owner_id:
-            raise PermissionError("not owner")
-
-        info = update_asset_info_full(
-            session,
-            asset_info_id=asset_info_id,
-            name=name,
-            tags=tags,
-            user_metadata=user_metadata,
-            tag_origin="manual",
-            asset_info_row=info_row,
-        )
-
-        tag_names = get_asset_tags(session, asset_info_id=asset_info_id)
-        result = schemas_out.AssetUpdated(
-            id=info.id,
-            name=info.name,
-            asset_hash=info.asset.hash if info.asset else None,
-            tags=tag_names,
-            user_metadata=info.user_metadata or {},
-            updated_at=info.updated_at,
-        )
-        session.commit()
-
-    return result
-
-
-def set_asset_preview(
-    *,
-    asset_info_id: str,
-    preview_asset_id: str | None = None,
-    owner_id: str = "",
-) -> schemas_out.AssetDetail:
-    with create_session() as session:
-        info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
-        if not info_row:
-            raise ValueError(f"AssetInfo {asset_info_id} not found")
-        if info_row.owner_id and info_row.owner_id != owner_id:
-            raise PermissionError("not owner")
-
-        set_asset_info_preview(
-            session,
-            asset_info_id=asset_info_id,
-            preview_asset_id=preview_asset_id,
-        )
-
-        res = fetch_asset_info_asset_and_tags(session, asset_info_id=asset_info_id, owner_id=owner_id)
-        if not res:
-            raise RuntimeError("State changed during preview update")
-        info, asset, tags = res
-        result = schemas_out.AssetDetail(
-            id=info.id,
-            name=info.name,
-            asset_hash=asset.hash if asset else None,
-            size=int(asset.size_bytes) if asset and asset.size_bytes is not None else None,
-            mime_type=asset.mime_type if asset else None,
-            tags=tags,
-            user_metadata=info.user_metadata or {},
-            preview_id=info.preview_id,
-            created_at=info.created_at,
-            last_access_time=info.last_access_time,
-        )
-        session.commit()
-
-    return result
-
-
-def delete_asset_reference(*, asset_info_id: str, owner_id: str, delete_content_if_orphan: bool = True) -> bool:
-    with create_session() as session:
-        info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
-        asset_id = info_row.asset_id if info_row else None
-        deleted = delete_asset_info_by_id(session, asset_info_id=asset_info_id, owner_id=owner_id)
-        if not deleted:
-            session.commit()
-            return False
-
-        if not delete_content_if_orphan or not asset_id:
-            session.commit()
-            return True
-
-        still_exists = asset_info_exists_for_asset_id(session, asset_id=asset_id)
-        if still_exists:
-            session.commit()
-            return True
-
-        states = list_cache_states_by_asset_id(session, asset_id=asset_id)
-        file_paths = [s.file_path for s in (states or []) if getattr(s, "file_path", None)]
-
-        asset_row = session.get(Asset, asset_id)
-        if asset_row is not None:
-            session.delete(asset_row)
-
-        session.commit()
-        for p in file_paths:
-            with contextlib.suppress(Exception):
-                if p and os.path.isfile(p):
-                    os.remove(p)
-    return True
-
-
-def create_asset_from_hash(
-    *,
-    hash_str: str,
-    name: str,
-    tags: list[str] | None = None,
-    user_metadata: dict | None = None,
-    owner_id: str = "",
-) -> schemas_out.AssetCreated | None:
-    canonical = hash_str.strip().lower()
-    with create_session() as session:
-        asset = get_asset_by_hash(session, asset_hash=canonical)
-        if not asset:
-            return None
-
-        info = create_asset_info_for_existing_asset(
-            session,
-            asset_hash=canonical,
-            name=_safe_filename(name, fallback=canonical.split(":", 1)[1]),
-            user_metadata=user_metadata or {},
-            tags=tags or [],
-            tag_origin="manual",
-            owner_id=owner_id,
-        )
-        tag_names = get_asset_tags(session, asset_info_id=info.id)
-        result = schemas_out.AssetCreated(
-            id=info.id,
-            name=info.name,
-            asset_hash=asset.hash,
-            size=int(asset.size_bytes),
-            mime_type=asset.mime_type,
-            tags=tag_names,
-            user_metadata=info.user_metadata or {},
-            preview_id=info.preview_id,
-            created_at=info.created_at,
-            last_access_time=info.last_access_time,
-            created_new=False,
-        )
-        session.commit()
-
-    return result
-
-
-def add_tags_to_asset(
-    *,
-    asset_info_id: str,
-    tags: list[str],
-    origin: str = "manual",
-    owner_id: str = "",
-) -> schemas_out.TagsAdd:
-    with create_session() as session:
-        info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
-        if not info_row:
-            raise ValueError(f"AssetInfo {asset_info_id} not found")
-        if info_row.owner_id and info_row.owner_id != owner_id:
-            raise PermissionError("not owner")
-        data = add_tags_to_asset_info(
-            session,
-            asset_info_id=asset_info_id,
-            tags=tags,
-            origin=origin,
-            create_if_missing=True,
-            asset_info_row=info_row,
-        )
-        session.commit()
-    return schemas_out.TagsAdd(**data)
-
-
-def remove_tags_from_asset(
-    *,
-    asset_info_id: str,
-    tags: list[str],
-    owner_id: str = "",
-) -> schemas_out.TagsRemove:
-    with create_session() as session:
-        info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
-        if not info_row:
-            raise ValueError(f"AssetInfo {asset_info_id} not found")
-        if info_row.owner_id and info_row.owner_id != owner_id:
-            raise PermissionError("not owner")
-
-        data = remove_tags_from_asset_info(
-            session,
-            asset_info_id=asset_info_id,
-            tags=tags,
-        )
-        session.commit()
-    return schemas_out.TagsRemove(**data)
-
-
-def list_tags(
-    prefix: str | None = None,
-    limit: int = 100,
-    offset: int = 0,
-    order: str = "count_desc",
-    include_zero: bool = True,
-    owner_id: str = "",
-) -> schemas_out.TagsList:
-    limit = max(1, min(1000, limit))
-    offset = max(0, offset)
-
-    with create_session() as session:
-        rows, total = list_tags_with_usage(
-            session,
-            prefix=prefix,
-            limit=limit,
-            offset=offset,
-            include_zero=include_zero,
-            order=order,
-            owner_id=owner_id,
-        )
-
-    tags = [schemas_out.TagUsage(name=name, count=count, type=tag_type) for (name, tag_type, count) in rows]
-    return schemas_out.TagsList(tags=tags, total=total, has_more=(offset + len(tags)) < total)

app/assets/scanner.py

@@ -1,263 +1,569 @@
-import contextlib
-import time
 import logging
 import os
-import sqlalchemy
+from pathlib import Path
+from typing import Callable, Literal, TypedDict
 
 import folder_paths
-from app.database.db import create_session, dependencies_available
-from app.assets.helpers import (
-    collect_models_files, compute_relative_filename, fast_asset_file_check, get_name_and_tags_from_asset_path,
-    list_tree,prefixes_for_root, escape_like_prefix,
-    RootType
+from app.assets.database.queries import (
+    add_missing_tag_for_asset_id,
+    bulk_update_enrichment_level,
+    bulk_update_is_missing,
+    bulk_update_needs_verify,
+    delete_orphaned_seed_asset,
+    delete_references_by_ids,
+    ensure_tags_exist,
+    get_asset_by_hash,
+    get_references_for_prefixes,
+    get_unenriched_references,
+    mark_references_missing_outside_prefixes,
+    reassign_asset_references,
+    remove_missing_tag_for_asset_id,
+    set_reference_metadata,
+    update_asset_hash_and_mime,
 )
-from app.assets.database.tags import add_missing_tag_for_asset_id, ensure_tags_exist, remove_missing_tag_for_asset_id
-from app.assets.database.bulk_ops import seed_from_paths_batch
-from app.assets.database.models import Asset, AssetCacheState, AssetInfo
+from app.assets.services.bulk_ingest import (
+    SeedAssetSpec,
+    batch_insert_seed_assets,
+)
+from app.assets.services.file_utils import (
+    get_mtime_ns,
+    is_visible,
+    list_files_recursively,
+    verify_file_unchanged,
+)
+from app.assets.services.hashing import HashCheckpoint, compute_blake3_hash
+from app.assets.services.metadata_extract import extract_file_metadata
+from app.assets.services.path_utils import (
+    compute_relative_filename,
+    get_comfy_models_folders,
+    get_name_and_tags_from_asset_path,
+)
+from app.database.db import create_session
 
 
-def seed_assets(roots: tuple[RootType, ...], enable_logging: bool = False) -> None:
-    """
-    Scan the given roots and seed the assets into the database.
-    """
-    if not dependencies_available():
-        if enable_logging:
-            logging.warning("Database dependencies not available, skipping assets scan")
-        return
-    t_start = time.perf_counter()
-    created = 0
-    skipped_existing = 0
-    orphans_pruned = 0
-    paths: list[str] = []
-    try:
-        existing_paths: set[str] = set()
-        for r in roots:
-            try:
-                survivors: set[str] = _fast_db_consistency_pass(r, collect_existing_paths=True, update_missing_tags=True)
-                if survivors:
-                    existing_paths.update(survivors)
-            except Exception as e:
-                logging.exception("fast DB scan failed for %s: %s", r, e)
+class _RefInfo(TypedDict):
+    ref_id: str
+    file_path: str
+    exists: bool
+    stat_unchanged: bool
+    needs_verify: bool
 
-        try:
-            orphans_pruned = _prune_orphaned_assets(roots)
-        except Exception as e:
-            logging.exception("orphan pruning failed: %s", e)
 
-        if "models" in roots:
-            paths.extend(collect_models_files())
-        if "input" in roots:
-            paths.extend(list_tree(folder_paths.get_input_directory()))
-        if "output" in roots:
-            paths.extend(list_tree(folder_paths.get_output_directory()))
+class _AssetAccumulator(TypedDict):
+    hash: str | None
+    size_db: int
+    refs: list[_RefInfo]
 
-        specs: list[dict] = []
-        tag_pool: set[str] = set()
-        for p in paths:
-            abs_p = os.path.abspath(p)
-            if abs_p in existing_paths:
-                skipped_existing += 1
+
+RootType = Literal["models", "input", "output"]
+
+
+def get_prefixes_for_root(root: RootType) -> list[str]:
+    if root == "models":
+        bases: list[str] = []
+        for _bucket, paths in get_comfy_models_folders():
+            bases.extend(paths)
+        return [os.path.abspath(p) for p in bases]
+    if root == "input":
+        return [os.path.abspath(folder_paths.get_input_directory())]
+    if root == "output":
+        return [os.path.abspath(folder_paths.get_output_directory())]
+    return []
+
+
+def get_all_known_prefixes() -> list[str]:
+    """Get all known asset prefixes across all root types."""
+    all_roots: tuple[RootType, ...] = ("models", "input", "output")
+    return [p for root in all_roots for p in get_prefixes_for_root(root)]
+
+
+def collect_models_files() -> list[str]:
+    out: list[str] = []
+    for folder_name, bases in get_comfy_models_folders():
+        rel_files = folder_paths.get_filename_list(folder_name) or []
+        for rel_path in rel_files:
+            if not all(is_visible(part) for part in Path(rel_path).parts):
                 continue
-            try:
-                stat_p = os.stat(abs_p, follow_symlinks=False)
-            except OSError:
+            abs_path = folder_paths.get_full_path(folder_name, rel_path)
+            if not abs_path:
                 continue
-            # skip empty files
-            if not stat_p.st_size:
-                continue
-            name, tags = get_name_and_tags_from_asset_path(abs_p)
-            specs.append(
-                {
-                    "abs_path": abs_p,
-                    "size_bytes": stat_p.st_size,
-                    "mtime_ns": getattr(stat_p, "st_mtime_ns", int(stat_p.st_mtime * 1_000_000_000)),
-                    "info_name": name,
-                    "tags": tags,
-                    "fname": compute_relative_filename(abs_p),
-                }
-            )
-            for t in tags:
-                tag_pool.add(t)
-        # if no file specs, nothing to do
-        if not specs:
-            return
-        with create_session() as sess:
-            if tag_pool:
-                ensure_tags_exist(sess, tag_pool, tag_type="user")
-
-            result = seed_from_paths_batch(sess, specs=specs, owner_id="")
-            created += result["inserted_infos"]
-            sess.commit()
-    finally:
-        if enable_logging:
-            logging.info(
-                "Assets scan(roots=%s) completed in %.3fs (created=%d, skipped_existing=%d, orphans_pruned=%d, total_seen=%d)",
-                roots,
-                time.perf_counter() - t_start,
-                created,
-                skipped_existing,
-                orphans_pruned,
-                len(paths),
-            )
+            abs_path = os.path.abspath(abs_path)
+            allowed = False
+            abs_p = Path(abs_path)
+            for b in bases:
+                if abs_p.is_relative_to(os.path.abspath(b)):
+                    allowed = True
+                    break
+            if allowed:
+                out.append(abs_path)
+    return out
 
 
-def _prune_orphaned_assets(roots: tuple[RootType, ...]) -> int:
-    """Prune cache states outside configured prefixes, then delete orphaned seed assets."""
-    all_prefixes = [os.path.abspath(p) for r in roots for p in prefixes_for_root(r)]
-    if not all_prefixes:
-        return 0
-
-    def make_prefix_condition(prefix: str):
-        base = prefix if prefix.endswith(os.sep) else prefix + os.sep
-        escaped, esc = escape_like_prefix(base)
-        return AssetCacheState.file_path.like(escaped + "%", escape=esc)
-
-    matches_valid_prefix = sqlalchemy.or_(*[make_prefix_condition(p) for p in all_prefixes])
-
-    orphan_subq = (
-        sqlalchemy.select(Asset.id)
-        .outerjoin(AssetCacheState, AssetCacheState.asset_id == Asset.id)
-        .where(Asset.hash.is_(None), AssetCacheState.id.is_(None))
-    ).scalar_subquery()
-
-    with create_session() as sess:
-        sess.execute(sqlalchemy.delete(AssetCacheState).where(~matches_valid_prefix))
-        sess.execute(sqlalchemy.delete(AssetInfo).where(AssetInfo.asset_id.in_(orphan_subq)))
-        result = sess.execute(sqlalchemy.delete(Asset).where(Asset.id.in_(orphan_subq)))
-        sess.commit()
-        return result.rowcount
-
-
-def _fast_db_consistency_pass(
+def sync_references_with_filesystem(
+    session,
     root: RootType,
-    *,
     collect_existing_paths: bool = False,
     update_missing_tags: bool = False,
 ) -> set[str] | None:
-    """Fast DB+FS pass for a root:
-      - Toggle needs_verify per state using fast check
-      - For hashed assets with at least one fast-ok state in this root: delete stale missing states
-      - For seed assets with all states missing: delete Asset and its AssetInfos
-      - Optionally add/remove 'missing' tags based on fast-ok in this root
-      - Optionally return surviving absolute paths
+    """Reconcile asset references with filesystem for a root.
+
+    - Toggle needs_verify per reference using mtime/size stat check
+    - For hashed assets with at least one stat-unchanged ref: delete stale missing refs
+    - For seed assets with all refs missing: delete Asset and its references
+    - Optionally add/remove 'missing' tags based on stat check in this root
+    - Optionally return surviving absolute paths
+
+    Args:
+        session: Database session
+        root: Root type to scan
+        collect_existing_paths: If True, return set of surviving file paths
+        update_missing_tags: If True, update 'missing' tags based on file status
+
+    Returns:
+        Set of surviving absolute paths if collect_existing_paths=True, else None
     """
-    prefixes = prefixes_for_root(root)
+    prefixes = get_prefixes_for_root(root)
     if not prefixes:
         return set() if collect_existing_paths else None
 
-    conds = []
-    for p in prefixes:
-        base = os.path.abspath(p)
-        if not base.endswith(os.sep):
-            base += os.sep
-        escaped, esc = escape_like_prefix(base)
-        conds.append(AssetCacheState.file_path.like(escaped + "%", escape=esc))
+    rows = get_references_for_prefixes(
+        session, prefixes, include_missing=update_missing_tags
+    )
+
+    by_asset: dict[str, _AssetAccumulator] = {}
+    for row in rows:
+        acc = by_asset.get(row.asset_id)
+        if acc is None:
+            acc = {"hash": row.asset_hash, "size_db": row.size_bytes, "refs": []}
+            by_asset[row.asset_id] = acc
+
+        stat_unchanged = False
+        try:
+            exists = True
+            stat_unchanged = verify_file_unchanged(
+                mtime_db=row.mtime_ns,
+                size_db=acc["size_db"],
+                stat_result=os.stat(row.file_path, follow_symlinks=True),
+            )
+        except FileNotFoundError:
+            exists = False
+        except PermissionError:
+            exists = True
+            logging.debug("Permission denied accessing %s", row.file_path)
+        except OSError as e:
+            exists = False
+            logging.debug("OSError checking %s: %s", row.file_path, e)
+
+        acc["refs"].append(
+            {
+                "ref_id": row.reference_id,
+                "file_path": row.file_path,
+                "exists": exists,
+                "stat_unchanged": stat_unchanged,
+                "needs_verify": row.needs_verify,
+            }
+        )
+
+    to_set_verify: list[str] = []
+    to_clear_verify: list[str] = []
+    stale_ref_ids: list[str] = []
+    to_mark_missing: list[str] = []
+    to_clear_missing: list[str] = []
+    survivors: set[str] = set()
+
+    for aid, acc in by_asset.items():
+        a_hash = acc["hash"]
+        refs = acc["refs"]
+        any_unchanged = any(r["stat_unchanged"] for r in refs)
+        all_missing = all(not r["exists"] for r in refs)
+
+        for r in refs:
+            if not r["exists"]:
+                to_mark_missing.append(r["ref_id"])
+                continue
+            if r["stat_unchanged"]:
+                to_clear_missing.append(r["ref_id"])
+                if r["needs_verify"]:
+                    to_clear_verify.append(r["ref_id"])
+            if not r["stat_unchanged"] and not r["needs_verify"]:
+                to_set_verify.append(r["ref_id"])
+
+        if a_hash is None:
+            if refs and all_missing:
+                delete_orphaned_seed_asset(session, aid)
+            else:
+                for r in refs:
+                    if r["exists"]:
+                        survivors.add(os.path.abspath(r["file_path"]))
+            continue
+
+        if any_unchanged:
+            for r in refs:
+                if not r["exists"]:
+                    stale_ref_ids.append(r["ref_id"])
+            if update_missing_tags:
+                try:
+                    remove_missing_tag_for_asset_id(session, asset_id=aid)
+                except Exception as e:
+                    logging.warning(
+                        "Failed to remove missing tag for asset %s: %s", aid, e
+                    )
+        elif update_missing_tags:
+            try:
+                add_missing_tag_for_asset_id(session, asset_id=aid, origin="automatic")
+            except Exception as e:
+                logging.warning("Failed to add missing tag for asset %s: %s", aid, e)
+
+        for r in refs:
+            if r["exists"]:
+                survivors.add(os.path.abspath(r["file_path"]))
+
+    delete_references_by_ids(session, stale_ref_ids)
+    stale_set = set(stale_ref_ids)
+    to_mark_missing = [ref_id for ref_id in to_mark_missing if ref_id not in stale_set]
+    bulk_update_is_missing(session, to_mark_missing, value=True)
+    bulk_update_is_missing(session, to_clear_missing, value=False)
+    bulk_update_needs_verify(session, to_set_verify, value=True)
+    bulk_update_needs_verify(session, to_clear_verify, value=False)
+
+    return survivors if collect_existing_paths else None
+
+
+def sync_root_safely(root: RootType) -> set[str]:
+    """Sync a single root's references with the filesystem.
+
+    Returns survivors (existing paths) or empty set on failure.
+    """
+    try:
+        with create_session() as sess:
+            survivors = sync_references_with_filesystem(
+                sess,
+                root,
+                collect_existing_paths=True,
+                update_missing_tags=True,
+            )
+            sess.commit()
+            return survivors or set()
+    except Exception as e:
+        logging.exception("fast DB scan failed for %s: %s", root, e)
+        return set()
+
+
+def mark_missing_outside_prefixes_safely(prefixes: list[str]) -> int:
+    """Mark references as missing when outside the given prefixes.
+
+    This is a non-destructive soft-delete. Returns count marked or 0 on failure.
+    """
+    try:
+        with create_session() as sess:
+            count = mark_references_missing_outside_prefixes(sess, prefixes)
+            sess.commit()
+            return count
+    except Exception as e:
+        logging.exception("marking missing assets failed: %s", e)
+        return 0
+
+
+def collect_paths_for_roots(roots: tuple[RootType, ...]) -> list[str]:
+    """Collect all file paths for the given roots."""
+    paths: list[str] = []
+    if "models" in roots:
+        paths.extend(collect_models_files())
+    if "input" in roots:
+        paths.extend(list_files_recursively(folder_paths.get_input_directory()))
+    if "output" in roots:
+        paths.extend(list_files_recursively(folder_paths.get_output_directory()))
+    return paths
+
+
+def build_asset_specs(
+    paths: list[str],
+    existing_paths: set[str],
+    enable_metadata_extraction: bool = True,
+    compute_hashes: bool = False,
+) -> tuple[list[SeedAssetSpec], set[str], int]:
+    """Build asset specs from paths, returning (specs, tag_pool, skipped_count).
+
+    Args:
+        paths: List of file paths to process
+        existing_paths: Set of paths that already exist in the database
+        enable_metadata_extraction: If True, extract tier 1 & 2 metadata
+        compute_hashes: If True, compute blake3 hashes (slow for large files)
+    """
+    specs: list[SeedAssetSpec] = []
+    tag_pool: set[str] = set()
+    skipped = 0
+
+    for p in paths:
+        abs_p = os.path.abspath(p)
+        if abs_p in existing_paths:
+            skipped += 1
+            continue
+        try:
+            stat_p = os.stat(abs_p, follow_symlinks=True)
+        except OSError:
+            continue
+        if not stat_p.st_size:
+            continue
+        name, tags = get_name_and_tags_from_asset_path(abs_p)
+        rel_fname = compute_relative_filename(abs_p)
+
+        # Extract metadata (tier 1: filesystem, tier 2: safetensors header)
+        metadata = None
+        if enable_metadata_extraction:
+            metadata = extract_file_metadata(
+                abs_p,
+                stat_result=stat_p,
+                enable_safetensors=True,
+                relative_filename=rel_fname,
+            )
+
+        # Compute hash if requested
+        asset_hash: str | None = None
+        if compute_hashes:
+            try:
+                digest, _ = compute_blake3_hash(abs_p)
+                asset_hash = "blake3:" + digest
+            except Exception as e:
+                logging.warning("Failed to hash %s: %s", abs_p, e)
+
+        mime_type = metadata.content_type if metadata else None
+        specs.append(
+            {
+                "abs_path": abs_p,
+                "size_bytes": stat_p.st_size,
+                "mtime_ns": get_mtime_ns(stat_p),
+                "info_name": name,
+                "tags": tags,
+                "fname": rel_fname,
+                "metadata": metadata,
+                "hash": asset_hash,
+                "mime_type": mime_type,
+            }
+        )
+        tag_pool.update(tags)
+
+    return specs, tag_pool, skipped
+
+
+
+def insert_asset_specs(specs: list[SeedAssetSpec], tag_pool: set[str]) -> int:
+    """Insert asset specs into database, returning count of created refs."""
+    if not specs:
+        return 0
+    with create_session() as sess:
+        if tag_pool:
+            ensure_tags_exist(sess, tag_pool, tag_type="user")
+        result = batch_insert_seed_assets(sess, specs=specs, owner_id="")
+        sess.commit()
+        return result.inserted_refs
+
+
+# Enrichment level constants
+ENRICHMENT_STUB = 0  # Fast scan: path, size, mtime only
+ENRICHMENT_METADATA = 1  # Metadata extracted (safetensors header, mime type)
+ENRICHMENT_HASHED = 2  # Hash computed (blake3)
+
+
+def get_unenriched_assets_for_roots(
+    roots: tuple[RootType, ...],
+    max_level: int = ENRICHMENT_STUB,
+    limit: int = 1000,
+) -> list:
+    """Get assets that need enrichment for the given roots.
+
+    Args:
+        roots: Tuple of root types to scan
+        max_level: Maximum enrichment level to include
+        limit: Maximum number of rows to return
+
+    Returns:
+        List of UnenrichedReferenceRow
+    """
+    prefixes: list[str] = []
+    for root in roots:
+        prefixes.extend(get_prefixes_for_root(root))
+
+    if not prefixes:
+        return []
 
     with create_session() as sess:
-        rows = (
-            sess.execute(
-                sqlalchemy.select(
-                    AssetCacheState.id,
-                    AssetCacheState.file_path,
-                    AssetCacheState.mtime_ns,
-                    AssetCacheState.needs_verify,
-                    AssetCacheState.asset_id,
-                    Asset.hash,
-                    Asset.size_bytes,
-                )
-                .join(Asset, Asset.id == AssetCacheState.asset_id)
-                .where(sqlalchemy.or_(*conds))
-                .order_by(AssetCacheState.asset_id.asc(), AssetCacheState.id.asc())
+        return get_unenriched_references(
+            sess, prefixes, max_level=max_level, limit=limit
+        )
+
+
+def enrich_asset(
+    session,
+    file_path: str,
+    reference_id: str,
+    asset_id: str,
+    extract_metadata: bool = True,
+    compute_hash: bool = False,
+    interrupt_check: Callable[[], bool] | None = None,
+    hash_checkpoints: dict[str, HashCheckpoint] | None = None,
+) -> int:
+    """Enrich a single asset with metadata and/or hash.
+
+    Args:
+        session: Database session (caller manages lifecycle)
+        file_path: Absolute path to the file
+        reference_id: ID of the reference to update
+        asset_id: ID of the asset to update (for mime_type and hash)
+        extract_metadata: If True, extract safetensors header and mime type
+        compute_hash: If True, compute blake3 hash
+        interrupt_check: Optional non-blocking callable that returns True if
+            the operation should be interrupted (e.g. paused or cancelled)
+        hash_checkpoints: Optional dict for saving/restoring hash progress
+            across interruptions, keyed by file path
+
+    Returns:
+        New enrichment level achieved
+    """
+    new_level = ENRICHMENT_STUB
+
+    try:
+        stat_p = os.stat(file_path, follow_symlinks=True)
+    except OSError:
+        return new_level
+
+    rel_fname = compute_relative_filename(file_path)
+    mime_type: str | None = None
+    metadata = None
+
+    if extract_metadata:
+        metadata = extract_file_metadata(
+            file_path,
+            stat_result=stat_p,
+            enable_safetensors=True,
+            relative_filename=rel_fname,
+        )
+        if metadata:
+            mime_type = metadata.content_type
+            new_level = ENRICHMENT_METADATA
+
+    full_hash: str | None = None
+    if compute_hash:
+        try:
+            mtime_before = get_mtime_ns(stat_p)
+            size_before = stat_p.st_size
+
+            # Restore checkpoint if available and file unchanged
+            checkpoint = None
+            if hash_checkpoints is not None:
+                checkpoint = hash_checkpoints.get(file_path)
+                if checkpoint is not None:
+                    cur_stat = os.stat(file_path, follow_symlinks=True)
+                    if (checkpoint.mtime_ns != get_mtime_ns(cur_stat)
+                            or checkpoint.file_size != cur_stat.st_size):
+                        checkpoint = None
+                        hash_checkpoints.pop(file_path, None)
+                    else:
+                        mtime_before = get_mtime_ns(cur_stat)
+
+            digest, new_checkpoint = compute_blake3_hash(
+                file_path,
+                interrupt_check=interrupt_check,
+                checkpoint=checkpoint,
             )
-        ).all()
 
-        by_asset: dict[str, dict] = {}
-        for sid, fp, mtime_db, needs_verify, aid, a_hash, a_size in rows:
-            acc = by_asset.get(aid)
-            if acc is None:
-                acc = {"hash": a_hash, "size_db": int(a_size or 0), "states": []}
-                by_asset[aid] = acc
+            if digest is None:
+                # Interrupted — save checkpoint for later resumption
+                if hash_checkpoints is not None and new_checkpoint is not None:
+                    new_checkpoint.mtime_ns = mtime_before
+                    new_checkpoint.file_size = size_before
+                    hash_checkpoints[file_path] = new_checkpoint
+                return new_level
+
+            # Completed — clear any saved checkpoint
+            if hash_checkpoints is not None:
+                hash_checkpoints.pop(file_path, None)
+
+            stat_after = os.stat(file_path, follow_symlinks=True)
+            mtime_after = get_mtime_ns(stat_after)
+            if mtime_before != mtime_after:
+                logging.warning("File modified during hashing, discarding hash: %s", file_path)
+            else:
+                full_hash = f"blake3:{digest}"
+                metadata_ok = not extract_metadata or metadata is not None
+                if metadata_ok:
+                    new_level = ENRICHMENT_HASHED
+        except Exception as e:
+            logging.warning("Failed to hash %s: %s", file_path, e)
+
+    if extract_metadata and metadata:
+        user_metadata = metadata.to_user_metadata()
+        set_reference_metadata(session, reference_id, user_metadata)
+
+    if full_hash:
+        existing = get_asset_by_hash(session, full_hash)
+        if existing and existing.id != asset_id:
+            reassign_asset_references(session, asset_id, existing.id, reference_id)
+            delete_orphaned_seed_asset(session, asset_id)
+            if mime_type:
+                update_asset_hash_and_mime(session, existing.id, mime_type=mime_type)
+        else:
+            update_asset_hash_and_mime(session, asset_id, full_hash, mime_type)
+    elif mime_type:
+        update_asset_hash_and_mime(session, asset_id, mime_type=mime_type)
+
+    bulk_update_enrichment_level(session, [reference_id], new_level)
+    session.commit()
+
+    return new_level
+
+
+def enrich_assets_batch(
+    rows: list,
+    extract_metadata: bool = True,
+    compute_hash: bool = False,
+    interrupt_check: Callable[[], bool] | None = None,
+    hash_checkpoints: dict[str, HashCheckpoint] | None = None,
+) -> tuple[int, list[str]]:
+    """Enrich a batch of assets.
+
+    Uses a single DB session for the entire batch, committing after each
+    individual asset to avoid long-held transactions while eliminating
+    per-asset session creation overhead.
+
+    Args:
+        rows: List of UnenrichedReferenceRow from get_unenriched_assets_for_roots
+        extract_metadata: If True, extract metadata for each asset
+        compute_hash: If True, compute hash for each asset
+        interrupt_check: Optional non-blocking callable that returns True if
+            the operation should be interrupted (e.g. paused or cancelled)
+        hash_checkpoints: Optional dict for saving/restoring hash progress
+            across interruptions, keyed by file path
+
+    Returns:
+        Tuple of (enriched_count, failed_reference_ids)
+    """
+    enriched = 0
+    failed_ids: list[str] = []
+
+    with create_session() as sess:
+        for row in rows:
+            if interrupt_check is not None and interrupt_check():
+                break
 
-            fast_ok = False
             try:
-                exists = True
-                fast_ok = fast_asset_file_check(
-                    mtime_db=mtime_db,
-                    size_db=acc["size_db"],
-                    stat_result=os.stat(fp, follow_symlinks=True),
+                new_level = enrich_asset(
+                    sess,
+                    file_path=row.file_path,
+                    reference_id=row.reference_id,
+                    asset_id=row.asset_id,
+                    extract_metadata=extract_metadata,
+                    compute_hash=compute_hash,
+                    interrupt_check=interrupt_check,
+                    hash_checkpoints=hash_checkpoints,
                 )
-            except FileNotFoundError:
-                exists = False
-            except OSError:
-                exists = False
-
-            acc["states"].append({
-                "sid": sid,
-                "fp": fp,
-                "exists": exists,
-                "fast_ok": fast_ok,
-                "needs_verify": bool(needs_verify),
-            })
-
-        to_set_verify: list[int] = []
-        to_clear_verify: list[int] = []
-        stale_state_ids: list[int] = []
-        survivors: set[str] = set()
-
-        for aid, acc in by_asset.items():
-            a_hash = acc["hash"]
-            states = acc["states"]
-            any_fast_ok = any(s["fast_ok"] for s in states)
-            all_missing = all(not s["exists"] for s in states)
-
-            for s in states:
-                if not s["exists"]:
-                    continue
-                if s["fast_ok"] and s["needs_verify"]:
-                    to_clear_verify.append(s["sid"])
-                if not s["fast_ok"] and not s["needs_verify"]:
-                    to_set_verify.append(s["sid"])
-
-            if a_hash is None:
-                if states and all_missing:  # remove seed Asset completely, if no valid AssetCache exists
-                    sess.execute(sqlalchemy.delete(AssetInfo).where(AssetInfo.asset_id == aid))
-                    asset = sess.get(Asset, aid)
-                    if asset:
-                        sess.delete(asset)
+                if new_level > row.enrichment_level:
+                    enriched += 1
                 else:
-                    for s in states:
-                        if s["exists"]:
-                            survivors.add(os.path.abspath(s["fp"]))
-                continue
+                    failed_ids.append(row.reference_id)
+            except Exception as e:
+                logging.warning("Failed to enrich %s: %s", row.file_path, e)
+                sess.rollback()
+                failed_ids.append(row.reference_id)
 
-            if any_fast_ok:  # if Asset has at least one valid AssetCache record, remove any invalid AssetCache records
-                for s in states:
-                    if not s["exists"]:
-                        stale_state_ids.append(s["sid"])
-                if update_missing_tags:
-                    with contextlib.suppress(Exception):
-                        remove_missing_tag_for_asset_id(sess, asset_id=aid)
-            elif update_missing_tags:
-                with contextlib.suppress(Exception):
-                    add_missing_tag_for_asset_id(sess, asset_id=aid, origin="automatic")
-
-            for s in states:
-                if s["exists"]:
-                    survivors.add(os.path.abspath(s["fp"]))
-
-        if stale_state_ids:
-            sess.execute(sqlalchemy.delete(AssetCacheState).where(AssetCacheState.id.in_(stale_state_ids)))
-        if to_set_verify:
-            sess.execute(
-                sqlalchemy.update(AssetCacheState)
-                .where(AssetCacheState.id.in_(to_set_verify))
-                .values(needs_verify=True)
-            )
-        if to_clear_verify:
-            sess.execute(
-                sqlalchemy.update(AssetCacheState)
-                .where(AssetCacheState.id.in_(to_clear_verify))
-                .values(needs_verify=False)
-            )
-        sess.commit()
-        return survivors if collect_existing_paths else None
+    return enriched, failed_ids

app/assets/seeder.py

@@ -0,0 +1,794 @@
+"""Background asset seeder with thread management and cancellation support."""
+
+import logging
+import os
+import threading
+import time
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import Callable
+
+from app.assets.scanner import (
+    ENRICHMENT_METADATA,
+    ENRICHMENT_STUB,
+    RootType,
+    build_asset_specs,
+    collect_paths_for_roots,
+    enrich_assets_batch,
+    get_all_known_prefixes,
+    get_prefixes_for_root,
+    get_unenriched_assets_for_roots,
+    insert_asset_specs,
+    mark_missing_outside_prefixes_safely,
+    sync_root_safely,
+)
+from app.database.db import dependencies_available
+
+
+class ScanInProgressError(Exception):
+    """Raised when an operation cannot proceed because a scan is running."""
+
+
+class State(Enum):
+    """Seeder state machine states."""
+
+    IDLE = "IDLE"
+    RUNNING = "RUNNING"
+    PAUSED = "PAUSED"
+    CANCELLING = "CANCELLING"
+
+
+class ScanPhase(Enum):
+    """Scan phase options."""
+
+    FAST = "fast"  # Phase 1: filesystem only (stubs)
+    ENRICH = "enrich"  # Phase 2: metadata + hash
+    FULL = "full"  # Both phases sequentially
+
+
+@dataclass
+class Progress:
+    """Progress information for a scan operation."""
+
+    scanned: int = 0
+    total: int = 0
+    created: int = 0
+    skipped: int = 0
+
+
+@dataclass
+class ScanStatus:
+    """Current status of the asset seeder."""
+
+    state: State
+    progress: Progress | None
+    errors: list[str] = field(default_factory=list)
+
+
+ProgressCallback = Callable[[Progress], None]
+
+
+class _AssetSeeder:
+    """Background asset scanning manager.
+
+    Spawns ephemeral daemon threads for scanning.
+    Each scan creates a new thread that exits when complete.
+    Use the module-level ``asset_seeder`` instance.
+    """
+
+    def __init__(self) -> None:
+        self._lock = threading.Lock()
+        self._state = State.IDLE
+        self._progress: Progress | None = None
+        self._last_progress: Progress | None = None
+        self._errors: list[str] = []
+        self._thread: threading.Thread | None = None
+        self._cancel_event = threading.Event()
+        self._run_gate = threading.Event()
+        self._run_gate.set()  # Start unpaused (set = running, clear = paused)
+        self._roots: tuple[RootType, ...] = ()
+        self._phase: ScanPhase = ScanPhase.FULL
+        self._compute_hashes: bool = False
+        self._prune_first: bool = False
+        self._progress_callback: ProgressCallback | None = None
+        self._disabled: bool = False
+
+    def disable(self) -> None:
+        """Disable the asset seeder, preventing any scans from starting."""
+        self._disabled = True
+        logging.info("Asset seeder disabled")
+
+    def is_disabled(self) -> bool:
+        """Check if the asset seeder is disabled."""
+        return self._disabled
+
+    def start(
+        self,
+        roots: tuple[RootType, ...] = ("models", "input", "output"),
+        phase: ScanPhase = ScanPhase.FULL,
+        progress_callback: ProgressCallback | None = None,
+        prune_first: bool = False,
+        compute_hashes: bool = False,
+    ) -> bool:
+        """Start a background scan for the given roots.
+
+        Args:
+            roots: Tuple of root types to scan (models, input, output)
+            phase: Scan phase to run (FAST, ENRICH, or FULL for both)
+            progress_callback: Optional callback called with progress updates
+            prune_first: If True, prune orphaned assets before scanning
+            compute_hashes: If True, compute blake3 hashes (slow)
+
+        Returns:
+            True if scan was started, False if already running
+        """
+        if self._disabled:
+            logging.debug("Asset seeder is disabled, skipping start")
+            return False
+        logging.info("Seeder start (roots=%s, phase=%s)", roots, phase.value)
+        with self._lock:
+            if self._state != State.IDLE:
+                logging.info("Asset seeder already running, skipping start")
+                return False
+            self._state = State.RUNNING
+            self._progress = Progress()
+            self._errors = []
+            self._roots = roots
+            self._phase = phase
+            self._prune_first = prune_first
+            self._compute_hashes = compute_hashes
+            self._progress_callback = progress_callback
+            self._cancel_event.clear()
+            self._run_gate.set()  # Ensure unpaused when starting
+            self._thread = threading.Thread(
+                target=self._run_scan,
+                name="_AssetSeeder",
+                daemon=True,
+            )
+            self._thread.start()
+            return True
+
+    def start_fast(
+        self,
+        roots: tuple[RootType, ...] = ("models", "input", "output"),
+        progress_callback: ProgressCallback | None = None,
+        prune_first: bool = False,
+    ) -> bool:
+        """Start a fast scan (phase 1 only) - creates stub records.
+
+        Args:
+            roots: Tuple of root types to scan
+            progress_callback: Optional callback for progress updates
+            prune_first: If True, prune orphaned assets before scanning
+
+        Returns:
+            True if scan was started, False if already running
+        """
+        return self.start(
+            roots=roots,
+            phase=ScanPhase.FAST,
+            progress_callback=progress_callback,
+            prune_first=prune_first,
+            compute_hashes=False,
+        )
+
+    def start_enrich(
+        self,
+        roots: tuple[RootType, ...] = ("models", "input", "output"),
+        progress_callback: ProgressCallback | None = None,
+        compute_hashes: bool = False,
+    ) -> bool:
+        """Start an enrichment scan (phase 2 only) - extracts metadata and hashes.
+
+        Args:
+            roots: Tuple of root types to scan
+            progress_callback: Optional callback for progress updates
+            compute_hashes: If True, compute blake3 hashes
+
+        Returns:
+            True if scan was started, False if already running
+        """
+        return self.start(
+            roots=roots,
+            phase=ScanPhase.ENRICH,
+            progress_callback=progress_callback,
+            prune_first=False,
+            compute_hashes=compute_hashes,
+        )
+
+    def cancel(self) -> bool:
+        """Request cancellation of the current scan.
+
+        Returns:
+            True if cancellation was requested, False if not running or paused
+        """
+        with self._lock:
+            if self._state not in (State.RUNNING, State.PAUSED):
+                return False
+            logging.info("Asset seeder cancelling (was %s)", self._state.value)
+            self._state = State.CANCELLING
+            self._cancel_event.set()
+            self._run_gate.set()  # Unblock if paused so thread can exit
+            return True
+
+    def stop(self) -> bool:
+        """Stop the current scan (alias for cancel).
+
+        Returns:
+            True if stop was requested, False if not running
+        """
+        return self.cancel()
+
+    def pause(self) -> bool:
+        """Pause the current scan.
+
+        The scan will complete its current batch before pausing.
+
+        Returns:
+            True if pause was requested, False if not running
+        """
+        with self._lock:
+            if self._state != State.RUNNING:
+                return False
+            logging.info("Asset seeder pausing")
+            self._state = State.PAUSED
+            self._run_gate.clear()
+            return True
+
+    def resume(self) -> bool:
+        """Resume a paused scan.
+
+        This is a noop if the scan is not in the PAUSED state
+
+        Returns:
+            True if resumed, False if not paused
+        """
+        with self._lock:
+            if self._state != State.PAUSED:
+                return False
+            logging.info("Asset seeder resuming")
+            self._state = State.RUNNING
+            self._run_gate.set()
+        self._emit_event("assets.seed.resumed", {})
+        return True
+
+    def restart(
+        self,
+        roots: tuple[RootType, ...] | None = None,
+        phase: ScanPhase | None = None,
+        progress_callback: ProgressCallback | None = None,
+        prune_first: bool | None = None,
+        compute_hashes: bool | None = None,
+        timeout: float = 5.0,
+    ) -> bool:
+        """Cancel any running scan and start a new one.
+
+        Args:
+            roots: Roots to scan (defaults to previous roots)
+            phase: Scan phase (defaults to previous phase)
+            progress_callback: Progress callback (defaults to previous)
+            prune_first: Prune before scan (defaults to previous)
+            compute_hashes: Compute hashes (defaults to previous)
+            timeout: Max seconds to wait for current scan to stop
+
+        Returns:
+            True if new scan was started, False if failed to stop previous
+        """
+        logging.info("Asset seeder restart requested")
+        with self._lock:
+            prev_roots = self._roots
+            prev_phase = self._phase
+            prev_callback = self._progress_callback
+            prev_prune = self._prune_first
+            prev_hashes = self._compute_hashes
+
+        self.cancel()
+        if not self.wait(timeout=timeout):
+            return False
+
+        cb = progress_callback if progress_callback is not None else prev_callback
+        return self.start(
+            roots=roots if roots is not None else prev_roots,
+            phase=phase if phase is not None else prev_phase,
+            progress_callback=cb,
+            prune_first=prune_first if prune_first is not None else prev_prune,
+            compute_hashes=(
+                compute_hashes if compute_hashes is not None else prev_hashes
+            ),
+        )
+
+    def wait(self, timeout: float | None = None) -> bool:
+        """Wait for the current scan to complete.
+
+        Args:
+            timeout: Maximum seconds to wait, or None for no timeout
+
+        Returns:
+            True if scan completed, False if timeout expired or no scan running
+        """
+        with self._lock:
+            thread = self._thread
+        if thread is None:
+            return True
+        thread.join(timeout=timeout)
+        return not thread.is_alive()
+
+    def get_status(self) -> ScanStatus:
+        """Get the current status and progress of the seeder."""
+        with self._lock:
+            src = self._progress or self._last_progress
+            return ScanStatus(
+                state=self._state,
+                progress=Progress(
+                    scanned=src.scanned,
+                    total=src.total,
+                    created=src.created,
+                    skipped=src.skipped,
+                )
+                if src
+                else None,
+                errors=list(self._errors),
+            )
+
+    def shutdown(self, timeout: float = 5.0) -> None:
+        """Gracefully shutdown: cancel any running scan and wait for thread.
+
+        Args:
+            timeout: Maximum seconds to wait for thread to exit
+        """
+        self.cancel()
+        self.wait(timeout=timeout)
+        with self._lock:
+            self._thread = None
+
+    def mark_missing_outside_prefixes(self) -> int:
+        """Mark references as missing when outside all known root prefixes.
+
+        This is a non-destructive soft-delete operation. Assets and their
+        metadata are preserved, but references are flagged as missing.
+        They can be restored if the file reappears in a future scan.
+
+        This operation is decoupled from scanning to prevent partial scans
+        from accidentally marking assets belonging to other roots.
+
+        Should be called explicitly when cleanup is desired, typically after
+        a full scan of all roots or during maintenance.
+
+        Returns:
+            Number of references marked as missing
+
+        Raises:
+            ScanInProgressError: If a scan is currently running
+        """
+        with self._lock:
+            if self._state != State.IDLE:
+                raise ScanInProgressError(
+                    "Cannot mark missing assets while scan is running"
+                )
+            self._state = State.RUNNING
+
+        try:
+            if not dependencies_available():
+                logging.warning(
+                    "Database dependencies not available, skipping mark missing"
+                )
+                return 0
+
+            all_prefixes = get_all_known_prefixes()
+            marked = mark_missing_outside_prefixes_safely(all_prefixes)
+            if marked > 0:
+                logging.info("Marked %d references as missing", marked)
+            return marked
+        finally:
+            with self._lock:
+                self._last_progress = self._progress
+                self._state = State.IDLE
+                self._progress = None
+
+    def _is_cancelled(self) -> bool:
+        """Check if cancellation has been requested."""
+        return self._cancel_event.is_set()
+
+    def _is_paused_or_cancelled(self) -> bool:
+        """Non-blocking check: True if paused or cancelled.
+
+        Use as interrupt_check for I/O-bound work (e.g. hashing) so that
+        file handles are released immediately on pause rather than held
+        open while blocked. The caller is responsible for blocking on
+        _check_pause_and_cancel() afterward.
+        """
+        return not self._run_gate.is_set() or self._cancel_event.is_set()
+
+    def _check_pause_and_cancel(self) -> bool:
+        """Block while paused, then check if cancelled.
+
+        Call this at checkpoint locations in scan loops. It will:
+        1. Block indefinitely while paused (until resume or cancel)
+        2. Return True if cancelled, False to continue
+
+        Returns:
+            True if scan should stop, False to continue
+        """
+        if not self._run_gate.is_set():
+            self._emit_event("assets.seed.paused", {})
+        self._run_gate.wait()  # Blocks if paused
+        return self._is_cancelled()
+
+    def _emit_event(self, event_type: str, data: dict) -> None:
+        """Emit a WebSocket event if server is available."""
+        try:
+            from server import PromptServer
+
+            if hasattr(PromptServer, "instance") and PromptServer.instance:
+                PromptServer.instance.send_sync(event_type, data)
+        except Exception:
+            pass
+
+    def _update_progress(
+        self,
+        scanned: int | None = None,
+        total: int | None = None,
+        created: int | None = None,
+        skipped: int | None = None,
+    ) -> None:
+        """Update progress counters (thread-safe)."""
+        callback: ProgressCallback | None = None
+        progress: Progress | None = None
+
+        with self._lock:
+            if self._progress is None:
+                return
+            if scanned is not None:
+                self._progress.scanned = scanned
+            if total is not None:
+                self._progress.total = total
+            if created is not None:
+                self._progress.created = created
+            if skipped is not None:
+                self._progress.skipped = skipped
+            if self._progress_callback:
+                callback = self._progress_callback
+                progress = Progress(
+                    scanned=self._progress.scanned,
+                    total=self._progress.total,
+                    created=self._progress.created,
+                    skipped=self._progress.skipped,
+                )
+
+        if callback and progress:
+            try:
+                callback(progress)
+            except Exception:
+                pass
+
+    _MAX_ERRORS = 200
+
+    def _add_error(self, message: str) -> None:
+        """Add an error message (thread-safe), capped at _MAX_ERRORS."""
+        with self._lock:
+            if len(self._errors) < self._MAX_ERRORS:
+                self._errors.append(message)
+
+    def _log_scan_config(self, roots: tuple[RootType, ...]) -> None:
+        """Log the directories that will be scanned."""
+        import folder_paths
+
+        for root in roots:
+            if root == "models":
+                logging.info(
+                    "Asset scan [models] directory: %s",
+                    os.path.abspath(folder_paths.models_dir),
+                )
+            else:
+                prefixes = get_prefixes_for_root(root)
+                if prefixes:
+                    logging.info("Asset scan [%s] directories: %s", root, prefixes)
+
+    def _run_scan(self) -> None:
+        """Main scan loop running in background thread."""
+        t_start = time.perf_counter()
+        roots = self._roots
+        phase = self._phase
+        cancelled = False
+        total_created = 0
+        total_enriched = 0
+        skipped_existing = 0
+        total_paths = 0
+
+        try:
+            if not dependencies_available():
+                self._add_error("Database dependencies not available")
+                self._emit_event(
+                    "assets.seed.error",
+                    {"message": "Database dependencies not available"},
+                )
+                return
+
+            if self._prune_first:
+                all_prefixes = get_all_known_prefixes()
+                marked = mark_missing_outside_prefixes_safely(all_prefixes)
+                if marked > 0:
+                    logging.info("Marked %d refs as missing before scan", marked)
+
+            if self._check_pause_and_cancel():
+                logging.info("Asset scan cancelled after pruning phase")
+                cancelled = True
+                return
+
+            self._log_scan_config(roots)
+
+            # Phase 1: Fast scan (stub records)
+            if phase in (ScanPhase.FAST, ScanPhase.FULL):
+                created, skipped, paths = self._run_fast_phase(roots)
+                total_created, skipped_existing, total_paths = created, skipped, paths
+
+                if self._check_pause_and_cancel():
+                    cancelled = True
+                    return
+
+                self._emit_event(
+                    "assets.seed.fast_complete",
+                    {
+                        "roots": list(roots),
+                        "created": total_created,
+                        "skipped": skipped_existing,
+                        "total": total_paths,
+                    },
+                )
+
+            # Phase 2: Enrichment scan (metadata + hashes)
+            if phase in (ScanPhase.ENRICH, ScanPhase.FULL):
+                if self._check_pause_and_cancel():
+                    cancelled = True
+                    return
+
+                enrich_cancelled, total_enriched = self._run_enrich_phase(roots)
+
+                if enrich_cancelled:
+                    cancelled = True
+                    return
+
+                self._emit_event(
+                    "assets.seed.enrich_complete",
+                    {
+                        "roots": list(roots),
+                        "enriched": total_enriched,
+                    },
+                )
+
+            elapsed = time.perf_counter() - t_start
+            logging.info(
+                "Scan(%s, %s) done %.3fs: created=%d enriched=%d skipped=%d",
+                roots,
+                phase.value,
+                elapsed,
+                total_created,
+                total_enriched,
+                skipped_existing,
+            )
+
+            self._emit_event(
+                "assets.seed.completed",
+                {
+                    "phase": phase.value,
+                    "total": total_paths,
+                    "created": total_created,
+                    "enriched": total_enriched,
+                    "skipped": skipped_existing,
+                    "elapsed": round(elapsed, 3),
+                },
+            )
+
+        except Exception as e:
+            self._add_error(f"Scan failed: {e}")
+            logging.exception("Asset scan failed")
+            self._emit_event("assets.seed.error", {"message": str(e)})
+        finally:
+            if cancelled:
+                self._emit_event(
+                    "assets.seed.cancelled",
+                    {
+                        "scanned": self._progress.scanned if self._progress else 0,
+                        "total": total_paths,
+                        "created": total_created,
+                    },
+                )
+            with self._lock:
+                self._last_progress = self._progress
+                self._state = State.IDLE
+                self._progress = None
+
+    def _run_fast_phase(self, roots: tuple[RootType, ...]) -> tuple[int, int, int]:
+        """Run phase 1: fast scan to create stub records.
+
+        Returns:
+            Tuple of (total_created, skipped_existing, total_paths)
+        """
+        t_fast_start = time.perf_counter()
+        total_created = 0
+        skipped_existing = 0
+
+        existing_paths: set[str] = set()
+        t_sync = time.perf_counter()
+        for r in roots:
+            if self._check_pause_and_cancel():
+                return total_created, skipped_existing, 0
+            existing_paths.update(sync_root_safely(r))
+        logging.debug(
+            "Fast scan: sync_root phase took %.3fs (%d existing paths)",
+            time.perf_counter() - t_sync,
+            len(existing_paths),
+        )
+
+        if self._check_pause_and_cancel():
+            return total_created, skipped_existing, 0
+
+        t_collect = time.perf_counter()
+        paths = collect_paths_for_roots(roots)
+        logging.debug(
+            "Fast scan: collect_paths took %.3fs (%d paths found)",
+            time.perf_counter() - t_collect,
+            len(paths),
+        )
+        total_paths = len(paths)
+        self._update_progress(total=total_paths)
+
+        self._emit_event(
+            "assets.seed.started",
+            {"roots": list(roots), "total": total_paths, "phase": "fast"},
+        )
+
+        # Use stub specs (no metadata extraction, no hashing)
+        t_specs = time.perf_counter()
+        specs, tag_pool, skipped_existing = build_asset_specs(
+            paths,
+            existing_paths,
+            enable_metadata_extraction=False,
+            compute_hashes=False,
+        )
+        logging.debug(
+            "Fast scan: build_asset_specs took %.3fs (%d specs, %d skipped)",
+            time.perf_counter() - t_specs,
+            len(specs),
+            skipped_existing,
+        )
+        self._update_progress(skipped=skipped_existing)
+
+        if self._check_pause_and_cancel():
+            return total_created, skipped_existing, total_paths
+
+        batch_size = 500
+        last_progress_time = time.perf_counter()
+        progress_interval = 1.0
+
+        for i in range(0, len(specs), batch_size):
+            if self._check_pause_and_cancel():
+                logging.info(
+                    "Fast scan cancelled after %d/%d files (created=%d)",
+                    i,
+                    len(specs),
+                    total_created,
+                )
+                return total_created, skipped_existing, total_paths
+
+            batch = specs[i : i + batch_size]
+            batch_tags = {t for spec in batch for t in spec["tags"]}
+            try:
+                created = insert_asset_specs(batch, batch_tags)
+                total_created += created
+            except Exception as e:
+                self._add_error(f"Batch insert failed at offset {i}: {e}")
+                logging.exception("Batch insert failed at offset %d", i)
+
+            scanned = i + len(batch)
+            now = time.perf_counter()
+            self._update_progress(scanned=scanned, created=total_created)
+
+            if now - last_progress_time >= progress_interval:
+                self._emit_event(
+                    "assets.seed.progress",
+                    {
+                        "phase": "fast",
+                        "scanned": scanned,
+                        "total": len(specs),
+                        "created": total_created,
+                    },
+                )
+                last_progress_time = now
+
+        self._update_progress(scanned=len(specs), created=total_created)
+        logging.info(
+            "Fast scan complete: %.3fs total (created=%d, skipped=%d, total_paths=%d)",
+            time.perf_counter() - t_fast_start,
+            total_created,
+            skipped_existing,
+            total_paths,
+        )
+        return total_created, skipped_existing, total_paths
+
+    def _run_enrich_phase(self, roots: tuple[RootType, ...]) -> tuple[bool, int]:
+        """Run phase 2: enrich existing records with metadata and hashes.
+
+        Returns:
+            Tuple of (cancelled, total_enriched)
+        """
+        total_enriched = 0
+        batch_size = 100
+        last_progress_time = time.perf_counter()
+        progress_interval = 1.0
+
+        # Get the target enrichment level based on compute_hashes
+        if not self._compute_hashes:
+            target_max_level = ENRICHMENT_STUB
+        else:
+            target_max_level = ENRICHMENT_METADATA
+
+        self._emit_event(
+            "assets.seed.started",
+            {"roots": list(roots), "phase": "enrich"},
+        )
+
+        skip_ids: set[str] = set()
+        consecutive_empty = 0
+        max_consecutive_empty = 3
+
+        # Hash checkpoints survive across batches so interrupted hashes
+        # can be resumed without re-reading the entire file.
+        hash_checkpoints: dict[str, object] = {}
+
+        while True:
+            if self._check_pause_and_cancel():
+                logging.info("Enrich scan cancelled after %d assets", total_enriched)
+                return True, total_enriched
+
+            # Fetch next batch of unenriched assets
+            unenriched = get_unenriched_assets_for_roots(
+                roots,
+                max_level=target_max_level,
+                limit=batch_size,
+            )
+
+            # Filter out previously failed references
+            if skip_ids:
+                unenriched = [r for r in unenriched if r.reference_id not in skip_ids]
+
+            if not unenriched:
+                break
+
+            enriched, failed_ids = enrich_assets_batch(
+                unenriched,
+                extract_metadata=True,
+                compute_hash=self._compute_hashes,
+                interrupt_check=self._is_paused_or_cancelled,
+                hash_checkpoints=hash_checkpoints,
+            )
+            total_enriched += enriched
+            skip_ids.update(failed_ids)
+
+            if enriched == 0:
+                consecutive_empty += 1
+                if consecutive_empty >= max_consecutive_empty:
+                    logging.warning(
+                        "Enrich phase stopping: %d consecutive batches with no progress (%d skipped)",
+                        consecutive_empty,
+                        len(skip_ids),
+                    )
+                    break
+            else:
+                consecutive_empty = 0
+
+            now = time.perf_counter()
+            if now - last_progress_time >= progress_interval:
+                self._emit_event(
+                    "assets.seed.progress",
+                    {
+                        "phase": "enrich",
+                        "enriched": total_enriched,
+                    },
+                )
+                last_progress_time = now
+
+        return False, total_enriched
+
+
+asset_seeder = _AssetSeeder()

app/assets/services/__init__.py

@@ -0,0 +1,87 @@
+from app.assets.services.asset_management import (
+    asset_exists,
+    delete_asset_reference,
+    get_asset_by_hash,
+    get_asset_detail,
+    list_assets_page,
+    resolve_asset_for_download,
+    set_asset_preview,
+    update_asset_metadata,
+)
+from app.assets.services.bulk_ingest import (
+    BulkInsertResult,
+    batch_insert_seed_assets,
+    cleanup_unreferenced_assets,
+)
+from app.assets.services.file_utils import (
+    get_mtime_ns,
+    get_size_and_mtime_ns,
+    list_files_recursively,
+    verify_file_unchanged,
+)
+from app.assets.services.ingest import (
+    DependencyMissingError,
+    HashMismatchError,
+    create_from_hash,
+    upload_from_temp_path,
+)
+from app.assets.database.queries import (
+    AddTagsResult,
+    RemoveTagsResult,
+)
+from app.assets.services.schemas import (
+    AssetData,
+    AssetDetailResult,
+    AssetSummaryData,
+    DownloadResolutionResult,
+    IngestResult,
+    ListAssetsResult,
+    ReferenceData,
+    RegisterAssetResult,
+    TagUsage,
+    UploadResult,
+    UserMetadata,
+)
+from app.assets.services.tagging import (
+    apply_tags,
+    list_tags,
+    remove_tags,
+)
+
+__all__ = [
+    "AddTagsResult",
+    "AssetData",
+    "AssetDetailResult",
+    "AssetSummaryData",
+    "ReferenceData",
+    "BulkInsertResult",
+    "DependencyMissingError",
+    "DownloadResolutionResult",
+    "HashMismatchError",
+    "IngestResult",
+    "ListAssetsResult",
+    "RegisterAssetResult",
+    "RemoveTagsResult",
+    "TagUsage",
+    "UploadResult",
+    "UserMetadata",
+    "apply_tags",
+    "asset_exists",
+    "batch_insert_seed_assets",
+    "create_from_hash",
+    "delete_asset_reference",
+    "get_asset_by_hash",
+    "get_asset_detail",
+    "get_mtime_ns",
+    "get_size_and_mtime_ns",
+    "list_assets_page",
+    "list_files_recursively",
+    "list_tags",
+    "cleanup_unreferenced_assets",
+    "remove_tags",
+    "resolve_asset_for_download",
+    "set_asset_preview",
+    "update_asset_metadata",
+    "upload_from_temp_path",
+    "verify_file_unchanged",
+]

app/assets/services/asset_management.py

@@ -0,0 +1,309 @@
+import contextlib
+import mimetypes
+import os
+from typing import Sequence
+
+
+from app.assets.database.models import Asset
+from app.assets.database.queries import (
+    asset_exists_by_hash,
+    reference_exists_for_asset_id,
+    delete_reference_by_id,
+    fetch_reference_and_asset,
+    soft_delete_reference_by_id,
+    fetch_reference_asset_and_tags,
+    get_asset_by_hash as queries_get_asset_by_hash,
+    get_reference_by_id,
+    get_reference_with_owner_check,
+    list_references_page,
+    list_references_by_asset_id,
+    set_reference_metadata,
+    set_reference_preview,
+    set_reference_tags,
+    update_reference_access_time,
+    update_reference_name,
+    update_reference_updated_at,
+)
+from app.assets.helpers import select_best_live_path
+from app.assets.services.path_utils import compute_relative_filename
+from app.assets.services.schemas import (
+    AssetData,
+    AssetDetailResult,
+    AssetSummaryData,
+    DownloadResolutionResult,
+    ListAssetsResult,
+    UserMetadata,
+    extract_asset_data,
+    extract_reference_data,
+)
+from app.database.db import create_session
+
+
+def get_asset_detail(
+    reference_id: str,
+    owner_id: str = "",
+) -> AssetDetailResult | None:
+    with create_session() as session:
+        result = fetch_reference_asset_and_tags(
+            session,
+            reference_id=reference_id,
+            owner_id=owner_id,
+        )
+        if not result:
+            return None
+
+        ref, asset, tags = result
+        return AssetDetailResult(
+            ref=extract_reference_data(ref),
+            asset=extract_asset_data(asset),
+            tags=tags,
+        )
+
+
+def update_asset_metadata(
+    reference_id: str,
+    name: str | None = None,
+    tags: Sequence[str] | None = None,
+    user_metadata: UserMetadata = None,
+    tag_origin: str = "manual",
+    owner_id: str = "",
+) -> AssetDetailResult:
+    with create_session() as session:
+        ref = get_reference_with_owner_check(session, reference_id, owner_id)
+
+        touched = False
+        if name is not None and name != ref.name:
+            update_reference_name(session, reference_id=reference_id, name=name)
+            touched = True
+
+        computed_filename = compute_relative_filename(ref.file_path) if ref.file_path else None
+
+        new_meta: dict | None = None
+        if user_metadata is not None:
+            new_meta = dict(user_metadata)
+        elif computed_filename:
+            current_meta = ref.user_metadata or {}
+            if current_meta.get("filename") != computed_filename:
+                new_meta = dict(current_meta)
+
+        if new_meta is not None:
+            if computed_filename:
+                new_meta["filename"] = computed_filename
+            set_reference_metadata(
+                session, reference_id=reference_id, user_metadata=new_meta
+            )
+            touched = True
+
+        if tags is not None:
+            set_reference_tags(
+                session,
+                reference_id=reference_id,
+                tags=tags,
+                origin=tag_origin,
+            )
+            touched = True
+
+        if touched and user_metadata is None:
+            update_reference_updated_at(session, reference_id=reference_id)
+
+        result = fetch_reference_asset_and_tags(
+            session,
+            reference_id=reference_id,
+            owner_id=owner_id,
+        )
+        if not result:
+            raise RuntimeError("State changed during update")
+
+        ref, asset, tag_list = result
+        detail = AssetDetailResult(
+            ref=extract_reference_data(ref),
+            asset=extract_asset_data(asset),
+            tags=tag_list,
+        )
+        session.commit()
+
+        return detail
+
+
+def delete_asset_reference(
+    reference_id: str,
+    owner_id: str,
+    delete_content_if_orphan: bool = True,
+) -> bool:
+    with create_session() as session:
+        if not delete_content_if_orphan:
+            # Soft delete: mark the reference as deleted but keep everything
+            deleted = soft_delete_reference_by_id(
+                session, reference_id=reference_id, owner_id=owner_id
+            )
+            session.commit()
+            return deleted
+
+        ref_row = get_reference_by_id(session, reference_id=reference_id)
+        asset_id = ref_row.asset_id if ref_row else None
+        file_path = ref_row.file_path if ref_row else None
+
+        deleted = delete_reference_by_id(
+            session, reference_id=reference_id, owner_id=owner_id
+        )
+        if not deleted:
+            session.commit()
+            return False
+
+        if not asset_id:
+            session.commit()
+            return True
+
+        still_exists = reference_exists_for_asset_id(session, asset_id=asset_id)
+        if still_exists:
+            session.commit()
+            return True
+
+        # Orphaned asset - delete it and its files
+        refs = list_references_by_asset_id(session, asset_id=asset_id)
+        file_paths = [
+            r.file_path for r in (refs or []) if getattr(r, "file_path", None)
+        ]
+        # Also include the just-deleted file path
+        if file_path:
+            file_paths.append(file_path)
+
+        asset_row = session.get(Asset, asset_id)
+        if asset_row is not None:
+            session.delete(asset_row)
+
+        session.commit()
+
+        # Delete files after commit
+        for p in file_paths:
+            with contextlib.suppress(Exception):
+                if p and os.path.isfile(p):
+                    os.remove(p)
+
+    return True
+
+
+def set_asset_preview(
+    reference_id: str,
+    preview_asset_id: str | None = None,
+    owner_id: str = "",
+) -> AssetDetailResult:
+    with create_session() as session:
+        get_reference_with_owner_check(session, reference_id, owner_id)
+
+        set_reference_preview(
+            session,
+            reference_id=reference_id,
+            preview_asset_id=preview_asset_id,
+        )
+
+        result = fetch_reference_asset_and_tags(
+            session, reference_id=reference_id, owner_id=owner_id
+        )
+        if not result:
+            raise RuntimeError("State changed during preview update")
+
+        ref, asset, tags = result
+        detail = AssetDetailResult(
+            ref=extract_reference_data(ref),
+            asset=extract_asset_data(asset),
+            tags=tags,
+        )
+        session.commit()
+
+        return detail
+
+
+def asset_exists(asset_hash: str) -> bool:
+    with create_session() as session:
+        return asset_exists_by_hash(session, asset_hash=asset_hash)
+
+
+def get_asset_by_hash(asset_hash: str) -> AssetData | None:
+    with create_session() as session:
+        asset = queries_get_asset_by_hash(session, asset_hash=asset_hash)
+        return extract_asset_data(asset)
+
+
+def list_assets_page(
+    owner_id: str = "",
+    include_tags: Sequence[str] | None = None,
+    exclude_tags: Sequence[str] | None = None,
+    name_contains: str | None = None,
+    metadata_filter: dict | None = None,
+    limit: int = 20,
+    offset: int = 0,
+    sort: str = "created_at",
+    order: str = "desc",
+) -> ListAssetsResult:
+    with create_session() as session:
+        refs, tag_map, total = list_references_page(
+            session,
+            owner_id=owner_id,
+            include_tags=include_tags,
+            exclude_tags=exclude_tags,
+            name_contains=name_contains,
+            metadata_filter=metadata_filter,
+            limit=limit,
+            offset=offset,
+            sort=sort,
+            order=order,
+        )
+
+        items: list[AssetSummaryData] = []
+        for ref in refs:
+            items.append(
+                AssetSummaryData(
+                    ref=extract_reference_data(ref),
+                    asset=extract_asset_data(ref.asset),
+                    tags=tag_map.get(ref.id, []),
+                )
+            )
+
+        return ListAssetsResult(items=items, total=total)
+
+
+def resolve_asset_for_download(
+    reference_id: str,
+    owner_id: str = "",
+) -> DownloadResolutionResult:
+    with create_session() as session:
+        pair = fetch_reference_and_asset(
+            session, reference_id=reference_id, owner_id=owner_id
+        )
+        if not pair:
+            raise ValueError(f"AssetReference {reference_id} not found")
+
+        ref, asset = pair
+
+        # For references with file_path, use that directly
+        if ref.file_path and os.path.isfile(ref.file_path):
+            abs_path = ref.file_path
+        else:
+            # For API-created refs without file_path, find a path from other refs
+            refs = list_references_by_asset_id(session, asset_id=asset.id)
+            abs_path = select_best_live_path(refs)
+            if not abs_path:
+                raise FileNotFoundError(
+                    f"No live path for AssetReference {reference_id} "
+                    f"(asset id={asset.id}, name={ref.name})"
+                )
+
+        # Capture ORM attributes before commit (commit expires loaded objects)
+        ref_name = ref.name
+        asset_mime = asset.mime_type
+
+        update_reference_access_time(session, reference_id=reference_id)
+        session.commit()
+
+        ctype = (
+            asset_mime
+            or mimetypes.guess_type(ref_name or abs_path)[0]
+            or "application/octet-stream"
+        )
+        download_name = ref_name or os.path.basename(abs_path)
+        return DownloadResolutionResult(
+            abs_path=abs_path,
+            content_type=ctype,
+            download_name=download_name,
+        )

app/assets/services/bulk_ingest.py

@@ -0,0 +1,280 @@
+from __future__ import annotations
+
+import os
+import uuid
+from dataclasses import dataclass
+from datetime import datetime
+from typing import TYPE_CHECKING, Any, TypedDict
+
+from sqlalchemy.orm import Session
+
+from app.assets.database.queries import (
+    bulk_insert_assets,
+    bulk_insert_references_ignore_conflicts,
+    bulk_insert_tags_and_meta,
+    delete_assets_by_ids,
+    get_existing_asset_ids,
+    get_reference_ids_by_ids,
+    get_references_by_paths_and_asset_ids,
+    get_unreferenced_unhashed_asset_ids,
+    restore_references_by_paths,
+)
+from app.assets.helpers import get_utc_now
+
+if TYPE_CHECKING:
+    from app.assets.services.metadata_extract import ExtractedMetadata
+
+
+class SeedAssetSpec(TypedDict):
+    """Spec for seeding an asset from filesystem."""
+
+    abs_path: str
+    size_bytes: int
+    mtime_ns: int
+    info_name: str
+    tags: list[str]
+    fname: str
+    metadata: ExtractedMetadata | None
+    hash: str | None
+    mime_type: str | None
+
+
+class AssetRow(TypedDict):
+    """Row data for inserting an Asset."""
+
+    id: str
+    hash: str | None
+    size_bytes: int
+    mime_type: str | None
+    created_at: datetime
+
+
+class ReferenceRow(TypedDict):
+    """Row data for inserting an AssetReference."""
+
+    id: str
+    asset_id: str
+    file_path: str
+    mtime_ns: int
+    owner_id: str
+    name: str
+    preview_id: str | None
+    user_metadata: dict[str, Any] | None
+    created_at: datetime
+    updated_at: datetime
+    last_access_time: datetime
+
+
+class TagRow(TypedDict):
+    """Row data for inserting a Tag."""
+
+    asset_reference_id: str
+    tag_name: str
+    origin: str
+    added_at: datetime
+
+
+class MetadataRow(TypedDict):
+    """Row data for inserting asset metadata."""
+
+    asset_reference_id: str
+    key: str
+    ordinal: int
+    val_str: str | None
+    val_num: float | None
+    val_bool: bool | None
+    val_json: dict[str, Any] | None
+
+
+@dataclass
+class BulkInsertResult:
+    """Result of bulk asset insertion."""
+
+    inserted_refs: int
+    won_paths: int
+    lost_paths: int
+
+
+def batch_insert_seed_assets(
+    session: Session,
+    specs: list[SeedAssetSpec],
+    owner_id: str = "",
+) -> BulkInsertResult:
+    """Seed assets from filesystem specs in batch.
+
+    Each spec is a dict with keys:
+      - abs_path: str
+      - size_bytes: int
+      - mtime_ns: int
+      - info_name: str
+      - tags: list[str]
+      - fname: Optional[str]
+
+    This function orchestrates:
+    1. Insert seed Assets (hash=NULL)
+    2. Claim references with ON CONFLICT DO NOTHING on file_path
+    3. Query to find winners (paths where our asset_id was inserted)
+    4. Delete Assets for losers (path already claimed by another asset)
+    5. Insert tags and metadata for successfully inserted references
+
+    Returns:
+        BulkInsertResult with inserted_refs, won_paths, lost_paths
+    """
+    if not specs:
+        return BulkInsertResult(inserted_refs=0, won_paths=0, lost_paths=0)
+
+    current_time = get_utc_now()
+    asset_rows: list[AssetRow] = []
+    reference_rows: list[ReferenceRow] = []
+    path_to_asset_id: dict[str, str] = {}
+    asset_id_to_ref_data: dict[str, dict] = {}
+    absolute_path_list: list[str] = []
+
+    for spec in specs:
+        absolute_path = os.path.abspath(spec["abs_path"])
+        asset_id = str(uuid.uuid4())
+        reference_id = str(uuid.uuid4())
+        absolute_path_list.append(absolute_path)
+        path_to_asset_id[absolute_path] = asset_id
+
+        mime_type = spec.get("mime_type")
+        asset_rows.append(
+            {
+                "id": asset_id,
+                "hash": spec.get("hash"),
+                "size_bytes": spec["size_bytes"],
+                "mime_type": mime_type,
+                "created_at": current_time,
+            }
+        )
+
+        # Build user_metadata from extracted metadata or fallback to filename
+        extracted_metadata = spec.get("metadata")
+        if extracted_metadata:
+            user_metadata: dict[str, Any] | None = extracted_metadata.to_user_metadata()
+        elif spec["fname"]:
+            user_metadata = {"filename": spec["fname"]}
+        else:
+            user_metadata = None
+
+        reference_rows.append(
+            {
+                "id": reference_id,
+                "asset_id": asset_id,
+                "file_path": absolute_path,
+                "mtime_ns": spec["mtime_ns"],
+                "owner_id": owner_id,
+                "name": spec["info_name"],
+                "preview_id": None,
+                "user_metadata": user_metadata,
+                "created_at": current_time,
+                "updated_at": current_time,
+                "last_access_time": current_time,
+            }
+        )
+
+        asset_id_to_ref_data[asset_id] = {
+            "reference_id": reference_id,
+            "tags": spec["tags"],
+            "filename": spec["fname"],
+            "extracted_metadata": extracted_metadata,
+        }
+
+    bulk_insert_assets(session, asset_rows)
+
+    # Filter reference rows to only those whose assets were actually inserted
+    # (assets with duplicate hashes are silently dropped by ON CONFLICT DO NOTHING)
+    inserted_asset_ids = get_existing_asset_ids(
+        session, [r["asset_id"] for r in reference_rows]
+    )
+    reference_rows = [r for r in reference_rows if r["asset_id"] in inserted_asset_ids]
+
+    bulk_insert_references_ignore_conflicts(session, reference_rows)
+    restore_references_by_paths(session, absolute_path_list)
+    winning_paths = get_references_by_paths_and_asset_ids(session, path_to_asset_id)
+
+    inserted_paths = {
+        path
+        for path in absolute_path_list
+        if path_to_asset_id[path] in inserted_asset_ids
+    }
+    losing_paths = inserted_paths - winning_paths
+    lost_asset_ids = [path_to_asset_id[path] for path in losing_paths]
+
+    if lost_asset_ids:
+        delete_assets_by_ids(session, lost_asset_ids)
+
+    if not winning_paths:
+        return BulkInsertResult(
+            inserted_refs=0,
+            won_paths=0,
+            lost_paths=len(losing_paths),
+        )
+
+    # Get reference IDs for winners
+    winning_ref_ids = [
+        asset_id_to_ref_data[path_to_asset_id[path]]["reference_id"]
+        for path in winning_paths
+    ]
+    inserted_ref_ids = get_reference_ids_by_ids(session, winning_ref_ids)
+
+    tag_rows: list[TagRow] = []
+    metadata_rows: list[MetadataRow] = []
+
+    if inserted_ref_ids:
+        for path in winning_paths:
+            asset_id = path_to_asset_id[path]
+            ref_data = asset_id_to_ref_data[asset_id]
+            ref_id = ref_data["reference_id"]
+
+            if ref_id not in inserted_ref_ids:
+                continue
+
+            for tag in ref_data["tags"]:
+                tag_rows.append(
+                    {
+                        "asset_reference_id": ref_id,
+                        "tag_name": tag,
+                        "origin": "automatic",
+                        "added_at": current_time,
+                    }
+                )
+
+            # Use extracted metadata for meta rows if available
+            extracted_metadata = ref_data.get("extracted_metadata")
+            if extracted_metadata:
+                metadata_rows.extend(extracted_metadata.to_meta_rows(ref_id))
+            elif ref_data["filename"]:
+                # Fallback: just store filename
+                metadata_rows.append(
+                    {
+                        "asset_reference_id": ref_id,
+                        "key": "filename",
+                        "ordinal": 0,
+                        "val_str": ref_data["filename"],
+                        "val_num": None,
+                        "val_bool": None,
+                        "val_json": None,
+                    }
+                )
+
+    bulk_insert_tags_and_meta(session, tag_rows=tag_rows, meta_rows=metadata_rows)
+
+    return BulkInsertResult(
+        inserted_refs=len(inserted_ref_ids),
+        won_paths=len(winning_paths),
+        lost_paths=len(losing_paths),
+    )
+
+
+def cleanup_unreferenced_assets(session: Session) -> int:
+    """Hard-delete unhashed assets with no active references.
+
+    This is a destructive operation intended for explicit cleanup.
+    Only deletes assets where hash=None and all references are missing.
+
+    Returns:
+        Number of assets deleted
+    """
+    unreferenced_ids = get_unreferenced_unhashed_asset_ids(session)
+    return delete_assets_by_ids(session, unreferenced_ids)

app/assets/services/file_utils.py

@@ -0,0 +1,70 @@
+import os
+
+
+def get_mtime_ns(stat_result: os.stat_result) -> int:
+    """Extract mtime in nanoseconds from a stat result."""
+    return getattr(
+        stat_result, "st_mtime_ns", int(stat_result.st_mtime * 1_000_000_000)
+    )
+
+
+def get_size_and_mtime_ns(path: str, follow_symlinks: bool = True) -> tuple[int, int]:
+    """Get file size in bytes and mtime in nanoseconds."""
+    st = os.stat(path, follow_symlinks=follow_symlinks)
+    return st.st_size, get_mtime_ns(st)
+
+
+def verify_file_unchanged(
+    mtime_db: int | None,
+    size_db: int | None,
+    stat_result: os.stat_result,
+) -> bool:
+    """Check if a file is unchanged based on mtime and size.
+
+    Returns True if the file's mtime and size match the database values.
+    Returns False if mtime_db is None or values don't match.
+
+    size_db=None means don't check size; 0 is a valid recorded size.
+    """
+    if mtime_db is None:
+        return False
+    actual_mtime_ns = get_mtime_ns(stat_result)
+    if int(mtime_db) != int(actual_mtime_ns):
+        return False
+    if size_db is not None:
+        return int(stat_result.st_size) == int(size_db)
+    return True
+
+
+def is_visible(name: str) -> bool:
+    """Return True if a file or directory name is visible (not hidden)."""
+    return not name.startswith(".")
+
+
+def list_files_recursively(base_dir: str) -> list[str]:
+    """Recursively list all files in a directory, following symlinks."""
+    out: list[str] = []
+    base_abs = os.path.abspath(base_dir)
+    if not os.path.isdir(base_abs):
+        return out
+    # Track seen real directory identities to prevent circular symlink loops
+    seen_dirs: set[tuple[int, int]] = set()
+    for dirpath, subdirs, filenames in os.walk(
+        base_abs, topdown=True, followlinks=True
+    ):
+        try:
+            st = os.stat(dirpath)
+            dir_id = (st.st_dev, st.st_ino)
+        except OSError:
+            subdirs.clear()
+            continue
+        if dir_id in seen_dirs:
+            subdirs.clear()
+            continue
+        seen_dirs.add(dir_id)
+        subdirs[:] = [d for d in subdirs if is_visible(d)]
+        for name in filenames:
+            if not is_visible(name):
+                continue
+            out.append(os.path.abspath(os.path.join(dirpath, name)))
+    return out

app/assets/services/hashing.py

@@ -0,0 +1,108 @@
+import io
+import os
+from dataclasses import dataclass
+from typing import IO, Any, Callable
+
+from blake3 import blake3
+
+DEFAULT_CHUNK = 8 * 1024 * 1024
+
+InterruptCheck = Callable[[], bool]
+
+
+@dataclass
+class HashCheckpoint:
+    """Saved state for resuming an interrupted hash computation."""
+
+    bytes_processed: int
+    hasher: Any  # blake3 hasher instance
+    mtime_ns: int = 0
+    file_size: int = 0
+
+
+def compute_blake3_hash(
+    fp: str | IO[bytes],
+    chunk_size: int = DEFAULT_CHUNK,
+    interrupt_check: InterruptCheck | None = None,
+    checkpoint: HashCheckpoint | None = None,
+) -> tuple[str | None, HashCheckpoint | None]:
+    """Compute BLAKE3 hash of a file, with optional checkpoint support.
+
+    Args:
+        fp: File path or file-like object
+        chunk_size: Size of chunks to read at a time
+        interrupt_check: Optional callable that returns True if the operation
+            should be interrupted (e.g. paused or cancelled). Must be
+            non-blocking so file handles are released immediately. Checked
+            between chunk reads.
+        checkpoint: Optional checkpoint to resume from (file paths only)
+
+    Returns:
+        Tuple of (hex_digest, None) on completion, or
+        (None, checkpoint) on interruption (file paths only), or
+        (None, None) on interruption of a file object
+    """
+    if hasattr(fp, "read"):
+        digest = _hash_file_obj(fp, chunk_size, interrupt_check)
+        return digest, None
+
+    with open(os.fspath(fp), "rb") as f:
+        if checkpoint is not None:
+            f.seek(checkpoint.bytes_processed)
+            h = checkpoint.hasher
+            bytes_processed = checkpoint.bytes_processed
+        else:
+            h = blake3()
+            bytes_processed = 0
+
+        if chunk_size <= 0:
+            chunk_size = DEFAULT_CHUNK
+
+        while True:
+            if interrupt_check is not None and interrupt_check():
+                return None, HashCheckpoint(
+                    bytes_processed=bytes_processed,
+                    hasher=h,
+                )
+            chunk = f.read(chunk_size)
+            if not chunk:
+                break
+            h.update(chunk)
+            bytes_processed += len(chunk)
+
+        return h.hexdigest(), None
+
+
+def _hash_file_obj(
+    file_obj: IO,
+    chunk_size: int = DEFAULT_CHUNK,
+    interrupt_check: InterruptCheck | None = None,
+) -> str | None:
+    if chunk_size <= 0:
+        chunk_size = DEFAULT_CHUNK
+
+    seekable = getattr(file_obj, "seekable", lambda: False)()
+    orig_pos = None
+
+    if seekable:
+        try:
+            orig_pos = file_obj.tell()
+            if orig_pos != 0:
+                file_obj.seek(0)
+        except io.UnsupportedOperation:
+            seekable = False
+            orig_pos = None
+
+    try:
+        h = blake3()
+        while True:
+            if interrupt_check is not None and interrupt_check():
+                return None
+            chunk = file_obj.read(chunk_size)
+            if not chunk:
+                break
+            h.update(chunk)
+        return h.hexdigest()
+    finally:
+        if seekable and orig_pos is not None:
+            file_obj.seek(orig_pos)

app/assets/services/ingest.py

@@ -0,0 +1,375 @@
+import contextlib
+import logging
+import mimetypes
+import os
+from typing import Any, Sequence
+
+from sqlalchemy.orm import Session
+
+import app.assets.services.hashing as hashing
+from app.assets.database.queries import (
+    add_tags_to_reference,
+    fetch_reference_and_asset,
+    get_asset_by_hash,
+    get_existing_asset_ids,
+    get_reference_by_file_path,
+    get_reference_tags,
+    get_or_create_reference,
+    remove_missing_tag_for_asset_id,
+    set_reference_metadata,
+    set_reference_tags,
+    upsert_asset,
+    upsert_reference,
+    validate_tags_exist,
+)
+from app.assets.helpers import normalize_tags
+from app.assets.services.file_utils import get_size_and_mtime_ns
+from app.assets.services.path_utils import (
+    compute_relative_filename,
+    resolve_destination_from_tags,
+    validate_path_within_base,
+)
+from app.assets.services.schemas import (
+    IngestResult,
+    RegisterAssetResult,
+    UploadResult,
+    UserMetadata,
+    extract_asset_data,
+    extract_reference_data,
+)
+from app.database.db import create_session
+
+
+def _ingest_file_from_path(
+    abs_path: str,
+    asset_hash: str,
+    size_bytes: int,
+    mtime_ns: int,
+    mime_type: str | None = None,
+    info_name: str | None = None,
+    owner_id: str = "",
+    preview_id: str | None = None,
+    user_metadata: UserMetadata = None,
+    tags: Sequence[str] = (),
+    tag_origin: str = "manual",
+    require_existing_tags: bool = False,
+) -> IngestResult:
+    locator = os.path.abspath(abs_path)
+    user_metadata = user_metadata or {}
+
+    asset_created = False
+    asset_updated = False
+    ref_created = False
+    ref_updated = False
+    reference_id: str | None = None
+
+    with create_session() as session:
+        if preview_id:
+            if preview_id not in get_existing_asset_ids(session, [preview_id]):
+                preview_id = None
+
+        asset, asset_created, asset_updated = upsert_asset(
+            session,
+            asset_hash=asset_hash,
+            size_bytes=size_bytes,
+            mime_type=mime_type,
+        )
+
+        ref_created, ref_updated = upsert_reference(
+            session,
+            asset_id=asset.id,
+            file_path=locator,
+            name=info_name or os.path.basename(locator),
+            mtime_ns=mtime_ns,
+            owner_id=owner_id,
+        )
+
+        # Get the reference we just created/updated
+        ref = get_reference_by_file_path(session, locator)
+        if ref:
+            reference_id = ref.id
+
+            if preview_id and ref.preview_id != preview_id:
+                ref.preview_id = preview_id
+
+            norm = normalize_tags(list(tags))
+            if norm:
+                if require_existing_tags:
+                    validate_tags_exist(session, norm)
+                add_tags_to_reference(
+                    session,
+                    reference_id=reference_id,
+                    tags=norm,
+                    origin=tag_origin,
+                    create_if_missing=not require_existing_tags,
+                )
+
+            _update_metadata_with_filename(
+                session,
+                reference_id=reference_id,
+                file_path=ref.file_path,
+                current_metadata=ref.user_metadata,
+                user_metadata=user_metadata,
+            )
+
+        try:
+            remove_missing_tag_for_asset_id(session, asset_id=asset.id)
+        except Exception:
+            logging.exception("Failed to clear 'missing' tag for asset %s", asset.id)
+
+        session.commit()
+
+    return IngestResult(
+        asset_created=asset_created,
+        asset_updated=asset_updated,
+        ref_created=ref_created,
+        ref_updated=ref_updated,
+        reference_id=reference_id,
+    )
+
+
+def _register_existing_asset(
+    asset_hash: str,
+    name: str,
+    user_metadata: UserMetadata = None,
+    tags: list[str] | None = None,
+    tag_origin: str = "manual",
+    owner_id: str = "",
+) -> RegisterAssetResult:
+    user_metadata = user_metadata or {}
+
+    with create_session() as session:
+        asset = get_asset_by_hash(session, asset_hash=asset_hash)
+        if not asset:
+            raise ValueError(f"No asset with hash {asset_hash}")
+
+        ref, ref_created = get_or_create_reference(
+            session,
+            asset_id=asset.id,
+            owner_id=owner_id,
+            name=name,
+        )
+
+        if not ref_created:
+            tag_names = get_reference_tags(session, reference_id=ref.id)
+            result = RegisterAssetResult(
+                ref=extract_reference_data(ref),
+                asset=extract_asset_data(asset),
+                tags=tag_names,
+                created=False,
+            )
+            session.commit()
+            return result
+
+        new_meta = dict(user_metadata)
+        computed_filename = compute_relative_filename(ref.file_path) if ref.file_path else None
+        if computed_filename:
+            new_meta["filename"] = computed_filename
+
+        if new_meta:
+            set_reference_metadata(
+                session,
+                reference_id=ref.id,
+                user_metadata=new_meta,
+            )
+
+        if tags is not None:
+            set_reference_tags(
+                session,
+                reference_id=ref.id,
+                tags=tags,
+                origin=tag_origin,
+            )
+
+        tag_names = get_reference_tags(session, reference_id=ref.id)
+        session.refresh(ref)
+        result = RegisterAssetResult(
+            ref=extract_reference_data(ref),
+            asset=extract_asset_data(asset),
+            tags=tag_names,
+            created=True,
+        )
+        session.commit()
+
+        return result
+
+
+
+def _update_metadata_with_filename(
+    session: Session,
+    reference_id: str,
+    file_path: str | None,
+    current_metadata: dict | None,
+    user_metadata: dict[str, Any],
+) -> None:
+    computed_filename = compute_relative_filename(file_path) if file_path else None
+
+    current_meta = current_metadata or {}
+    new_meta = dict(current_meta)
+    for k, v in user_metadata.items():
+        new_meta[k] = v
+    if computed_filename:
+        new_meta["filename"] = computed_filename
+
+    if new_meta != current_meta:
+        set_reference_metadata(
+            session,
+            reference_id=reference_id,
+            user_metadata=new_meta,
+        )
+
+
+def _sanitize_filename(name: str | None, fallback: str) -> str:
+    n = os.path.basename((name or "").strip() or fallback)
+    return n if n else fallback
+
+
+class HashMismatchError(Exception):
+    pass
+
+
+class DependencyMissingError(Exception):
+    def __init__(self, message: str):
+        self.message = message
+        super().__init__(message)
+
+
+def upload_from_temp_path(
+    temp_path: str,
+    name: str | None = None,
+    tags: list[str] | None = None,
+    user_metadata: dict | None = None,
+    client_filename: str | None = None,
+    owner_id: str = "",
+    expected_hash: str | None = None,
+) -> UploadResult:
+    try:
+        digest, _ = hashing.compute_blake3_hash(temp_path)
+    except ImportError as e:
+        raise DependencyMissingError(str(e))
+    except Exception as e:
+        raise RuntimeError(f"failed to hash uploaded file: {e}")
+    asset_hash = "blake3:" + digest
+
+    if expected_hash and asset_hash != expected_hash.strip().lower():
+        raise HashMismatchError("Uploaded file hash does not match provided hash.")
+
+    with create_session() as session:
+        existing = get_asset_by_hash(session, asset_hash=asset_hash)
+
+    if existing is not None:
+        with contextlib.suppress(Exception):
+            if temp_path and os.path.exists(temp_path):
+                os.remove(temp_path)
+
+        display_name = _sanitize_filename(name or client_filename, fallback=digest)
+        result = _register_existing_asset(
+            asset_hash=asset_hash,
+            name=display_name,
+            user_metadata=user_metadata or {},
+            tags=tags or [],
+            tag_origin="manual",
+            owner_id=owner_id,
+        )
+        return UploadResult(
+            ref=result.ref,
+            asset=result.asset,
+            tags=result.tags,
+            created_new=False,
+        )
+
+    if not tags:
+        raise ValueError("tags are required for new asset uploads")
+    base_dir, subdirs = resolve_destination_from_tags(tags)
+    dest_dir = os.path.join(base_dir, *subdirs) if subdirs else base_dir
+    os.makedirs(dest_dir, exist_ok=True)
+
+    src_for_ext = (client_filename or name or "").strip()
+    _ext = os.path.splitext(os.path.basename(src_for_ext))[1] if src_for_ext else ""
+    ext = _ext if 0 < len(_ext) <= 16 else ""
+    hashed_basename = f"{digest}{ext}"
+    dest_abs = os.path.abspath(os.path.join(dest_dir, hashed_basename))
+    validate_path_within_base(dest_abs, base_dir)
+
+    content_type = (
+        mimetypes.guess_type(os.path.basename(src_for_ext), strict=False)[0]
+        or mimetypes.guess_type(hashed_basename, strict=False)[0]
+        or "application/octet-stream"
+    )
+
+    try:
+        os.replace(temp_path, dest_abs)
+    except Exception as e:
+        raise RuntimeError(f"failed to move uploaded file into place: {e}")
+
+    try:
+        size_bytes, mtime_ns = get_size_and_mtime_ns(dest_abs)
+    except OSError as e:
+        raise RuntimeError(f"failed to stat destination file: {e}")
+
+    ingest_result = _ingest_file_from_path(
+        asset_hash=asset_hash,
+        abs_path=dest_abs,
+        size_bytes=size_bytes,
+        mtime_ns=mtime_ns,
+        mime_type=content_type,
+        info_name=_sanitize_filename(name or client_filename, fallback=digest),
+        owner_id=owner_id,
+        preview_id=None,
+        user_metadata=user_metadata or {},
+        tags=tags,
+        tag_origin="manual",
+        require_existing_tags=False,
+    )
+    reference_id = ingest_result.reference_id
+    if not reference_id:
+        raise RuntimeError("failed to create asset reference")
+
+    with create_session() as session:
+        pair = fetch_reference_and_asset(
+            session, reference_id=reference_id, owner_id=owner_id
+        )
+        if not pair:
+            raise RuntimeError("inconsistent DB state after ingest")
+        ref, asset = pair
+        tag_names = get_reference_tags(session, reference_id=ref.id)
+
+    return UploadResult(
+        ref=extract_reference_data(ref),
+        asset=extract_asset_data(asset),
+        tags=tag_names,
+        created_new=ingest_result.asset_created,
+    )
+
+
+def create_from_hash(
+    hash_str: str,
+    name: str,
+    tags: list[str] | None = None,
+    user_metadata: dict | None = None,
+    owner_id: str = "",
+) -> UploadResult | None:
+    canonical = hash_str.strip().lower()
+
+    with create_session() as session:
+        asset = get_asset_by_hash(session, asset_hash=canonical)
+        if not asset:
+            return None
+
+    result = _register_existing_asset(
+        asset_hash=canonical,
+        name=_sanitize_filename(
+            name, fallback=canonical.split(":", 1)[1] if ":" in canonical else canonical
+        ),
+        user_metadata=user_metadata or {},
+        tags=tags or [],
+        tag_origin="manual",
+        owner_id=owner_id,
+    )
+
+    return UploadResult(
+        ref=result.ref,
+        asset=result.asset,
+        tags=result.tags,
+        created_new=False,
+    )

app/assets/services/metadata_extract.py

@@ -0,0 +1,329 @@
+"""Metadata extraction for asset scanning.
+
+Tier 1: Filesystem metadata (zero parsing)
+Tier 2: Safetensors header metadata (fast JSON read only)
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import mimetypes
+import os
+import struct
+from dataclasses import dataclass
+from typing import Any
+
+from utils.mime_types import init_mime_types
+
+init_mime_types()
+
+# Supported safetensors extensions
+SAFETENSORS_EXTENSIONS = frozenset({".safetensors", ".sft"})
+
+# Maximum safetensors header size to read (8MB)
+MAX_SAFETENSORS_HEADER_SIZE = 8 * 1024 * 1024
+
+
+@dataclass
+class ExtractedMetadata:
+    """Metadata extracted from a file during scanning."""
+
+    # Tier 1: Filesystem (always available)
+    filename: str = ""
+    file_path: str = ""  # Full absolute path to the file
+    content_length: int = 0
+    content_type: str | None = None
+    format: str = ""  # file extension without dot
+
+    # Tier 2: Safetensors header (if available)
+    base_model: str | None = None
+    trained_words: list[str] | None = None
+    air: str | None = None  # CivitAI AIR identifier
+    has_preview_images: bool = False
+
+    # Source provenance (populated if embedded in safetensors)
+    source_url: str | None = None
+    source_arn: str | None = None
+    repo_url: str | None = None
+    preview_url: str | None = None
+    source_hash: str | None = None
+
+    # HuggingFace specific
+    repo_id: str | None = None
+    revision: str | None = None
+    filepath: str | None = None
+    resolve_url: str | None = None
+
+    def to_user_metadata(self) -> dict[str, Any]:
+        """Convert to user_metadata dict for AssetReference.user_metadata JSON field."""
+        data: dict[str, Any] = {
+            "filename": self.filename,
+            "content_length": self.content_length,
+            "format": self.format,
+        }
+        if self.file_path:
+            data["file_path"] = self.file_path
+        if self.content_type:
+            data["content_type"] = self.content_type
+
+        # Tier 2 fields
+        if self.base_model:
+            data["base_model"] = self.base_model
+        if self.trained_words:
+            data["trained_words"] = self.trained_words
+        if self.air:
+            data["air"] = self.air
+        if self.has_preview_images:
+            data["has_preview_images"] = True
+
+        # Source provenance
+        if self.source_url:
+            data["source_url"] = self.source_url
+        if self.source_arn:
+            data["source_arn"] = self.source_arn
+        if self.repo_url:
+            data["repo_url"] = self.repo_url
+        if self.preview_url:
+            data["preview_url"] = self.preview_url
+        if self.source_hash:
+            data["source_hash"] = self.source_hash
+
+        # HuggingFace
+        if self.repo_id:
+            data["repo_id"] = self.repo_id
+        if self.revision:
+            data["revision"] = self.revision
+        if self.filepath:
+            data["filepath"] = self.filepath
+        if self.resolve_url:
+            data["resolve_url"] = self.resolve_url
+
+        return data
+
+    def to_meta_rows(self, reference_id: str) -> list[dict]:
+        """Convert to asset_reference_meta rows for typed/indexed querying."""
+        rows: list[dict] = []
+
+        def add_str(key: str, val: str | None, ordinal: int = 0) -> None:
+            if val:
+                rows.append({
+                    "asset_reference_id": reference_id,
+                    "key": key,
+                    "ordinal": ordinal,
+                    "val_str": val[:2048] if len(val) > 2048 else val,
+                    "val_num": None,
+                    "val_bool": None,
+                    "val_json": None,
+                })
+
+        def add_num(key: str, val: int | float | None) -> None:
+            if val is not None:
+                rows.append({
+                    "asset_reference_id": reference_id,
+                    "key": key,
+                    "ordinal": 0,
+                    "val_str": None,
+                    "val_num": val,
+                    "val_bool": None,
+                    "val_json": None,
+                })
+
+        def add_bool(key: str, val: bool | None) -> None:
+            if val is not None:
+                rows.append({
+                    "asset_reference_id": reference_id,
+                    "key": key,
+                    "ordinal": 0,
+                    "val_str": None,
+                    "val_num": None,
+                    "val_bool": val,
+                    "val_json": None,
+                })
+
+        # Tier 1
+        add_str("filename", self.filename)
+        add_num("content_length", self.content_length)
+        add_str("content_type", self.content_type)
+        add_str("format", self.format)
+
+        # Tier 2
+        add_str("base_model", self.base_model)
+        add_str("air", self.air)
+        has_previews = self.has_preview_images if self.has_preview_images else None
+        add_bool("has_preview_images", has_previews)
+
+        # trained_words as multiple rows with ordinals
+        if self.trained_words:
+            for i, word in enumerate(self.trained_words[:100]):  # limit to 100 words
+                add_str("trained_words", word, ordinal=i)
+
+        # Source provenance
+        add_str("source_url", self.source_url)
+        add_str("source_arn", self.source_arn)
+        add_str("repo_url", self.repo_url)
+        add_str("preview_url", self.preview_url)
+        add_str("source_hash", self.source_hash)
+
+        # HuggingFace
+        add_str("repo_id", self.repo_id)
+        add_str("revision", self.revision)
+        add_str("filepath", self.filepath)
+        add_str("resolve_url", self.resolve_url)
+
+        return rows
+
+
+def _read_safetensors_header(
+    path: str, max_size: int = MAX_SAFETENSORS_HEADER_SIZE
+) -> dict[str, Any] | None:
+    """Read only the JSON header from a safetensors file.
+
+    This is very fast - reads 8 bytes for header length, then the JSON header.
+    No tensor data is loaded.
+
+    Args:
+        path: Absolute path to safetensors file
+        max_size: Maximum header size to read (default 8MB)
+
+    Returns:
+        Parsed header dict or None if failed
+    """
+    try:
+        with open(path, "rb") as f:
+            header_bytes = f.read(8)
+            if len(header_bytes) < 8:
+                return None
+            length_of_header = struct.unpack("<Q", header_bytes)[0]
+            if length_of_header > max_size:
+                return None
+            header_data = f.read(length_of_header)
+            if len(header_data) < length_of_header:
+                return None
+            return json.loads(header_data.decode("utf-8"))
+    except (OSError, json.JSONDecodeError, UnicodeDecodeError, struct.error):
+        return None
+
+
+def _extract_safetensors_metadata(
+    header: dict[str, Any], meta: ExtractedMetadata
+) -> None:
+    """Extract metadata from safetensors header __metadata__ section.
+
+    Modifies meta in-place.
+    """
+    st_meta = header.get("__metadata__", {})
+    if not isinstance(st_meta, dict):
+        return
+
+    # Common model metadata
+    meta.base_model = (
+        st_meta.get("ss_base_model_version")
+        or st_meta.get("modelspec.base_model")
+        or st_meta.get("base_model")
+    )
+
+    # Trained words / trigger words
+    trained_words = st_meta.get("ss_tag_frequency")
+    if trained_words and isinstance(trained_words, str):
+        try:
+            tag_freq = json.loads(trained_words)
+            # Extract unique tags from all datasets
+            all_tags: set[str] = set()
+            for dataset_tags in tag_freq.values():
+                if isinstance(dataset_tags, dict):
+                    all_tags.update(dataset_tags.keys())
+            if all_tags:
+                meta.trained_words = sorted(all_tags)[:100]
+        except json.JSONDecodeError:
+            pass
+
+    # Direct trained_words field (some formats)
+    if not meta.trained_words:
+        tw = st_meta.get("trained_words")
+        if isinstance(tw, str):
+            try:
+                parsed = json.loads(tw)
+                if isinstance(parsed, list):
+                    meta.trained_words = [str(x) for x in parsed]
+                else:
+                    meta.trained_words = [w.strip() for w in tw.split(",") if w.strip()]
+            except json.JSONDecodeError:
+                meta.trained_words = [w.strip() for w in tw.split(",") if w.strip()]
+        elif isinstance(tw, list):
+            meta.trained_words = [str(x) for x in tw]
+
+    # CivitAI AIR
+    meta.air = st_meta.get("air") or st_meta.get("modelspec.air")
+
+    # Preview images (ssmd_cover_images)
+    cover_images = st_meta.get("ssmd_cover_images")
+    if cover_images:
+        meta.has_preview_images = True
+
+    # Source provenance fields
+    meta.source_url = st_meta.get("source_url")
+    meta.source_arn = st_meta.get("source_arn")
+    meta.repo_url = st_meta.get("repo_url")
+    meta.preview_url = st_meta.get("preview_url")
+    meta.source_hash = st_meta.get("source_hash") or st_meta.get("sshs_model_hash")
+
+    # HuggingFace fields
+    meta.repo_id = st_meta.get("repo_id") or st_meta.get("hf_repo_id")
+    meta.revision = st_meta.get("revision") or st_meta.get("hf_revision")
+    meta.filepath = st_meta.get("filepath") or st_meta.get("hf_filepath")
+    meta.resolve_url = st_meta.get("resolve_url") or st_meta.get("hf_url")
+
+
+def extract_file_metadata(
+    abs_path: str,
+    stat_result: os.stat_result | None = None,
+    enable_safetensors: bool = True,
+    relative_filename: str | None = None,
+) -> ExtractedMetadata:
+    """Extract metadata from a file using tier 1 and optionally tier 2 methods.
+
+    Tier 1 (always): Filesystem metadata from path and stat
+    Tier 2 (optional): Safetensors header parsing if applicable
+
+    Args:
+        abs_path: Absolute path to the file
+        stat_result: Optional pre-fetched stat result (saves a syscall)
+        enable_safetensors: Whether to parse safetensors headers (tier 2)
+        relative_filename: Optional relative filename to use instead of basename
+            (e.g., "flux/123/model.safetensors" for model paths)
+
+    Returns:
+        ExtractedMetadata with all available fields populated
+    """
+    meta = ExtractedMetadata()
+
+    # Tier 1: Filesystem metadata
+    meta.filename = relative_filename or os.path.basename(abs_path)
+    meta.file_path = abs_path
+    _, ext = os.path.splitext(abs_path)
+    meta.format = ext.lstrip(".").lower() if ext else ""
+
+    mime_type, _ = mimetypes.guess_type(abs_path)
+    meta.content_type = mime_type
+
+    # Size from stat
+    if stat_result is None:
+        try:
+            stat_result = os.stat(abs_path, follow_symlinks=True)
+        except OSError:
+            pass
+
+    if stat_result:
+        meta.content_length = stat_result.st_size
+
+    # Tier 2: Safetensors header (if applicable and enabled)
+    if enable_safetensors and ext.lower() in SAFETENSORS_EXTENSIONS:
+        header = _read_safetensors_header(abs_path)
+        if header:
+            try:
+                _extract_safetensors_metadata(header, meta)
+            except Exception as e:
+                logging.debug("Safetensors meta extract failed %s: %s", abs_path, e)
+
+    return meta

app/assets/services/path_utils.py

@@ -0,0 +1,167 @@
+import os
+from pathlib import Path
+from typing import Literal
+
+import folder_paths
+from app.assets.helpers import normalize_tags
+
+
+_NON_MODEL_FOLDER_NAMES = frozenset({"custom_nodes"})
+
+
+def get_comfy_models_folders() -> list[tuple[str, list[str]]]:
+    """Build list of (folder_name, base_paths[]) for all model locations.
+
+    Includes every category registered in folder_names_and_paths,
+    regardless of whether its paths are under the main models_dir,
+    but excludes non-model entries like custom_nodes.
+    """
+    targets: list[tuple[str, list[str]]] = []
+    for name, values in folder_paths.folder_names_and_paths.items():
+        if name in _NON_MODEL_FOLDER_NAMES:
+            continue
+        paths, _exts = values[0], values[1]
+        if paths:
+            targets.append((name, paths))
+    return targets
+
+
+def resolve_destination_from_tags(tags: list[str]) -> tuple[str, list[str]]:
+    """Validates and maps tags -> (base_dir, subdirs_for_fs)"""
+    if not tags:
+        raise ValueError("tags must not be empty")
+    root = tags[0].lower()
+    if root == "models":
+        if len(tags) < 2:
+            raise ValueError("at least two tags required for model asset")
+        try:
+            bases = folder_paths.folder_names_and_paths[tags[1]][0]
+        except KeyError:
+            raise ValueError(f"unknown model category '{tags[1]}'")
+        if not bases:
+            raise ValueError(f"no base path configured for category '{tags[1]}'")
+        base_dir = os.path.abspath(bases[0])
+        raw_subdirs = tags[2:]
+    elif root == "input":
+        base_dir = os.path.abspath(folder_paths.get_input_directory())
+        raw_subdirs = tags[1:]
+    elif root == "output":
+        base_dir = os.path.abspath(folder_paths.get_output_directory())
+        raw_subdirs = tags[1:]
+    else:
+        raise ValueError(f"unknown root tag '{tags[0]}'; expected 'models', 'input', or 'output'")
+    _sep_chars = frozenset(("/", "\\", os.sep))
+    for i in raw_subdirs:
+        if i in (".", "..") or _sep_chars & set(i):
+            raise ValueError("invalid path component in tags")
+
+    return base_dir, raw_subdirs if raw_subdirs else []
+
+
+def validate_path_within_base(candidate: str, base: str) -> None:
+    cand_abs = Path(os.path.abspath(candidate))
+    base_abs = Path(os.path.abspath(base))
+    if not cand_abs.is_relative_to(base_abs):
+        raise ValueError("destination escapes base directory")
+
+
+def compute_relative_filename(file_path: str) -> str | None:
+    """
+    Return the model's path relative to the last well-known folder (the model category),
+    using forward slashes, eg:
+      /.../models/checkpoints/flux/123/flux.safetensors -> "flux/123/flux.safetensors"
+      /.../models/text_encoders/clip_g.safetensors -> "clip_g.safetensors"
+
+    For non-model paths, returns None.
+    """
+    try:
+        root_category, rel_path = get_asset_category_and_relative_path(file_path)
+    except ValueError:
+        return None
+
+    p = Path(rel_path)
+    parts = [seg for seg in p.parts if seg not in (".", "..", p.anchor)]
+    if not parts:
+        return None
+
+    if root_category == "models":
+        # parts[0] is the category ("checkpoints", "vae", etc) – drop it
+        inside = parts[1:] if len(parts) > 1 else [parts[0]]
+        return "/".join(inside)
+    return "/".join(parts)  # input/output: keep all parts
+
+
+def get_asset_category_and_relative_path(
+    file_path: str,
+) -> tuple[Literal["input", "output", "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()
+      - 'models': under any base path from get_comfy_models_folders()
+
+    Returns:
+        (root_category, relative_path_inside_that_root)
+
+    Raises:
+        ValueError: path does not belong to any known root.
+    """
+    fp_abs = os.path.abspath(file_path)
+
+    def _check_is_within(child: str, parent: str) -> bool:
+        return Path(child).is_relative_to(parent)
+
+    def _compute_relative(child: str, parent: str) -> str:
+        # Normalize relative path, stripping any leading ".." components
+        # by anchoring to root (os.sep) then computing relpath back from it.
+        return os.path.relpath(
+            os.path.join(os.sep, os.path.relpath(child, parent)), os.sep
+        )
+
+    # 1) input
+    input_base = os.path.abspath(folder_paths.get_input_directory())
+    if _check_is_within(fp_abs, input_base):
+        return "input", _compute_relative(fp_abs, input_base)
+
+    # 2) output
+    output_base = os.path.abspath(folder_paths.get_output_directory())
+    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)
+    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:
+            base_abs = os.path.abspath(b)
+            if not _check_is_within(fp_abs, base_abs):
+                continue
+            cand = (len(base_abs), bucket, _compute_relative(fp_abs, base_abs))
+            if best is None or cand[0] > best[0]:
+                best = cand
+
+    if best is not None:
+        _, bucket, rel_inside = best
+        combined = os.path.join(bucket, rel_inside)
+        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}"
+    )
+
+
+def get_name_and_tags_from_asset_path(file_path: str) -> tuple[str, list[str]]:
+    """Return (name, tags) derived from a filesystem path.
+
+    - name: base filename with extension
+    - tags: [root_category] + parent folder names in order
+
+    Raises:
+        ValueError: path does not belong to any known root.
+    """
+    root_category, some_path = get_asset_category_and_relative_path(file_path)
+    p = Path(some_path)
+    parent_parts = [
+        part for part in p.parent.parts if part not in (".", "..", p.anchor)
+    ]
+    return p.name, list(dict.fromkeys(normalize_tags([root_category, *parent_parts])))

app/assets/services/schemas.py

@@ -0,0 +1,109 @@
+from dataclasses import dataclass
+from datetime import datetime
+from typing import Any, NamedTuple
+
+from app.assets.database.models import Asset, AssetReference
+
+UserMetadata = dict[str, Any] | None
+
+
+@dataclass(frozen=True)
+class AssetData:
+    hash: str | None
+    size_bytes: int | None
+    mime_type: str | None
+
+
+@dataclass(frozen=True)
+class ReferenceData:
+    """Data transfer object for AssetReference."""
+
+    id: str
+    name: str
+    file_path: str | None
+    user_metadata: UserMetadata
+    preview_id: str | None
+    created_at: datetime
+    updated_at: datetime
+    last_access_time: datetime | None
+
+
+@dataclass(frozen=True)
+class AssetDetailResult:
+    ref: ReferenceData
+    asset: AssetData | None
+    tags: list[str]
+
+
+@dataclass(frozen=True)
+class RegisterAssetResult:
+    ref: ReferenceData
+    asset: AssetData
+    tags: list[str]
+    created: bool
+
+
+@dataclass(frozen=True)
+class IngestResult:
+    asset_created: bool
+    asset_updated: bool
+    ref_created: bool
+    ref_updated: bool
+    reference_id: str | None
+
+
+class TagUsage(NamedTuple):
+    name: str
+    tag_type: str
+    count: int
+
+
+@dataclass(frozen=True)
+class AssetSummaryData:
+    ref: ReferenceData
+    asset: AssetData | None
+    tags: list[str]
+
+
+@dataclass(frozen=True)
+class ListAssetsResult:
+    items: list[AssetSummaryData]
+    total: int
+
+
+@dataclass(frozen=True)
+class DownloadResolutionResult:
+    abs_path: str
+    content_type: str
+    download_name: str
+
+
+@dataclass(frozen=True)
+class UploadResult:
+    ref: ReferenceData
+    asset: AssetData
+    tags: list[str]
+    created_new: bool
+
+
+def extract_reference_data(ref: AssetReference) -> ReferenceData:
+    return ReferenceData(
+        id=ref.id,
+        name=ref.name,
+        file_path=ref.file_path,
+        user_metadata=ref.user_metadata,
+        preview_id=ref.preview_id,
+        created_at=ref.created_at,
+        updated_at=ref.updated_at,
+        last_access_time=ref.last_access_time,
+    )
+
+
+def extract_asset_data(asset: Asset | None) -> AssetData | None:
+    if asset is None:
+        return None
+    return AssetData(
+        hash=asset.hash,
+        size_bytes=asset.size_bytes,
+        mime_type=asset.mime_type,
+    )

app/assets/services/tagging.py

@@ -0,0 +1,75 @@
+from app.assets.database.queries import (
+    AddTagsResult,
+    RemoveTagsResult,
+    add_tags_to_reference,
+    get_reference_with_owner_check,
+    list_tags_with_usage,
+    remove_tags_from_reference,
+)
+from app.assets.services.schemas import TagUsage
+from app.database.db import create_session
+
+
+def apply_tags(
+    reference_id: str,
+    tags: list[str],
+    origin: str = "manual",
+    owner_id: str = "",
+) -> AddTagsResult:
+    with create_session() as session:
+        ref_row = get_reference_with_owner_check(session, reference_id, owner_id)
+
+        result = add_tags_to_reference(
+            session,
+            reference_id=reference_id,
+            tags=tags,
+            origin=origin,
+            create_if_missing=True,
+            reference_row=ref_row,
+        )
+        session.commit()
+
+    return result
+
+
+def remove_tags(
+    reference_id: str,
+    tags: list[str],
+    owner_id: str = "",
+) -> RemoveTagsResult:
+    with create_session() as session:
+        get_reference_with_owner_check(session, reference_id, owner_id)
+
+        result = remove_tags_from_reference(
+            session,
+            reference_id=reference_id,
+            tags=tags,
+        )
+        session.commit()
+
+    return result
+
+
+def list_tags(
+    prefix: str | None = None,
+    limit: int = 100,
+    offset: int = 0,
+    order: str = "count_desc",
+    include_zero: bool = True,
+    owner_id: str = "",
+) -> tuple[list[TagUsage], int]:
+    limit = max(1, min(1000, limit))
+    offset = max(0, offset)
+
+    with create_session() as session:
+        rows, total = list_tags_with_usage(
+            session,
+            prefix=prefix,
+            limit=limit,
+            offset=offset,
+            include_zero=include_zero,
+            order=order,
+            owner_id=owner_id,
+        )
+
+    return [TagUsage(name, tag_type, count) for name, tag_type, count in rows], total

app/database/db.py

@@ -3,6 +3,7 @@ import os
 import shutil
 from app.logger import log_startup_warning
 from utils.install_util import get_missing_requirements_message
+from filelock import FileLock, Timeout
 from comfy.cli_args import args
 
 _DB_AVAILABLE = False
@@ -14,8 +15,12 @@ try:
     from alembic.config import Config
     from alembic.runtime.migration import MigrationContext
     from alembic.script import ScriptDirectory
-    from sqlalchemy import create_engine
+    from sqlalchemy import create_engine, event
     from sqlalchemy.orm import sessionmaker
+    from sqlalchemy.pool import StaticPool
+
+    from app.database.models import Base
+    import app.assets.database.models  # noqa: F401 — register models with Base.metadata
 
     _DB_AVAILABLE = True
 except ImportError as e:
@@ -65,9 +70,69 @@ def get_db_path():
         raise ValueError(f"Unsupported database URL '{url}'.")
 
 
+_db_lock = None
+
+def _acquire_file_lock(db_path):
+    """Acquire an OS-level file lock to prevent multi-process access.
+
+    Uses filelock for cross-platform support (macOS, Linux, Windows).
+    The OS automatically releases the lock when the process exits, even on crashes.
+    """
+    global _db_lock
+    lock_path = db_path + ".lock"
+    _db_lock = FileLock(lock_path)
+    try:
+        _db_lock.acquire(timeout=0)
+    except Timeout:
+        raise RuntimeError(
+            f"Could not acquire lock on database '{db_path}'. "
+            "Another ComfyUI process may already be using it. "
+            "Use --database-url to specify a separate database file."
+        )
+
+
+def _is_memory_db(db_url):
+    """Check if the database URL refers to an in-memory SQLite database."""
+    return db_url in ("sqlite:///:memory:", "sqlite://")
+
+
 def init_db():
     db_url = args.database_url
     logging.debug(f"Database URL: {db_url}")
+
+    if _is_memory_db(db_url):
+        _init_memory_db(db_url)
+    else:
+        _init_file_db(db_url)
+
+
+def _init_memory_db(db_url):
+    """Initialize an in-memory SQLite database using metadata.create_all.
+
+    Alembic migrations don't work with in-memory SQLite because each
+    connection gets its own separate database — tables created by Alembic's
+    internal connection are lost immediately.
+    """
+    engine = create_engine(
+        db_url,
+        poolclass=StaticPool,
+        connect_args={"check_same_thread": False},
+    )
+
+    @event.listens_for(engine, "connect")
+    def set_sqlite_pragma(dbapi_connection, connection_record):
+        cursor = dbapi_connection.cursor()
+        cursor.execute("PRAGMA foreign_keys=ON")
+        cursor.close()
+
+    Base.metadata.create_all(engine)
+
+    global Session
+    Session = sessionmaker(bind=engine)
+
+
+def _init_file_db(db_url):
+    """Initialize a file-backed SQLite database using Alembic migrations."""
     db_path = get_db_path()
     db_exists = os.path.exists(db_path)
 
@@ -75,6 +140,14 @@ def init_db():
 
     # Check if we need to upgrade
     engine = create_engine(db_url)
+
+    # Enable foreign key enforcement for SQLite
+    @event.listens_for(engine, "connect")
+    def set_sqlite_pragma(dbapi_connection, connection_record):
+        cursor = dbapi_connection.cursor()
+        cursor.execute("PRAGMA foreign_keys=ON")
+        cursor.close()
+
     conn = engine.connect()
 
     context = MigrationContext.configure(conn)
@@ -104,6 +177,12 @@ def init_db():
             logging.exception("Error upgrading database: ")
             raise e
 
+    # Acquire an OS-level file lock after migrations are complete.
+    # Alembic uses its own connection, so we must wait until it's done
+    # before locking — otherwise our own lock blocks the migration.
+    conn.close()
+    _acquire_file_lock(db_path)
+
     global Session
     Session = sessionmaker(bind=engine)
 

app/frontend_management.py

@@ -17,7 +17,7 @@ from importlib.metadata import version
 import requests
 from typing_extensions import NotRequired
 
-from utils.install_util import get_missing_requirements_message, requirements_path
+from utils.install_util import get_missing_requirements_message, get_required_packages_versions
 
 from comfy.cli_args import DEFAULT_VERSION_STRING
 import app.logger
@@ -45,25 +45,7 @@ def get_installed_frontend_version():
 
 
 def get_required_frontend_version():
-    """Get the required frontend version from requirements.txt."""
-    try:
-        with open(requirements_path, "r", encoding="utf-8") as f:
-            for line in f:
-                line = line.strip()
-                if line.startswith("comfyui-frontend-package=="):
-                    version_str = line.split("==")[-1]
-                    if not is_valid_version(version_str):
-                        logging.error(f"Invalid version format in requirements.txt: {version_str}")
-                        return None
-                    return version_str
-            logging.error("comfyui-frontend-package not found in requirements.txt")
-            return None
-    except FileNotFoundError:
-        logging.error("requirements.txt not found. Cannot determine required frontend version.")
-        return None
-    except Exception as e:
-        logging.error(f"Error reading requirements.txt: {e}")
-        return None
+    return get_required_packages_versions().get("comfyui-frontend-package", None)
 
 
 def check_frontend_version():
@@ -217,25 +199,7 @@ class FrontendManager:
 
     @classmethod
     def get_required_templates_version(cls) -> str:
-        """Get the required workflow templates version from requirements.txt."""
-        try:
-            with open(requirements_path, "r", encoding="utf-8") as f:
-                for line in f:
-                    line = line.strip()
-                    if line.startswith("comfyui-workflow-templates=="):
-                        version_str = line.split("==")[-1]
-                        if not is_valid_version(version_str):
-                            logging.error(f"Invalid templates version format in requirements.txt: {version_str}")
-                            return None
-                        return version_str
-                logging.error("comfyui-workflow-templates not found in requirements.txt")
-                return None
-        except FileNotFoundError:
-            logging.error("requirements.txt not found. Cannot determine required templates version.")
-            return None
-        except Exception as e:
-            logging.error(f"Error reading requirements.txt: {e}")
-            return None
+        return get_required_packages_versions().get("comfyui-workflow-templates", None)
 
     @classmethod
     def default_frontend_path(cls) -> str:

app/node_replace_manager.py

@@ -0,0 +1,107 @@
+from __future__ import annotations
+
+from aiohttp import web
+
+from typing import TYPE_CHECKING, TypedDict
+if TYPE_CHECKING:
+    from comfy_api.latest._io_public import NodeReplace
+
+from comfy_execution.graph_utils import is_link
+import nodes
+
+class NodeStruct(TypedDict):
+    inputs: dict[str, str | int | float | bool | tuple[str, int]]
+    class_type: str
+    _meta: dict[str, str]
+
+def copy_node_struct(node_struct: NodeStruct, empty_inputs: bool = False) -> NodeStruct:
+    new_node_struct = node_struct.copy()
+    if empty_inputs:
+        new_node_struct["inputs"] = {}
+    else:
+        new_node_struct["inputs"] = node_struct["inputs"].copy()
+    new_node_struct["_meta"] = node_struct["_meta"].copy()
+    return new_node_struct
+
+
+class NodeReplaceManager:
+    """Manages node replacement registrations."""
+
+    def __init__(self):
+        self._replacements: dict[str, list[NodeReplace]] = {}
+
+    def register(self, node_replace: NodeReplace):
+        """Register a node replacement mapping."""
+        self._replacements.setdefault(node_replace.old_node_id, []).append(node_replace)
+
+    def get_replacement(self, old_node_id: str) -> list[NodeReplace] | None:
+        """Get replacements for an old node ID."""
+        return self._replacements.get(old_node_id)
+
+    def has_replacement(self, old_node_id: str) -> bool:
+        """Check if a replacement exists for an old node ID."""
+        return old_node_id in self._replacements
+
+    def apply_replacements(self, prompt: dict[str, NodeStruct]):
+        connections: dict[str, list[tuple[str, str, int]]] = {}
+        need_replacement: set[str] = set()
+        for node_number, node_struct in prompt.items():
+            if "class_type" not in node_struct or "inputs" not in node_struct:
+                continue
+            class_type = node_struct["class_type"]
+            # need replacement if not in NODE_CLASS_MAPPINGS and has replacement
+            if class_type not in nodes.NODE_CLASS_MAPPINGS.keys() and self.has_replacement(class_type):
+                need_replacement.add(node_number)
+            # keep track of connections
+            for input_id, input_value in node_struct["inputs"].items():
+                if is_link(input_value):
+                    conn_number = input_value[0]
+                    connections.setdefault(conn_number, []).append((node_number, input_id, input_value[1]))
+        for node_number in need_replacement:
+            node_struct = prompt[node_number]
+            class_type = node_struct["class_type"]
+            replacements = self.get_replacement(class_type)
+            if replacements is None:
+                continue
+            # just use the first replacement
+            replacement = replacements[0]
+            new_node_id = replacement.new_node_id
+            # if replacement is not a valid node, skip trying to replace it as will only cause confusion
+            if new_node_id not in nodes.NODE_CLASS_MAPPINGS.keys():
+                continue
+            # first, replace node id (class_type)
+            new_node_struct = copy_node_struct(node_struct, empty_inputs=True)
+            new_node_struct["class_type"] = new_node_id
+            # TODO: consider replacing display_name in _meta as well for error reporting purposes; would need to query node schema
+            # second, replace inputs
+            if replacement.input_mapping is not None:
+                for input_map in replacement.input_mapping:
+                    if "set_value" in input_map:
+                        new_node_struct["inputs"][input_map["new_id"]] = input_map["set_value"]
+                    elif "old_id" in input_map:
+                        new_node_struct["inputs"][input_map["new_id"]] = node_struct["inputs"][input_map["old_id"]]
+            # finalize input replacement
+            prompt[node_number] = new_node_struct
+            # third, replace outputs
+            if replacement.output_mapping is not None:
+                # re-mapping outputs requires changing the input values of nodes that receive connections from this one
+                if node_number in connections:
+                    for conns in connections[node_number]:
+                        conn_node_number, conn_input_id, old_output_idx = conns
+                        for output_map in replacement.output_mapping:
+                            if output_map["old_idx"] == old_output_idx:
+                                new_output_idx = output_map["new_idx"]
+                                previous_input = prompt[conn_node_number]["inputs"][conn_input_id]
+                                previous_input[1] = new_output_idx
+
+    def as_dict(self):
+        """Serialize all replacements to dict."""
+        return {
+            k: [v.as_dict() for v in v_list]
+            for k, v_list in self._replacements.items()
+        }
+
+    def add_routes(self, routes):
+        @routes.get("/node_replacements")
+        async def get_node_replacements(request):
+            return web.json_response(self.as_dict())

app/subgraph_manager.py

@@ -53,7 +53,7 @@ class SubgraphManager:
         return entry_id, entry
 
     async def load_entry_data(self, entry: SubgraphEntry):
-        with open(entry['path'], 'r') as f:
+        with open(entry['path'], 'r', encoding='utf-8') as f:
             entry['data'] = f.read()
         return entry
 

blueprints/.glsl/Brightness_and_Contrast_1.frag

@@ -0,0 +1,44 @@
+#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+uniform float u_float0; // Brightness slider -100..100
+uniform float u_float1; // Contrast slider -100..100
+
+in vec2 v_texCoord;
+out vec4 fragColor;
+
+const float MID_GRAY = 0.18;  // 18% reflectance
+
+// sRGB gamma 2.2 approximation
+vec3 srgbToLinear(vec3 c) {
+    return pow(max(c, 0.0), vec3(2.2));
+}
+
+vec3 linearToSrgb(vec3 c) {
+    return pow(max(c, 0.0), vec3(1.0/2.2));
+}
+
+float mapBrightness(float b) {
+    return clamp(b / 100.0, -1.0, 1.0);
+}
+
+float mapContrast(float c) {
+    return clamp(c / 100.0 + 1.0, 0.0, 2.0);
+}
+
+void main() {
+    vec4 orig = texture(u_image0, v_texCoord);
+
+    float brightness = mapBrightness(u_float0);
+    float contrast   = mapContrast(u_float1);
+
+    vec3 lin = srgbToLinear(orig.rgb);
+
+    lin = (lin - MID_GRAY) * contrast + brightness + MID_GRAY;
+
+    // Convert back to sRGB
+    vec3 result = linearToSrgb(clamp(lin, 0.0, 1.0));
+
+    fragColor = vec4(result, orig.a);
+}

blueprints/.glsl/Chromatic_Aberration_16.frag

@@ -0,0 +1,72 @@
+#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+uniform vec2 u_resolution;
+uniform int u_int0;      // Mode
+uniform float u_float0;  // Amount (0 to 100)
+
+in vec2 v_texCoord;
+out vec4 fragColor;
+
+const int MODE_LINEAR   = 0;
+const int MODE_RADIAL   = 1;
+const int MODE_BARREL   = 2;
+const int MODE_SWIRL    = 3;
+const int MODE_DIAGONAL = 4;
+
+const float AMOUNT_SCALE = 0.0005;
+const float RADIAL_MULT = 4.0;
+const float BARREL_MULT = 8.0;
+const float INV_SQRT2 = 0.70710678118;
+
+void main() {
+    vec2 uv = v_texCoord;
+    vec4 original = texture(u_image0, uv);
+
+    float amount = u_float0 * AMOUNT_SCALE;
+
+    if (amount < 0.000001) {
+        fragColor = original;
+        return;
+    }
+
+    // Aspect-corrected coordinates for circular effects
+    float aspect = u_resolution.x / u_resolution.y;
+    vec2 centered = uv - 0.5;
+    vec2 corrected = vec2(centered.x * aspect, centered.y);
+    float r = length(corrected);
+    vec2 dir = r > 0.0001 ? corrected / r : vec2(0.0);
+    vec2 offset = vec2(0.0);
+
+    if (u_int0 == MODE_LINEAR) {
+        // Horizontal shift (no aspect correction needed)
+        offset = vec2(amount, 0.0);
+    }
+    else if (u_int0 == MODE_RADIAL) {
+        // Outward from center, stronger at edges
+        offset = dir * r * amount * RADIAL_MULT;
+        offset.x /= aspect;  // Convert back to UV space
+    }
+    else if (u_int0 == MODE_BARREL) {
+        // Lens distortion simulation (r² falloff)
+        offset = dir * r * r * amount * BARREL_MULT;
+        offset.x /= aspect;  // Convert back to UV space
+    }
+    else if (u_int0 == MODE_SWIRL) {
+        // Perpendicular to radial (rotational aberration)
+        vec2 perp = vec2(-dir.y, dir.x);
+        offset = perp * r * amount * RADIAL_MULT;
+        offset.x /= aspect;  // Convert back to UV space
+    }
+    else if (u_int0 == MODE_DIAGONAL) {
+        // 45° offset (no aspect correction needed)
+        offset = vec2(amount, amount) * INV_SQRT2;
+    }
+    
+    float red = texture(u_image0, uv + offset).r;
+    float green = original.g;
+    float blue = texture(u_image0, uv - offset).b;
+    
+    fragColor = vec4(red, green, blue, original.a);
+}

blueprints/.glsl/Color_Adjustment_15.frag

@@ -0,0 +1,78 @@
+#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+uniform float u_float0; // temperature (-100 to 100)
+uniform float u_float1; // tint (-100 to 100)
+uniform float u_float2; // vibrance (-100 to 100)
+uniform float u_float3; // saturation (-100 to 100)
+
+in vec2 v_texCoord;
+out vec4 fragColor;
+
+const float INPUT_SCALE = 0.01;
+const float TEMP_TINT_PRIMARY = 0.3;
+const float TEMP_TINT_SECONDARY = 0.15;
+const float VIBRANCE_BOOST = 2.0;
+const float SATURATION_BOOST = 2.0;
+const float SKIN_PROTECTION = 0.5;
+const float EPSILON = 0.001;
+const vec3 LUMA_WEIGHTS = vec3(0.299, 0.587, 0.114);
+
+void main() {
+    vec4 tex = texture(u_image0, v_texCoord);
+    vec3 color = tex.rgb;
+    
+    // Scale inputs: -100/100 → -1/1
+    float temperature = u_float0 * INPUT_SCALE;
+    float tint = u_float1 * INPUT_SCALE;
+    float vibrance = u_float2 * INPUT_SCALE;
+    float saturation = u_float3 * INPUT_SCALE;
+    
+    // Temperature (warm/cool): positive = warm, negative = cool
+    color.r += temperature * TEMP_TINT_PRIMARY;
+    color.b -= temperature * TEMP_TINT_PRIMARY;
+    
+    // Tint (green/magenta): positive = green, negative = magenta
+    color.g += tint * TEMP_TINT_PRIMARY;
+    color.r -= tint * TEMP_TINT_SECONDARY;
+    color.b -= tint * TEMP_TINT_SECONDARY;
+    
+    // Single clamp after temperature/tint
+    color = clamp(color, 0.0, 1.0);
+    
+    // Vibrance with skin protection
+    if (vibrance != 0.0) {
+        float maxC = max(color.r, max(color.g, color.b));
+        float minC = min(color.r, min(color.g, color.b));
+        float sat = maxC - minC;
+        float gray = dot(color, LUMA_WEIGHTS);
+        
+        if (vibrance < 0.0) {
+            // Desaturate: -100 → gray
+            color = mix(vec3(gray), color, 1.0 + vibrance);
+        } else {
+            // Boost less saturated colors more
+            float vibranceAmt = vibrance * (1.0 - sat);
+            
+            // Branchless skin tone protection
+            float isWarmTone = step(color.b, color.g) * step(color.g, color.r);
+            float warmth = (color.r - color.b) / max(maxC, EPSILON);
+            float skinTone = isWarmTone * warmth * sat * (1.0 - sat);
+            vibranceAmt *= (1.0 - skinTone * SKIN_PROTECTION);
+            
+            color = mix(vec3(gray), color, 1.0 + vibranceAmt * VIBRANCE_BOOST);
+        }
+    }
+    
+    // Saturation
+    if (saturation != 0.0) {
+        float gray = dot(color, LUMA_WEIGHTS);
+        float satMix = saturation < 0.0
+            ? 1.0 + saturation                      // -100 → gray
+            : 1.0 + saturation * SATURATION_BOOST;  // +100 → 3x boost
+        color = mix(vec3(gray), color, satMix);
+    }
+    
+    fragColor = vec4(clamp(color, 0.0, 1.0), tex.a);
+}

blueprints/.glsl/Edge-Preserving_Blur_128.frag

@@ -0,0 +1,94 @@
+#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+uniform float u_float0;   // Blur radius (0–20, default ~5)
+uniform float u_float1;   // Edge threshold (0–100, default ~30)
+uniform int u_int0;       // Step size (0/1 = every pixel, 2+ = skip pixels)
+
+in vec2 v_texCoord;
+out vec4 fragColor;
+
+const int MAX_RADIUS = 20;
+const float EPSILON = 0.0001;
+
+// Perceptual luminance
+float getLuminance(vec3 rgb) {
+    return dot(rgb, vec3(0.299, 0.587, 0.114));
+}
+
+vec4 bilateralFilter(vec2 uv, vec2 texelSize, int radius,
+                     float sigmaSpatial, float sigmaColor)
+{
+    vec4 center = texture(u_image0, uv);
+    vec3 centerRGB = center.rgb;
+
+    float invSpatial2 = -0.5 / (sigmaSpatial * sigmaSpatial);
+    float invColor2   = -0.5 / (sigmaColor * sigmaColor + EPSILON);
+
+    vec3 sumRGB = vec3(0.0);
+    float sumWeight = 0.0;
+
+    int step = max(u_int0, 1);
+    float radius2 = float(radius * radius);
+
+    for (int dy = -MAX_RADIUS; dy <= MAX_RADIUS; dy++) {
+        if (dy < -radius || dy > radius) continue;
+        if (abs(dy) % step != 0) continue;
+
+        for (int dx = -MAX_RADIUS; dx <= MAX_RADIUS; dx++) {
+            if (dx < -radius || dx > radius) continue;
+            if (abs(dx) % step != 0) continue;
+
+            vec2 offset = vec2(float(dx), float(dy));
+            float dist2 = dot(offset, offset);
+            if (dist2 > radius2) continue;
+
+            vec3 sampleRGB = texture(u_image0, uv + offset * texelSize).rgb;
+
+            // Spatial Gaussian
+            float spatialWeight = exp(dist2 * invSpatial2);
+
+            // Perceptual color distance (weighted RGB)
+            vec3 diff = sampleRGB - centerRGB;
+            float colorDist = dot(diff * diff, vec3(0.299, 0.587, 0.114));
+            float colorWeight = exp(colorDist * invColor2);
+
+            float w = spatialWeight * colorWeight;
+            sumRGB += sampleRGB * w;
+            sumWeight += w;
+        }
+    }
+
+    vec3 resultRGB = sumRGB / max(sumWeight, EPSILON);
+    return vec4(resultRGB, center.a); // preserve center alpha
+}
+
+void main() {
+    vec2 texelSize = 1.0 / vec2(textureSize(u_image0, 0));
+
+    float radiusF = clamp(u_float0, 0.0, float(MAX_RADIUS));
+    int radius = int(radiusF + 0.5);
+
+    if (radius == 0) {
+        fragColor = texture(u_image0, v_texCoord);
+        return;
+    }
+
+    // Edge threshold → color sigma
+    // Squared curve for better low-end control
+    float t = clamp(u_float1, 0.0, 100.0) / 100.0;
+    t *= t;
+    float sigmaColor = mix(0.01, 0.5, t);
+
+    // Spatial sigma tied to radius
+    float sigmaSpatial = max(radiusF * 0.75, 0.5);
+
+    fragColor = bilateralFilter(
+        v_texCoord,
+        texelSize,
+        radius,
+        sigmaSpatial,
+        sigmaColor
+    );
+}

blueprints/.glsl/Film_Grain_15.frag

@@ -0,0 +1,124 @@
+#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+uniform vec2 u_resolution;
+uniform float u_float0; // grain amount      [0.0 – 1.0]   typical: 0.2–0.8
+uniform float u_float1; // grain size        [0.3 – 3.0]   lower = finer grain
+uniform float u_float2; // color amount      [0.0 – 1.0]   0 = monochrome, 1 = RGB grain
+uniform float u_float3; // luminance bias    [0.0 – 1.0]   0 = uniform, 1 = shadows only
+uniform int   u_int0;   // noise mode        [0 or 1]      0 = smooth, 1 = grainy
+
+in vec2 v_texCoord;
+layout(location = 0) out vec4 fragColor0;
+
+// High-quality integer hash (pcg-like)
+uint pcg(uint v) {
+    uint state = v * 747796405u + 2891336453u;
+    uint word = ((state >> ((state >> 28u) + 4u)) ^ state) * 277803737u;
+    return (word >> 22u) ^ word;
+}
+
+// 2D -> 1D hash input
+uint hash2d(uvec2 p) {
+    return pcg(p.x + pcg(p.y));
+}
+
+// Hash to float [0, 1]
+float hashf(uvec2 p) {
+    return float(hash2d(p)) / float(0xffffffffu);
+}
+
+// Hash to float with offset (for RGB channels)
+float hashf(uvec2 p, uint offset) {
+    return float(pcg(hash2d(p) + offset)) / float(0xffffffffu);
+}
+
+// Convert uniform [0,1] to roughly Gaussian distribution
+// Using simple approximation: average of multiple samples
+float toGaussian(uvec2 p) {
+    float sum = hashf(p, 0u) + hashf(p, 1u) + hashf(p, 2u) + hashf(p, 3u);
+    return (sum - 2.0) * 0.7;  // Centered, scaled
+}
+
+float toGaussian(uvec2 p, uint offset) {
+    float sum = hashf(p, offset) + hashf(p, offset + 1u) 
+              + hashf(p, offset + 2u) + hashf(p, offset + 3u);
+    return (sum - 2.0) * 0.7;
+}
+
+// Smooth noise with better interpolation
+float smoothNoise(vec2 p) {
+    vec2 i = floor(p);
+    vec2 f = fract(p);
+    
+    // Quintic interpolation (less banding than cubic)
+    f = f * f * f * (f * (f * 6.0 - 15.0) + 10.0);
+    
+    uvec2 ui = uvec2(i);
+    float a = toGaussian(ui);
+    float b = toGaussian(ui + uvec2(1u, 0u));
+    float c = toGaussian(ui + uvec2(0u, 1u));
+    float d = toGaussian(ui + uvec2(1u, 1u));
+    
+    return mix(mix(a, b, f.x), mix(c, d, f.x), f.y);
+}
+
+float smoothNoise(vec2 p, uint offset) {
+    vec2 i = floor(p);
+    vec2 f = fract(p);
+    
+    f = f * f * f * (f * (f * 6.0 - 15.0) + 10.0);
+    
+    uvec2 ui = uvec2(i);
+    float a = toGaussian(ui, offset);
+    float b = toGaussian(ui + uvec2(1u, 0u), offset);
+    float c = toGaussian(ui + uvec2(0u, 1u), offset);
+    float d = toGaussian(ui + uvec2(1u, 1u), offset);
+    
+    return mix(mix(a, b, f.x), mix(c, d, f.x), f.y);
+}
+
+void main() {
+    vec4 color = texture(u_image0, v_texCoord);
+    
+    // Luminance (Rec.709)
+    float luma = dot(color.rgb, vec3(0.2126, 0.7152, 0.0722));
+    
+    // Grain UV (resolution-independent)
+    vec2 grainUV = v_texCoord * u_resolution / max(u_float1, 0.01);
+    uvec2 grainPixel = uvec2(grainUV);
+    
+    float g;
+    vec3 grainRGB;
+    
+    if (u_int0 == 1) {
+        // Grainy mode: pure hash noise (no interpolation = no banding)
+        g = toGaussian(grainPixel);
+        grainRGB = vec3(
+            toGaussian(grainPixel, 100u),
+            toGaussian(grainPixel, 200u),
+            toGaussian(grainPixel, 300u)
+        );
+    } else {
+        // Smooth mode: interpolated with quintic curve
+        g = smoothNoise(grainUV);
+        grainRGB = vec3(
+            smoothNoise(grainUV, 100u),
+            smoothNoise(grainUV, 200u),
+            smoothNoise(grainUV, 300u)
+        );
+    }
+    
+    // Luminance weighting (less grain in highlights)
+    float lumWeight = mix(1.0, 1.0 - luma, clamp(u_float3, 0.0, 1.0));
+    
+    // Strength
+    float strength = u_float0 * 0.15;
+    
+    // Color vs monochrome grain
+    vec3 grainColor = mix(vec3(g), grainRGB, clamp(u_float2, 0.0, 1.0));
+    
+    color.rgb += grainColor * strength * lumWeight;
+    fragColor0 = vec4(clamp(color.rgb, 0.0, 1.0), color.a);
+}

blueprints/.glsl/Glow_30.frag

@@ -0,0 +1,133 @@
+#version 300 es
+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
+uniform float u_float1;  // Radius
+uniform float u_float2;  // Threshold
+
+in vec2 v_texCoord;
+out vec4 fragColor;
+
+const int BLEND_ADD      = 0;
+const int BLEND_SCREEN   = 1;
+const int BLEND_SOFT     = 2;
+const int BLEND_OVERLAY  = 3;
+const int BLEND_LIGHTEN  = 4;
+
+const float GOLDEN_ANGLE = 2.39996323;
+const int MAX_SAMPLES = 48;
+const vec3 LUMA = vec3(0.299, 0.587, 0.114);
+
+float hash(vec2 p) {
+    p = fract(p * vec2(123.34, 456.21));
+    p += dot(p, p + 45.32);
+    return fract(p.x * p.y);
+}
+
+vec3 hexToRgb(int h) {
+    return vec3(
+        float((h >> 16) & 255),
+        float((h >> 8) & 255),
+        float(h & 255)
+    ) * (1.0 / 255.0);
+}
+
+vec3 blend(vec3 base, vec3 glow, int mode) {
+    if (mode == BLEND_SCREEN) {
+        return 1.0 - (1.0 - base) * (1.0 - glow);
+    }
+    if (mode == BLEND_SOFT) {
+        return mix(
+            base - (1.0 - 2.0 * glow) * base * (1.0 - base),
+            base + (2.0 * glow - 1.0) * (sqrt(base) - base),
+            step(0.5, glow)
+        );
+    }
+    if (mode == BLEND_OVERLAY) {
+        return mix(
+            2.0 * base * glow,
+            1.0 - 2.0 * (1.0 - base) * (1.0 - glow),
+            step(0.5, base)
+        );
+    }
+    if (mode == BLEND_LIGHTEN) {
+        return max(base, glow);
+    }
+    return base + glow;
+}
+
+void main() {
+    vec4 original = texture(u_image0, v_texCoord);
+    
+    float intensity = u_float0 * 0.05;
+    float radius = u_float1 * u_float1 * 0.012;
+    
+    if (intensity < 0.001 || radius < 0.1) {
+        fragColor = original;
+        return;
+    }
+    
+    float threshold = 1.0 - u_float2 * 0.01;
+    float t0 = threshold - 0.15;
+    float t1 = threshold + 0.15;
+    
+    vec2 texelSize = 1.0 / u_resolution;
+    float radius2 = radius * radius;
+    
+    float sampleScale = clamp(radius * 0.75, 0.35, 1.0);
+    int samples = int(float(MAX_SAMPLES) * sampleScale);
+    
+    float noise = hash(gl_FragCoord.xy);
+    float angleOffset = noise * GOLDEN_ANGLE;
+    float radiusJitter = 0.85 + noise * 0.3;
+    
+    float ca = cos(GOLDEN_ANGLE);
+    float sa = sin(GOLDEN_ANGLE);
+    vec2 dir = vec2(cos(angleOffset), sin(angleOffset));
+    
+    vec3 glow = vec3(0.0);
+    float totalWeight = 0.0;
+    
+    // Center tap
+    float centerMask = smoothstep(t0, t1, dot(original.rgb, LUMA));
+    glow += original.rgb * centerMask * 2.0;
+    totalWeight += 2.0;
+    
+    for (int i = 1; i < MAX_SAMPLES; i++) {
+        if (i >= samples) break;
+        
+        float fi = float(i);
+        float dist = sqrt(fi / float(samples)) * radius * radiusJitter;
+        
+        vec2 offset = dir * dist * texelSize;
+        vec3 c = texture(u_image0, v_texCoord + offset).rgb;
+        float mask = smoothstep(t0, t1, dot(c, LUMA));
+        
+        float w = 1.0 - (dist * dist) / (radius2 * 1.5);
+        w = max(w, 0.0);
+        w *= w;
+        
+        glow += c * mask * w;
+        totalWeight += w;
+        
+        dir = vec2(
+            dir.x * ca - dir.y * sa,
+            dir.x * sa + dir.y * ca
+        );
+    }
+    
+    glow *= intensity / max(totalWeight, 0.001);
+    
+    if (u_int1 > 0) {
+        glow *= hexToRgb(u_int1);
+    }
+    
+    vec3 result = blend(original.rgb, glow, u_int0);
+    result += (noise - 0.5) * (1.0 / 255.0);
+    
+    fragColor = vec4(clamp(result, 0.0, 1.0), original.a);
+}

blueprints/.glsl/Hue_and_Saturation_1.frag

@@ -0,0 +1,222 @@
+#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+uniform int u_int0;      // Mode: 0=Master, 1=Reds, 2=Yellows, 3=Greens, 4=Cyans, 5=Blues, 6=Magentas, 7=Colorize
+uniform int u_int1;      // Color Space: 0=HSL, 1=HSB/HSV
+uniform float u_float0;  // Hue (-180 to 180)
+uniform float u_float1;  // Saturation (-100 to 100)
+uniform float u_float2;  // Lightness/Brightness (-100 to 100)
+uniform float u_float3;  // Overlap (0 to 100) - feathering between adjacent color ranges
+
+in vec2 v_texCoord;
+out vec4 fragColor;
+
+// Color range modes
+const int MODE_MASTER   = 0;
+const int MODE_RED      = 1;
+const int MODE_YELLOW   = 2;
+const int MODE_GREEN    = 3;
+const int MODE_CYAN     = 4;
+const int MODE_BLUE     = 5;
+const int MODE_MAGENTA  = 6;
+const int MODE_COLORIZE = 7;
+
+// Color space modes
+const int COLORSPACE_HSL = 0;
+const int COLORSPACE_HSB = 1;
+
+const float EPSILON = 0.0001;
+
+//=============================================================================
+// RGB <-> HSL Conversions
+//=============================================================================
+
+vec3 rgb2hsl(vec3 c) {
+    float maxC = max(max(c.r, c.g), c.b);
+    float minC = min(min(c.r, c.g), c.b);
+    float delta = maxC - minC;
+
+    float h = 0.0;
+    float s = 0.0;
+    float l = (maxC + minC) * 0.5;
+
+    if (delta > EPSILON) {
+        s = l < 0.5
+            ? delta / (maxC + minC)
+            : delta / (2.0 - maxC - minC);
+
+        if (maxC == c.r) {
+            h = (c.g - c.b) / delta + (c.g < c.b ? 6.0 : 0.0);
+        } else if (maxC == c.g) {
+            h = (c.b - c.r) / delta + 2.0;
+        } else {
+            h = (c.r - c.g) / delta + 4.0;
+        }
+        h /= 6.0;
+    }
+
+    return vec3(h, s, l);
+}
+
+float hue2rgb(float p, float q, float t) {
+    t = fract(t);
+    if (t < 1.0/6.0) return p + (q - p) * 6.0 * t;
+    if (t < 0.5)       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) {
+    if (hsl.y < EPSILON) return vec3(hsl.z);
+
+    float q = hsl.z < 0.5
+        ? hsl.z * (1.0 + hsl.y)
+        : hsl.z + hsl.y - hsl.z * hsl.y;
+    float p = 2.0 * hsl.z - q;
+
+    return vec3(
+        hue2rgb(p, q, hsl.x + 1.0/3.0),
+        hue2rgb(p, q, hsl.x),
+        hue2rgb(p, q, hsl.x - 1.0/3.0)
+    );
+}
+
+vec3 rgb2hsb(vec3 c) {
+    float maxC = max(max(c.r, c.g), c.b);
+    float minC = min(min(c.r, c.g), c.b);
+    float delta = maxC - minC;
+
+    float h = 0.0;
+    float s = (maxC > EPSILON) ? delta / maxC : 0.0;
+    float b = maxC;
+
+    if (delta > EPSILON) {
+        if (maxC == c.r) {
+            h = (c.g - c.b) / delta + (c.g < c.b ? 6.0 : 0.0);
+        } else if (maxC == c.g) {
+            h = (c.b - c.r) / delta + 2.0;
+        } else {
+            h = (c.r - c.g) / delta + 4.0;
+        }
+        h /= 6.0;
+    }
+
+    return vec3(h, s, b);
+}
+
+vec3 hsb2rgb(vec3 hsb) {
+    vec3 rgb = clamp(abs(mod(hsb.x * 6.0 + vec3(0.0, 4.0, 2.0), 6.0) - 3.0) - 1.0, 0.0, 1.0);
+    return hsb.z * mix(vec3(1.0), rgb, hsb.y);
+}
+
+//=============================================================================
+// Color Range Weight Calculation
+//=============================================================================
+
+float hueDistance(float a, float b) {
+    float d = abs(a - b);
+    return min(d, 1.0 - d);
+}
+
+float getHueWeight(float hue, float center, float overlap) {
+    float baseWidth = 1.0 / 6.0;
+    float feather = baseWidth * overlap;
+
+    float d = hueDistance(hue, center);
+
+    float inner = baseWidth * 0.5;
+    float outer = inner + feather;
+
+    return 1.0 - smoothstep(inner, outer, d);
+}
+
+float getModeWeight(float hue, int mode, float overlap) {
+    if (mode == MODE_MASTER || mode == MODE_COLORIZE) return 1.0;
+
+    if (mode == MODE_RED) {
+        return max(
+            getHueWeight(hue, 0.0, overlap),
+            getHueWeight(hue, 1.0, overlap)
+        );
+    }
+
+    float center = float(mode - 1) / 6.0;
+    return getHueWeight(hue, center, overlap);
+}
+
+//=============================================================================
+// Adjustment Functions
+//=============================================================================
+
+float adjustLightness(float l, float amount) {
+    return amount > 0.0
+        ? l + (1.0 - l) * amount
+        : l + l * amount;
+}
+
+float adjustBrightness(float b, float amount) {
+    return clamp(b + amount, 0.0, 1.0);
+}
+
+float adjustSaturation(float s, float amount) {
+    return amount > 0.0
+        ? s + (1.0 - s) * amount
+        : s + s * amount;
+}
+
+vec3 colorize(vec3 rgb, float hue, float sat, float light) {
+    float lum = dot(rgb, vec3(0.299, 0.587, 0.114));
+    float l = adjustLightness(lum, light);
+
+    vec3 hsl = vec3(fract(hue), clamp(sat, 0.0, 1.0), clamp(l, 0.0, 1.0));
+    return hsl2rgb(hsl);
+}
+
+//=============================================================================
+// Main
+//=============================================================================
+
+void main() {
+    vec4 original = texture(u_image0, v_texCoord);
+
+    float hueShift   = u_float0 / 360.0;   // -180..180 -> -0.5..0.5
+    float satAmount  = u_float1 / 100.0;   // -100..100 -> -1..1
+    float lightAmount= u_float2 / 100.0;   // -100..100 -> -1..1
+    float overlap    = u_float3 / 100.0;   // 0..100 -> 0..1
+
+    vec3 result;
+
+    if (u_int0 == MODE_COLORIZE) {
+        result = colorize(original.rgb, hueShift, satAmount, lightAmount);
+        fragColor = vec4(result, original.a);
+        return;
+    }
+
+    vec3 hsx = (u_int1 == COLORSPACE_HSL)
+        ? rgb2hsl(original.rgb)
+        : rgb2hsb(original.rgb);
+
+    float weight = getModeWeight(hsx.x, u_int0, overlap);
+
+    if (u_int0 != MODE_MASTER && hsx.y < EPSILON) {
+        weight = 0.0;
+    }
+
+    if (weight > EPSILON) {
+        float h = fract(hsx.x + hueShift * weight);
+        float s = clamp(adjustSaturation(hsx.y, satAmount * weight), 0.0, 1.0);
+        float v = (u_int1 == COLORSPACE_HSL)
+            ? clamp(adjustLightness(hsx.z, lightAmount * weight), 0.0, 1.0)
+            : clamp(adjustBrightness(hsx.z, lightAmount * weight), 0.0, 1.0);
+
+        vec3 adjusted = vec3(h, s, v);
+        result = (u_int1 == COLORSPACE_HSL)
+            ? hsl2rgb(adjusted)
+            : hsb2rgb(adjusted);
+    } else {
+        result = original.rgb;
+    }
+
+    fragColor = vec4(result, original.a);
+}

blueprints/.glsl/Image_Blur_1.frag

@@ -0,0 +1,111 @@
+#version 300 es
+#pragma passes 2
+precision highp float;
+
+// Blur type constants
+const int BLUR_GAUSSIAN = 0;
+const int BLUR_BOX = 1;
+const int BLUR_RADIAL = 2;
+
+// Radial blur config
+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)
+
+in vec2 v_texCoord;
+layout(location = 0) out vec4 fragColor0;
+
+float gaussian(float x, float sigma) {
+    return exp(-(x * x) / (2.0 * sigma * sigma));
+}
+
+void main() {
+    vec2 texelSize = 1.0 / u_resolution;
+    float radius = max(u_float0, 0.0);
+
+    // Radial (angular) blur - single pass, doesn't use separable
+    if (u_int0 == BLUR_RADIAL) {
+        // Only execute on first pass
+        if (u_pass > 0) {
+            fragColor0 = texture(u_image0, v_texCoord);
+            return;
+        }
+
+        vec2 center = vec2(0.5);
+        vec2 dir = v_texCoord - center;
+        float dist = length(dir);
+
+        if (dist < 1e-4) {
+            fragColor0 = texture(u_image0, v_texCoord);
+            return;
+        }
+
+        vec4 sum = vec4(0.0);
+        float totalWeight = 0.0;
+        float angleStep = radius * RADIAL_STRENGTH;
+
+        dir /= dist;
+
+        float cosStep = cos(angleStep);
+        float sinStep = sin(angleStep);
+
+        float negAngle = -float(RADIAL_SAMPLES) * angleStep;
+        vec2 rotDir = vec2(
+            dir.x * cos(negAngle) - dir.y * sin(negAngle),
+            dir.x * sin(negAngle) + dir.y * cos(negAngle)
+        );
+
+        for (int i = -RADIAL_SAMPLES; i <= RADIAL_SAMPLES; i++) {
+            vec2 uv = center + rotDir * dist;
+            float w = 1.0 - abs(float(i)) / float(RADIAL_SAMPLES);
+            sum += texture(u_image0, uv) * w;
+            totalWeight += w;
+
+            rotDir = vec2(
+                rotDir.x * cosStep - rotDir.y * sinStep,
+                rotDir.x * sinStep + rotDir.y * cosStep
+            );
+        }
+
+        fragColor0 = sum / max(totalWeight, 0.001);
+        return;
+    }
+
+    // Separable Gaussian / Box blur
+    int samples = int(ceil(radius));
+
+    if (samples == 0) {
+        fragColor0 = texture(u_image0, v_texCoord);
+        return;
+    }
+
+    // Direction: pass 0 = horizontal, pass 1 = vertical
+    vec2 dir = (u_pass == 0) ? vec2(1.0, 0.0) : vec2(0.0, 1.0);
+
+    vec4 color = vec4(0.0);
+    float totalWeight = 0.0;
+    float sigma = radius / 2.0;
+
+    for (int i = -samples; i <= samples; i++) {
+        vec2 offset = dir * float(i) * texelSize;
+        vec4 sample_color = texture(u_image0, v_texCoord + offset);
+
+        float weight;
+        if (u_int0 == BLUR_GAUSSIAN) {
+            weight = gaussian(float(i), sigma);
+        } else {
+            // BLUR_BOX
+            weight = 1.0;
+        }
+
+        color += sample_color * weight;
+        totalWeight += weight;
+    }
+
+    fragColor0 = color / totalWeight;
+}

blueprints/.glsl/Image_Channels_23.frag

@@ -0,0 +1,19 @@
+#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+
+in vec2 v_texCoord;
+layout(location = 0) out vec4 fragColor0;
+layout(location = 1) out vec4 fragColor1;
+layout(location = 2) out vec4 fragColor2;
+layout(location = 3) out vec4 fragColor3;
+
+void main() {
+  vec4 color = texture(u_image0, v_texCoord);
+  // Output each channel as grayscale to separate render targets
+  fragColor0 = vec4(vec3(color.r), 1.0);  // Red channel
+  fragColor1 = vec4(vec3(color.g), 1.0);  // Green channel
+  fragColor2 = vec4(vec3(color.b), 1.0);  // Blue channel
+  fragColor3 = vec4(vec3(color.a), 1.0);  // Alpha channel
+}

blueprints/.glsl/Image_Levels_1.frag

@@ -0,0 +1,71 @@
+#version 300 es
+precision highp float;
+
+// Levels Adjustment
+// u_int0:   channel      (0=RGB, 1=R, 2=G, 3=B)         default: 0
+// u_float0: input black  (0-255)                        default: 0
+// u_float1: input white  (0-255)                        default: 255
+// u_float2: gamma        (0.01-9.99)                    default: 1.0
+// u_float3: output black (0-255)                        default: 0
+// u_float4: output white (0-255)                        default: 255
+
+uniform sampler2D u_image0;
+uniform int u_int0;
+uniform float u_float0;
+uniform float u_float1;
+uniform float u_float2;
+uniform float u_float3;
+uniform float u_float4;
+
+in vec2 v_texCoord;
+out vec4 fragColor;
+
+vec3 applyLevels(vec3 color, float inBlack, float inWhite, float gamma, float outBlack, float outWhite) {
+    float inRange = max(inWhite - inBlack, 0.0001);
+    vec3 result = clamp((color - inBlack) / inRange, 0.0, 1.0);
+    result = pow(result, vec3(1.0 / gamma));
+    result = mix(vec3(outBlack), vec3(outWhite), result);
+    return result;
+}
+
+float applySingleChannel(float value, float inBlack, float inWhite, float gamma, float outBlack, float outWhite) {
+    float inRange = max(inWhite - inBlack, 0.0001);
+    float result = clamp((value - inBlack) / inRange, 0.0, 1.0);
+    result = pow(result, 1.0 / gamma);
+    result = mix(outBlack, outWhite, result);
+    return result;
+}
+
+void main() {
+    vec4 texColor = texture(u_image0, v_texCoord);
+    vec3 color = texColor.rgb;
+    
+    float inBlack = u_float0 / 255.0;
+    float inWhite = u_float1 / 255.0;
+    float gamma = u_float2;
+    float outBlack = u_float3 / 255.0;
+    float outWhite = u_float4 / 255.0;
+    
+    vec3 result;
+    
+    if (u_int0 == 0) {
+        result = applyLevels(color, inBlack, inWhite, gamma, outBlack, outWhite);
+    }
+    else if (u_int0 == 1) {
+        result = color;
+        result.r = applySingleChannel(color.r, inBlack, inWhite, gamma, outBlack, outWhite);
+    }
+    else if (u_int0 == 2) {
+        result = color;
+        result.g = applySingleChannel(color.g, inBlack, inWhite, gamma, outBlack, outWhite);
+    }
+    else if (u_int0 == 3) {
+        result = color;
+        result.b = applySingleChannel(color.b, inBlack, inWhite, gamma, outBlack, outWhite);
+    }
+    else {
+        result = color;
+    }
+    
+    fragColor = vec4(result, texColor.a);
+}

blueprints/.glsl/README.md

@@ -0,0 +1,28 @@
+# GLSL Shader Sources
+
+This folder contains the GLSL fragment shaders extracted from blueprint JSON files for easier editing and version control.
+
+## File Naming Convention
+
+`{Blueprint_Name}_{node_id}.frag`
+
+- **Blueprint_Name**: The JSON filename with spaces/special chars replaced by underscores
+- **node_id**: The GLSLShader node ID within the subgraph
+
+## Usage
+
+```bash
+# Extract shaders from blueprint JSONs to this folder
+python update_blueprints.py extract
+
+# Patch edited shaders back into blueprint JSONs
+python update_blueprints.py patch
+```
+
+## Workflow
+
+1. Run `extract` to pull current shaders from JSONs
+2. Edit `.frag` files
+3. Run `patch` to update the blueprint JSONs
+4. Test
+5. Commit both `.frag` files and updated JSONs

blueprints/.glsl/Sharpen_23.frag

@@ -0,0 +1,28 @@
+#version 300 es
+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;
+    
+    // Sample center and neighbors
+    vec4 center = texture(u_image0, v_texCoord);
+    vec4 top    = texture(u_image0, v_texCoord + vec2( 0.0, -texel.y));
+    vec4 bottom = texture(u_image0, v_texCoord + vec2( 0.0,  texel.y));
+    vec4 left   = texture(u_image0, v_texCoord + vec2(-texel.x,  0.0));
+    vec4 right  = texture(u_image0, v_texCoord + vec2( texel.x,  0.0));
+    
+    // Edge enhancement (Laplacian)
+    vec4 edges = center * 4.0 - top - bottom - left - right;
+    
+    // Add edges back scaled by strength
+    vec4 sharpened = center + edges * u_float0;
+    
+    fragColor0 = vec4(clamp(sharpened.rgb, 0.0, 1.0), center.a);
+}

blueprints/.glsl/Unsharp_Mask_26.frag

@@ -0,0 +1,61 @@
+#version 300 es
+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
+
+in vec2 v_texCoord;
+layout(location = 0) out vec4 fragColor0;
+
+float gaussian(float x, float sigma) {
+    return exp(-(x * x) / (2.0 * sigma * sigma));
+}
+
+float getLuminance(vec3 color) {
+    return dot(color, vec3(0.2126, 0.7152, 0.0722));
+}
+
+void main() {
+    vec2 texel = 1.0 / u_resolution;
+    float radius = max(u_float1, 0.5);
+    float amount = u_float0;
+    float threshold = u_float2;
+
+    vec4 original = texture(u_image0, v_texCoord);
+
+    // Gaussian blur for the "unsharp" mask
+    int samples = int(ceil(radius));
+    float sigma = radius / 2.0;
+
+    vec4 blurred = vec4(0.0);
+    float totalWeight = 0.0;
+
+    for (int x = -samples; x <= samples; x++) {
+        for (int y = -samples; y <= samples; y++) {
+            vec2 offset = vec2(float(x), float(y)) * texel;
+            vec4 sample_color = texture(u_image0, v_texCoord + offset);
+
+            float dist = length(vec2(float(x), float(y)));
+            float weight = gaussian(dist, sigma);
+            blurred += sample_color * weight;
+            totalWeight += weight;
+        }
+    }
+    blurred /= totalWeight;
+
+    // Unsharp mask = original - blurred
+    vec3 mask = original.rgb - blurred.rgb;
+
+    // Luminance-based threshold with smooth falloff
+    float lumaDelta = abs(getLuminance(original.rgb) - getLuminance(blurred.rgb));
+    float thresholdScale = smoothstep(0.0, threshold, lumaDelta);
+    mask *= thresholdScale;
+
+    // Sharpen: original + mask * amount
+    vec3 sharpened = original.rgb + mask * amount;
+
+    fragColor0 = vec4(clamp(sharpened, 0.0, 1.0), original.a);
+}

blueprints/.glsl/update_blueprints.py

@@ -0,0 +1,159 @@
+#!/usr/bin/env python3
+"""
+Shader Blueprint Updater
+
+Syncs GLSL shader files between this folder and blueprint JSON files.
+
+File naming convention:
+    {Blueprint Name}_{node_id}.frag
+
+Usage:
+    python update_blueprints.py extract   # Extract shaders from JSONs to here
+    python update_blueprints.py patch     # Patch shaders back into JSONs
+    python update_blueprints.py           # Same as patch (default)
+"""
+
+import json
+import logging
+import sys
+import re
+from pathlib import Path
+
+logging.basicConfig(level=logging.INFO, format='%(message)s')
+logger = logging.getLogger(__name__)
+
+GLSL_DIR = Path(__file__).parent
+BLUEPRINTS_DIR = GLSL_DIR.parent
+
+
+def get_blueprint_files():
+    """Get all blueprint JSON files."""
+    return sorted(BLUEPRINTS_DIR.glob("*.json"))
+
+
+def sanitize_filename(name):
+    """Convert blueprint name to safe filename."""
+    return re.sub(r'[^\w\-]', '_', name)
+
+
+def extract_shaders():
+    """Extract all shaders from blueprint JSONs to this folder."""
+    extracted = 0
+    for json_path in get_blueprint_files():
+        blueprint_name = json_path.stem
+
+        try:
+            with open(json_path, 'r') as f:
+                data = json.load(f)
+        except (json.JSONDecodeError, IOError) as e:
+            logger.warning("Skipping %s: %s", json_path.name, e)
+            continue
+
+        # Find GLSLShader nodes in subgraphs
+        for subgraph in data.get('definitions', {}).get('subgraphs', []):
+            for node in subgraph.get('nodes', []):
+                if node.get('type') == 'GLSLShader':
+                    node_id = node.get('id')
+                    widgets = node.get('widgets_values', [])
+
+                    # Find shader code (first string that looks like GLSL)
+                    for widget in widgets:
+                        if isinstance(widget, str) and widget.startswith('#version'):
+                            safe_name = sanitize_filename(blueprint_name)
+                            frag_name = f"{safe_name}_{node_id}.frag"
+                            frag_path = GLSL_DIR / frag_name
+
+                            with open(frag_path, 'w') as f:
+                                f.write(widget)
+
+                            logger.info("  Extracted: %s", frag_name)
+                            extracted += 1
+                            break
+
+    logger.info("\nExtracted %d shader(s)", extracted)
+
+
+def patch_shaders():
+    """Patch shaders from this folder back into blueprint JSONs."""
+    # Build lookup: blueprint_name -> [(node_id, shader_code), ...]
+    shader_updates = {}
+
+    for frag_path in sorted(GLSL_DIR.glob("*.frag")):
+        # Parse filename: {blueprint_name}_{node_id}.frag
+        parts = frag_path.stem.rsplit('_', 1)
+        if len(parts) != 2:
+            logger.warning("Skipping %s: invalid filename format", frag_path.name)
+            continue
+
+        blueprint_name, node_id_str = parts
+
+        try:
+            node_id = int(node_id_str)
+        except ValueError:
+            logger.warning("Skipping %s: invalid node_id", frag_path.name)
+            continue
+
+        with open(frag_path, 'r') as f:
+            shader_code = f.read()
+
+        if blueprint_name not in shader_updates:
+            shader_updates[blueprint_name] = []
+        shader_updates[blueprint_name].append((node_id, shader_code))
+
+    # Apply updates to JSON files
+    patched = 0
+    for json_path in get_blueprint_files():
+        blueprint_name = sanitize_filename(json_path.stem)
+
+        if blueprint_name not in shader_updates:
+            continue
+
+        try:
+            with open(json_path, 'r') as f:
+                data = json.load(f)
+        except (json.JSONDecodeError, IOError) as e:
+            logger.error("Error reading %s: %s", json_path.name, e)
+            continue
+
+        modified = False
+        for node_id, shader_code in shader_updates[blueprint_name]:
+            # Find the node and update
+            for subgraph in data.get('definitions', {}).get('subgraphs', []):
+                for node in subgraph.get('nodes', []):
+                    if node.get('id') == node_id and node.get('type') == 'GLSLShader':
+                        widgets = node.get('widgets_values', [])
+                        if len(widgets) > 0 and widgets[0] != shader_code:
+                            widgets[0] = shader_code
+                            modified = True
+                            logger.info("  Patched: %s (node %d)", json_path.name, node_id)
+                            patched += 1
+
+        if modified:
+            with open(json_path, 'w') as f:
+                json.dump(data, f)
+
+    if patched == 0:
+        logger.info("No changes to apply.")
+    else:
+        logger.info("\nPatched %d shader(s)", patched)
+
+
+def main():
+    if len(sys.argv) < 2:
+        command = "patch"
+    else:
+        command = sys.argv[1].lower()
+
+    if command == "extract":
+        logger.info("Extracting shaders from blueprints...")
+        extract_shaders()
+    elif command in ("patch", "update", "apply"):
+        logger.info("Patching shaders into blueprints...")
+        patch_shaders()
+    else:
+        logger.info(__doc__)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

blueprints/Image Channels.json

@@ -0,0 +1 @@
+{"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"}]}}

blueprints/Prompt Enhance.json

@@ -0,0 +1 @@
+{"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": {}}

blueprints/Sharpen.json

@@ -0,0 +1 @@
+{"revision": 0, "last_node_id": 25, "last_link_id": 0, "nodes": [{"id": 25, "type": "621ba4e2-22a8-482d-a369-023753198b7b", "pos": [4610, -790], "size": [230, 58], "flags": {}, "order": 4, "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": []}], "title": "Sharpen", "properties": {"proxyWidgets": [["24", "value"]]}, "widgets_values": []}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "621ba4e2-22a8-482d-a369-023753198b7b", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 24, "lastLinkId": 36, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Sharpen", "inputNode": {"id": -10, "bounding": [4090, -825, 120, 60]}, "outputNode": {"id": -20, "bounding": [5150, -825, 120, 60]}, "inputs": [{"id": "37011fb7-14b7-4e0e-b1a0-6a02e8da1fd7", "name": "images.image0", "type": "IMAGE", "linkIds": [34], "localized_name": "images.image0", "label": "image", "pos": [4190, -805]}], "outputs": [{"id": "e9182b3f-635c-4cd4-a152-4b4be17ae4b9", "name": "IMAGE0", "type": "IMAGE", "linkIds": [35], "localized_name": "IMAGE0", "label": "IMAGE", "pos": [5170, -805]}], "widgets": [], "nodes": [{"id": 24, "type": "PrimitiveFloat", "pos": [4280, -1240], "size": [270, 58], "flags": {}, "order": 0, "mode": 0, "inputs": [{"label": "strength", "localized_name": "value", "name": "value", "type": "FLOAT", "widget": {"name": "value"}, "link": null}], "outputs": [{"localized_name": "FLOAT", "name": "FLOAT", "type": "FLOAT", "links": [36]}], "properties": {"Node name for S&R": "PrimitiveFloat", "min": 0, "max": 3, "precision": 2, "step": 0.05}, "widgets_values": [0.5]}, {"id": 23, "type": "GLSLShader", "pos": [4570, -1240], "size": [370, 192], "flags": {}, "order": 1, "mode": 0, "inputs": [{"label": "image0", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": 34}, {"label": "image1", "localized_name": "images.image1", "name": "images.image1", "shape": 7, "type": "IMAGE", "link": null}, {"label": "u_float0", "localized_name": "floats.u_float0", "name": "floats.u_float0", "shape": 7, "type": "FLOAT", "link": 36}, {"label": "u_float1", "localized_name": "floats.u_float1", "name": "floats.u_float1", "shape": 7, "type": "FLOAT", "link": null}, {"label": "u_int0", "localized_name": "ints.u_int0", "name": "ints.u_int0", "shape": 7, "type": "INT", "link": null}, {"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": [35]}, {"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 vec2 u_resolution;\nuniform float u_float0;  // strength [0.0 – 2.0] typical: 0.3–1.0\n\nin vec2 v_texCoord;\nlayout(location = 0) out vec4 fragColor0;\n\nvoid main() {\n    vec2 texel = 1.0 / u_resolution;\n    \n    // Sample center and neighbors\n    vec4 center = texture(u_image0, v_texCoord);\n    vec4 top    = texture(u_image0, v_texCoord + vec2( 0.0, -texel.y));\n    vec4 bottom = texture(u_image0, v_texCoord + vec2( 0.0,  texel.y));\n    vec4 left   = texture(u_image0, v_texCoord + vec2(-texel.x,  0.0));\n    vec4 right  = texture(u_image0, v_texCoord + vec2( texel.x,  0.0));\n    \n    // Edge enhancement (Laplacian)\n    vec4 edges = center * 4.0 - top - bottom - left - right;\n    \n    // Add edges back scaled by strength\n    vec4 sharpened = center + edges * u_float0;\n    \n    fragColor0 = vec4(clamp(sharpened.rgb, 0.0, 1.0), center.a);\n}", "from_input"]}], "groups": [], "links": [{"id": 36, "origin_id": 24, "origin_slot": 0, "target_id": 23, "target_slot": 2, "type": "FLOAT"}, {"id": 34, "origin_id": -10, "origin_slot": 0, "target_id": 23, "target_slot": 0, "type": "IMAGE"}, {"id": 35, "origin_id": 23, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "IMAGE"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Image Tools/Sharpen"}]}}

blueprints/Video Upscale(GAN x4).json

@@ -0,0 +1 @@
+{"revision": 0, "last_node_id": 13, "last_link_id": 0, "nodes": [{"id": 13, "type": "cf95b747-3e17-46cb-8097-cac60ff9b2e1", "pos": [1120, 330], "size": [240, 58], "flags": {}, "order": 3, "mode": 0, "inputs": [{"localized_name": "video", "name": "video", "type": "VIDEO", "link": null}, {"name": "model_name", "type": "COMBO", "widget": {"name": "model_name"}, "link": null}], "outputs": [{"localized_name": "VIDEO", "name": "VIDEO", "type": "VIDEO", "links": []}], "title": "Video Upscale(GAN x4)", "properties": {"proxyWidgets": [["-1", "model_name"]], "cnr_id": "comfy-core", "ver": "0.14.1"}, "widgets_values": ["RealESRGAN_x4plus.safetensors"]}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "cf95b747-3e17-46cb-8097-cac60ff9b2e1", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 13, "lastLinkId": 19, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Video Upscale(GAN x4)", "inputNode": {"id": -10, "bounding": [550, 460, 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/audio_encoders/audio_encoders.py

@@ -27,6 +27,7 @@ class AudioEncoderModel():
         self.model.eval()
         self.patcher = comfy.model_patcher.CoreModelPatcher(self.model, load_device=self.load_device, offload_device=offload_device)
         self.model_sample_rate = 16000
+        comfy.model_management.archive_model_dtypes(self.model)
 
     def load_sd(self, sd):
         return self.model.load_state_dict(sd, strict=False, assign=self.patcher.is_dynamic())

comfy/checkpoint_pickle.py

@@ -1,13 +0,0 @@
-import pickle
-
-load = pickle.load
-
-class Empty:
-    pass
-
-class Unpickler(pickle.Unpickler):
-    def find_class(self, module, name):
-        #TODO: safe unpickle
-        if module.startswith("pytorch_lightning"):
-            return Empty
-        return super().find_class(module, name)

comfy/cli_args.py

@@ -146,6 +146,7 @@ parser.add_argument("--reserve-vram", type=float, default=None, help="Set the am
 
 parser.add_argument("--async-offload", nargs='?', const=2, type=int, default=None, metavar="NUM_STREAMS", help="Use async weight offloading. An optional argument controls the amount of offload streams. Default is 2. Enabled by default on Nvidia.")
 parser.add_argument("--disable-async-offload", action="store_true", help="Disable async weight offloading.")
+parser.add_argument("--disable-dynamic-vram", action="store_true", help="Disable dynamic VRAM and use estimate based model loading.")
 
 parser.add_argument("--force-non-blocking", action="store_true", help="Force ComfyUI to use non-blocking operations for all applicable tensors. This may improve performance on some non-Nvidia systems but can cause issues with some workflows.")
 
@@ -159,7 +160,6 @@ class PerformanceFeature(enum.Enum):
     Fp8MatrixMultiplication = "fp8_matrix_mult"
     CublasOps = "cublas_ops"
     AutoTune = "autotune"
-    DynamicVRAM = "dynamic_vram"
 
 parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. This is used to test new features so using it might crash your comfyui. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: {}".format(" ".join(map(lambda c: c.value, PerformanceFeature))))
 
@@ -232,7 +232,7 @@ 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-assets-autoscan", action="store_true", help="Disable asset scanning on startup for database synchronization.")
+parser.add_argument("--enable-assets", action="store_true", help="Enable the assets system (API routes, database synchronization, and background scanning).")
 
 if comfy.options.args_parsing:
     args = parser.parse_args()
@@ -260,4 +260,4 @@ else:
     args.fast = set(args.fast)
 
 def enables_dynamic_vram():
-    return PerformanceFeature.DynamicVRAM in args.fast and not args.highvram and not args.gpu_only
+    return not args.disable_dynamic_vram and not args.highvram and not args.gpu_only and not args.novram and not args.cpu

comfy/comfy_types/node_typing.py

@@ -176,6 +176,8 @@ class InputTypeOptions(TypedDict):
     """COMBO type only. Specifies the configuration for a multi-select widget.
     Available after ComfyUI frontend v1.13.4
     https://github.com/Comfy-Org/ComfyUI_frontend/pull/2987"""
+    gradient_stops: NotRequired[list[list[float]]]
+    """Gradient color stops for gradientslider display mode. Each stop is [offset, r, g, b] (``FLOAT``)."""
 
 
 class HiddenInputTypeDict(TypedDict):

comfy/conds.py

@@ -4,6 +4,25 @@ import comfy.utils
 import logging
 
 
+def is_equal(x, y):
+    if torch.is_tensor(x) and torch.is_tensor(y):
+        return torch.equal(x, y)
+    elif isinstance(x, dict) and isinstance(y, dict):
+        if x.keys() != y.keys():
+            return False
+        return all(is_equal(x[k], y[k]) for k in x)
+    elif isinstance(x, (list, tuple)) and isinstance(y, (list, tuple)):
+        if type(x) is not type(y) or len(x) != len(y):
+            return False
+        return all(is_equal(a, b) for a, b in zip(x, y))
+    else:
+        try:
+            return x == y
+        except Exception:
+            logging.warning("comparison issue with COND")
+            return False
+
+
 class CONDRegular:
     def __init__(self, cond):
         self.cond = cond
@@ -84,7 +103,7 @@ class CONDConstant(CONDRegular):
         return self._copy_with(self.cond)
 
     def can_concat(self, other):
-        if self.cond != other.cond:
+        if not is_equal(self.cond, other.cond):
             return False
         return True
 

comfy/context_windows.py

@@ -214,7 +214,7 @@ class IndexListContextHandler(ContextHandlerABC):
         mask = torch.isclose(model_options["transformer_options"]["sample_sigmas"], timestep[0], rtol=0.0001)
         matches = torch.nonzero(mask)
         if torch.numel(matches) == 0:
-            raise Exception("No sample_sigmas matched current timestep; something went wrong.")
+            return  # substep from multi-step sampler: keep self._step from the last full step
         self._step = int(matches[0].item())
 
     def get_context_windows(self, model: BaseModel, x_in: torch.Tensor, model_options: dict[str]) -> list[IndexListContextWindow]:

comfy/latent_formats.py

@@ -776,3 +776,10 @@ class ChromaRadiance(LatentFormat):
 
     def process_out(self, latent):
         return latent
+
+
+class ZImagePixelSpace(ChromaRadiance):
+    """Pixel-space latent format for ZImage DCT variant.
+    No VAE encoding/decoding — the model operates directly on RGB pixels.
+    """
+    pass

comfy/ldm/anima/model.py

@@ -179,8 +179,8 @@ class LLMAdapter(nn.Module):
             if source_attention_mask.ndim == 2:
                 source_attention_mask = source_attention_mask.unsqueeze(1).unsqueeze(1)
 
-        x = self.in_proj(self.embed(target_input_ids))
         context = source_hidden_states
+        x = self.in_proj(self.embed(target_input_ids, out_dtype=context.dtype))
         position_ids = torch.arange(x.shape[1], device=x.device).unsqueeze(0)
         position_ids_context = torch.arange(context.shape[1], device=x.device).unsqueeze(0)
         position_embeddings = self.rotary_emb(x, position_ids)

comfy/ldm/chroma/model.py

@@ -152,6 +152,7 @@ class Chroma(nn.Module):
         transformer_options={},
         attn_mask: Tensor = None,
     ) -> Tensor:
+        transformer_options = transformer_options.copy()
         patches_replace = transformer_options.get("patches_replace", {})
 
         # running on sequences img
@@ -228,6 +229,7 @@ class Chroma(nn.Module):
 
         transformer_options["total_blocks"] = len(self.single_blocks)
         transformer_options["block_type"] = "single"
+        transformer_options["img_slice"] = [txt.shape[1], img.shape[1]]
         for i, block in enumerate(self.single_blocks):
             transformer_options["block_index"] = i
             if i not in self.skip_dit:

comfy/ldm/flux/layers.py

@@ -196,6 +196,9 @@ class DoubleStreamBlock(nn.Module):
         else:
             (img_mod1, img_mod2), (txt_mod1, txt_mod2) = vec
 
+        transformer_patches = transformer_options.get("patches", {})
+        extra_options = transformer_options.copy()
+
         # prepare image for attention
         img_modulated = self.img_norm1(img)
         img_modulated = apply_mod(img_modulated, (1 + img_mod1.scale), img_mod1.shift, modulation_dims_img)
@@ -224,6 +227,12 @@ class DoubleStreamBlock(nn.Module):
         attn = attention(q, k, v, pe=pe, mask=attn_mask, transformer_options=transformer_options)
         del q, k, v
 
+        if "attn1_output_patch" in transformer_patches:
+            extra_options["img_slice"] = [txt.shape[1], attn.shape[1]]
+            patch = transformer_patches["attn1_output_patch"]
+            for p in patch:
+                attn = p(attn, extra_options)
+
         txt_attn, img_attn = attn[:, : txt.shape[1]], attn[:, txt.shape[1]:]
 
         # calculate the img bloks
@@ -303,6 +312,9 @@ class SingleStreamBlock(nn.Module):
         else:
             mod = vec
 
+        transformer_patches = transformer_options.get("patches", {})
+        extra_options = transformer_options.copy()
+
         qkv, mlp = torch.split(self.linear1(apply_mod(self.pre_norm(x), (1 + mod.scale), mod.shift, modulation_dims)), [3 * self.hidden_size, self.mlp_hidden_dim_first], dim=-1)
 
         q, k, v = qkv.view(qkv.shape[0], qkv.shape[1], 3, self.num_heads, -1).permute(2, 0, 3, 1, 4)
@@ -312,6 +324,12 @@ class SingleStreamBlock(nn.Module):
         # compute attention
         attn = attention(q, k, v, pe=pe, mask=attn_mask, transformer_options=transformer_options)
         del q, k, v
+
+        if "attn1_output_patch" in transformer_patches:
+            patch = transformer_patches["attn1_output_patch"]
+            for p in patch:
+                attn = p(attn, extra_options)
+
         # compute activation in mlp stream, cat again and run second linear layer
         if self.yak_mlp:
             mlp = self.mlp_act(mlp[..., self.mlp_hidden_dim_first // 2:]) * mlp[..., :self.mlp_hidden_dim_first // 2]

comfy/ldm/flux/model.py

@@ -142,6 +142,7 @@ class Flux(nn.Module):
         attn_mask: Tensor = None,
     ) -> Tensor:
 
+        transformer_options = transformer_options.copy()
         patches = transformer_options.get("patches", {})
         patches_replace = transformer_options.get("patches_replace", {})
         if img.ndim != 3 or txt.ndim != 3:
@@ -231,6 +232,7 @@ class Flux(nn.Module):
 
         transformer_options["total_blocks"] = len(self.single_blocks)
         transformer_options["block_type"] = "single"
+        transformer_options["img_slice"] = [txt.shape[1], img.shape[1]]
         for i, block in enumerate(self.single_blocks):
             transformer_options["block_index"] = i
             if ("single_block", i) in blocks_replace:

comfy/ldm/hunyuan_video/model.py

@@ -304,6 +304,7 @@ class HunyuanVideo(nn.Module):
         control=None,
         transformer_options={},
     ) -> Tensor:
+        transformer_options = transformer_options.copy()
         patches_replace = transformer_options.get("patches_replace", {})
 
         initial_shape = list(img.shape)
@@ -416,6 +417,7 @@ class HunyuanVideo(nn.Module):
 
         transformer_options["total_blocks"] = len(self.single_blocks)
         transformer_options["block_type"] = "single"
+        transformer_options["img_slice"] = [txt.shape[1], img.shape[1]]
         for i, block in enumerate(self.single_blocks):
             transformer_options["block_index"] = i
             if ("single_block", i) in blocks_replace:

comfy/ldm/lightricks/av_model.py

@@ -2,13 +2,19 @@ from typing import Tuple
 import torch
 import torch.nn as nn
 from comfy.ldm.lightricks.model import (
+    ADALN_BASE_PARAMS_COUNT,
+    ADALN_CROSS_ATTN_PARAMS_COUNT,
     CrossAttention,
     FeedForward,
     AdaLayerNormSingle,
     PixArtAlphaTextProjection,
+    NormSingleLinearTextProjection,
     LTXVModel,
+    apply_cross_attention_adaln,
+    compute_prompt_timestep,
 )
 from comfy.ldm.lightricks.symmetric_patchifier import AudioPatchifier
+from comfy.ldm.lightricks.embeddings_connector import Embeddings1DConnector
 import comfy.ldm.common_dit
 
 class CompressedTimestep:
@@ -86,6 +92,8 @@ class BasicAVTransformerBlock(nn.Module):
         v_context_dim=None,
         a_context_dim=None,
         attn_precision=None,
+        apply_gated_attention=False,
+        cross_attention_adaln=False,
         dtype=None,
         device=None,
         operations=None,
@@ -93,6 +101,7 @@ class BasicAVTransformerBlock(nn.Module):
         super().__init__()
 
         self.attn_precision = attn_precision
+        self.cross_attention_adaln = cross_attention_adaln
 
         self.attn1 = CrossAttention(
             query_dim=v_dim,
@@ -100,6 +109,7 @@ class BasicAVTransformerBlock(nn.Module):
             dim_head=vd_head,
             context_dim=None,
             attn_precision=self.attn_precision,
+            apply_gated_attention=apply_gated_attention,
             dtype=dtype,
             device=device,
             operations=operations,
@@ -110,6 +120,7 @@ class BasicAVTransformerBlock(nn.Module):
             dim_head=ad_head,
             context_dim=None,
             attn_precision=self.attn_precision,
+            apply_gated_attention=apply_gated_attention,
             dtype=dtype,
             device=device,
             operations=operations,
@@ -121,6 +132,7 @@ class BasicAVTransformerBlock(nn.Module):
             heads=v_heads,
             dim_head=vd_head,
             attn_precision=self.attn_precision,
+            apply_gated_attention=apply_gated_attention,
             dtype=dtype,
             device=device,
             operations=operations,
@@ -131,6 +143,7 @@ class BasicAVTransformerBlock(nn.Module):
             heads=a_heads,
             dim_head=ad_head,
             attn_precision=self.attn_precision,
+            apply_gated_attention=apply_gated_attention,
             dtype=dtype,
             device=device,
             operations=operations,
@@ -143,6 +156,7 @@ class BasicAVTransformerBlock(nn.Module):
             heads=a_heads,
             dim_head=ad_head,
             attn_precision=self.attn_precision,
+            apply_gated_attention=apply_gated_attention,
             dtype=dtype,
             device=device,
             operations=operations,
@@ -155,6 +169,7 @@ class BasicAVTransformerBlock(nn.Module):
             heads=a_heads,
             dim_head=ad_head,
             attn_precision=self.attn_precision,
+            apply_gated_attention=apply_gated_attention,
             dtype=dtype,
             device=device,
             operations=operations,
@@ -167,11 +182,16 @@ class BasicAVTransformerBlock(nn.Module):
             a_dim, dim_out=a_dim, glu=True, dtype=dtype, device=device, operations=operations
         )
 
-        self.scale_shift_table = nn.Parameter(torch.empty(6, v_dim, device=device, dtype=dtype))
+        num_ada_params = ADALN_CROSS_ATTN_PARAMS_COUNT if cross_attention_adaln else ADALN_BASE_PARAMS_COUNT
+        self.scale_shift_table = nn.Parameter(torch.empty(num_ada_params, v_dim, device=device, dtype=dtype))
         self.audio_scale_shift_table = nn.Parameter(
-            torch.empty(6, a_dim, device=device, dtype=dtype)
+            torch.empty(num_ada_params, a_dim, device=device, dtype=dtype)
         )
 
+        if cross_attention_adaln:
+            self.prompt_scale_shift_table = nn.Parameter(torch.empty(2, v_dim, device=device, dtype=dtype))
+            self.audio_prompt_scale_shift_table = nn.Parameter(torch.empty(2, a_dim, device=device, dtype=dtype))
+
         self.scale_shift_table_a2v_ca_audio = nn.Parameter(
             torch.empty(5, a_dim, device=device, dtype=dtype)
         )
@@ -214,10 +234,30 @@ class BasicAVTransformerBlock(nn.Module):
 
         return (*scale_shift_ada_values, *gate_ada_values)
 
+    def _apply_text_cross_attention(
+        self, x, context, attn, scale_shift_table, prompt_scale_shift_table,
+        timestep, prompt_timestep, attention_mask, transformer_options,
+    ):
+        """Apply text cross-attention, with optional ADaLN modulation."""
+        if self.cross_attention_adaln:
+            shift_q, scale_q, gate = self.get_ada_values(
+                scale_shift_table, x.shape[0], timestep, slice(6, 9)
+            )
+            return apply_cross_attention_adaln(
+                x, context, attn, shift_q, scale_q, gate,
+                prompt_scale_shift_table, prompt_timestep,
+                attention_mask, transformer_options,
+            )
+        return attn(
+            comfy.ldm.common_dit.rms_norm(x), context=context,
+            mask=attention_mask, transformer_options=transformer_options,
+        )
+
     def forward(
         self, x: Tuple[torch.Tensor, torch.Tensor], v_context=None, a_context=None, attention_mask=None, v_timestep=None, a_timestep=None,
         v_pe=None, a_pe=None, v_cross_pe=None, a_cross_pe=None, v_cross_scale_shift_timestep=None, a_cross_scale_shift_timestep=None,
-        v_cross_gate_timestep=None, a_cross_gate_timestep=None, transformer_options=None,
+        v_cross_gate_timestep=None, a_cross_gate_timestep=None, transformer_options=None, self_attention_mask=None,
+        v_prompt_timestep=None, a_prompt_timestep=None,
     ) -> Tuple[torch.Tensor, torch.Tensor]:
         run_vx = transformer_options.get("run_vx", True)
         run_ax = transformer_options.get("run_ax", True)
@@ -233,13 +273,17 @@ class BasicAVTransformerBlock(nn.Module):
             vshift_msa, vscale_msa = (self.get_ada_values(self.scale_shift_table, vx.shape[0], v_timestep, slice(0, 2)))
             norm_vx = comfy.ldm.common_dit.rms_norm(vx) * (1 + vscale_msa) + vshift_msa
             del vshift_msa, vscale_msa
-            attn1_out = self.attn1(norm_vx, pe=v_pe, transformer_options=transformer_options)
+            attn1_out = self.attn1(norm_vx, pe=v_pe, mask=self_attention_mask, transformer_options=transformer_options)
             del norm_vx
             # video cross-attention
             vgate_msa = self.get_ada_values(self.scale_shift_table, vx.shape[0], v_timestep, slice(2, 3))[0]
             vx.addcmul_(attn1_out, vgate_msa)
             del vgate_msa, attn1_out
-            vx.add_(self.attn2(comfy.ldm.common_dit.rms_norm(vx), context=v_context, mask=attention_mask, transformer_options=transformer_options))
+            vx.add_(self._apply_text_cross_attention(
+                vx, v_context, self.attn2, self.scale_shift_table,
+                getattr(self, 'prompt_scale_shift_table', None),
+                v_timestep, v_prompt_timestep, attention_mask, transformer_options,)
+            )
 
         # audio
         if run_ax:
@@ -253,7 +297,11 @@ class BasicAVTransformerBlock(nn.Module):
             agate_msa = self.get_ada_values(self.audio_scale_shift_table, ax.shape[0], a_timestep, slice(2, 3))[0]
             ax.addcmul_(attn1_out, agate_msa)
             del agate_msa, attn1_out
-            ax.add_(self.audio_attn2(comfy.ldm.common_dit.rms_norm(ax), context=a_context, mask=attention_mask, transformer_options=transformer_options))
+            ax.add_(self._apply_text_cross_attention(
+                ax, a_context, self.audio_attn2, self.audio_scale_shift_table,
+                getattr(self, 'audio_prompt_scale_shift_table', None),
+                a_timestep, a_prompt_timestep, attention_mask, transformer_options,)
+            )
 
         # video - audio cross attention.
         if run_a2v or run_v2a:
@@ -350,6 +398,9 @@ class LTXAVModel(LTXVModel):
         use_middle_indices_grid=False,
         timestep_scale_multiplier=1000.0,
         av_ca_timestep_scale_multiplier=1.0,
+        apply_gated_attention=False,
+        caption_proj_before_connector=False,
+        cross_attention_adaln=False,
         dtype=None,
         device=None,
         operations=None,
@@ -361,6 +412,7 @@ class LTXAVModel(LTXVModel):
         self.audio_attention_head_dim = audio_attention_head_dim
         self.audio_num_attention_heads = audio_num_attention_heads
         self.audio_positional_embedding_max_pos = audio_positional_embedding_max_pos
+        self.apply_gated_attention = apply_gated_attention
 
         # Calculate audio dimensions
         self.audio_inner_dim = audio_num_attention_heads * audio_attention_head_dim
@@ -385,6 +437,8 @@ class LTXAVModel(LTXVModel):
             vae_scale_factors=vae_scale_factors,
             use_middle_indices_grid=use_middle_indices_grid,
             timestep_scale_multiplier=timestep_scale_multiplier,
+            caption_proj_before_connector=caption_proj_before_connector,
+            cross_attention_adaln=cross_attention_adaln,
             dtype=dtype,
             device=device,
             operations=operations,
@@ -399,14 +453,28 @@ class LTXAVModel(LTXVModel):
         )
 
         # Audio-specific AdaLN
+        audio_embedding_coefficient = ADALN_CROSS_ATTN_PARAMS_COUNT if self.cross_attention_adaln else ADALN_BASE_PARAMS_COUNT
         self.audio_adaln_single = AdaLayerNormSingle(
             self.audio_inner_dim,
+            embedding_coefficient=audio_embedding_coefficient,
             use_additional_conditions=False,
             dtype=dtype,
             device=device,
             operations=self.operations,
         )
 
+        if self.cross_attention_adaln:
+            self.audio_prompt_adaln_single = AdaLayerNormSingle(
+                self.audio_inner_dim,
+                embedding_coefficient=2,
+                use_additional_conditions=False,
+                dtype=dtype,
+                device=device,
+                operations=self.operations,
+            )
+        else:
+            self.audio_prompt_adaln_single = None
+
         num_scale_shift_values = 4
         self.av_ca_video_scale_shift_adaln_single = AdaLayerNormSingle(
             self.inner_dim,
@@ -442,14 +510,75 @@ class LTXAVModel(LTXVModel):
         )
 
         # Audio caption projection
-        self.audio_caption_projection = PixArtAlphaTextProjection(
-            in_features=self.caption_channels,
-            hidden_size=self.audio_inner_dim,
+        if self.caption_proj_before_connector:
+            if self.caption_projection_first_linear:
+                self.audio_caption_projection = NormSingleLinearTextProjection(
+                    in_features=self.caption_channels,
+                    hidden_size=self.audio_inner_dim,
+                    dtype=dtype,
+                    device=device,
+                    operations=self.operations,
+                )
+            else:
+                self.audio_caption_projection = lambda a: a
+        else:
+            self.audio_caption_projection = PixArtAlphaTextProjection(
+                in_features=self.caption_channels,
+                hidden_size=self.audio_inner_dim,
+                dtype=dtype,
+                device=device,
+                operations=self.operations,
+            )
+
+        connector_split_rope = kwargs.get("rope_type", "split") == "split"
+        connector_gated_attention = kwargs.get("connector_apply_gated_attention", False)
+        attention_head_dim = kwargs.get("connector_attention_head_dim", 128)
+        num_attention_heads = kwargs.get("connector_num_attention_heads", 30)
+        num_layers = kwargs.get("connector_num_layers", 2)
+
+        self.audio_embeddings_connector = Embeddings1DConnector(
+            attention_head_dim=kwargs.get("audio_connector_attention_head_dim", attention_head_dim),
+            num_attention_heads=kwargs.get("audio_connector_num_attention_heads", num_attention_heads),
+            num_layers=num_layers,
+            split_rope=connector_split_rope,
+            double_precision_rope=True,
+            apply_gated_attention=connector_gated_attention,
             dtype=dtype,
             device=device,
             operations=self.operations,
         )
 
+        self.video_embeddings_connector = Embeddings1DConnector(
+            attention_head_dim=attention_head_dim,
+            num_attention_heads=num_attention_heads,
+            num_layers=num_layers,
+            split_rope=connector_split_rope,
+            double_precision_rope=True,
+            apply_gated_attention=connector_gated_attention,
+            dtype=dtype,
+            device=device,
+            operations=self.operations,
+        )
+
+    def preprocess_text_embeds(self, context, unprocessed=False):
+        # LTXv2 fully processed context has dimension of self.caption_channels * 2
+        # LTXv2.3 fully processed context has dimension of self.cross_attention_dim + self.audio_cross_attention_dim
+        if not unprocessed:
+            if context.shape[-1] in (self.cross_attention_dim + self.audio_cross_attention_dim, self.caption_channels * 2):
+                return context
+        if context.shape[-1] == self.cross_attention_dim + self.audio_cross_attention_dim:
+            context_vid = context[:, :, :self.cross_attention_dim]
+            context_audio = context[:, :, self.cross_attention_dim:]
+        else:
+            context_vid = context
+            context_audio = context
+        if self.caption_proj_before_connector:
+            context_vid = self.caption_projection(context_vid)
+            context_audio = self.audio_caption_projection(context_audio)
+        out_vid = self.video_embeddings_connector(context_vid)[0]
+        out_audio = self.audio_embeddings_connector(context_audio)[0]
+        return torch.concat((out_vid, out_audio), dim=-1)
+
     def _init_transformer_blocks(self, device, dtype, **kwargs):
         """Initialize transformer blocks for LTXAV."""
         self.transformer_blocks = nn.ModuleList(
@@ -463,6 +592,8 @@ class LTXAVModel(LTXVModel):
                     ad_head=self.audio_attention_head_dim,
                     v_context_dim=self.cross_attention_dim,
                     a_context_dim=self.audio_cross_attention_dim,
+                    apply_gated_attention=self.apply_gated_attention,
+                    cross_attention_adaln=self.cross_attention_adaln,
                     dtype=dtype,
                     device=device,
                     operations=self.operations,
@@ -584,6 +715,10 @@ class LTXAVModel(LTXVModel):
         v_timestep = CompressedTimestep(v_timestep.view(batch_size, -1, v_timestep.shape[-1]), v_patches_per_frame)
         v_embedded_timestep = CompressedTimestep(v_embedded_timestep.view(batch_size, -1, v_embedded_timestep.shape[-1]), v_patches_per_frame)
 
+        v_prompt_timestep = compute_prompt_timestep(
+            self.prompt_adaln_single, timestep_scaled, batch_size, hidden_dtype
+        )
+
         # Prepare audio timestep
         a_timestep = kwargs.get("a_timestep")
         if a_timestep is not None:
@@ -594,25 +729,25 @@ class LTXAVModel(LTXVModel):
 
             # Cross-attention timesteps - compress these too
             av_ca_audio_scale_shift_timestep, _ = self.av_ca_audio_scale_shift_adaln_single(
-                a_timestep_flat,
+                timestep.max().expand_as(a_timestep_flat),
                 {"resolution": None, "aspect_ratio": None},
                 batch_size=batch_size,
                 hidden_dtype=hidden_dtype,
             )
             av_ca_video_scale_shift_timestep, _ = self.av_ca_video_scale_shift_adaln_single(
-                timestep_flat,
+                a_timestep.max().expand_as(timestep_flat),
                 {"resolution": None, "aspect_ratio": None},
                 batch_size=batch_size,
                 hidden_dtype=hidden_dtype,
             )
             av_ca_a2v_gate_noise_timestep, _ = self.av_ca_a2v_gate_adaln_single(
-                timestep_flat * av_ca_factor,
+                a_timestep.max().expand_as(timestep_flat) * av_ca_factor,
                 {"resolution": None, "aspect_ratio": None},
                 batch_size=batch_size,
                 hidden_dtype=hidden_dtype,
             )
             av_ca_v2a_gate_noise_timestep, _ = self.av_ca_v2a_gate_adaln_single(
-                a_timestep_flat * av_ca_factor,
+                timestep.max().expand_as(a_timestep_flat) * av_ca_factor,
                 {"resolution": None, "aspect_ratio": None},
                 batch_size=batch_size,
                 hidden_dtype=hidden_dtype,
@@ -636,29 +771,40 @@ class LTXAVModel(LTXVModel):
             # Audio timesteps
             a_timestep = a_timestep.view(batch_size, -1, a_timestep.shape[-1])
             a_embedded_timestep = a_embedded_timestep.view(batch_size, -1, a_embedded_timestep.shape[-1])
+
+            a_prompt_timestep = compute_prompt_timestep(
+                self.audio_prompt_adaln_single, a_timestep_scaled, batch_size, hidden_dtype
+            )
         else:
             a_timestep = timestep_scaled
             a_embedded_timestep = kwargs.get("embedded_timestep")
             cross_av_timestep_ss = []
+            a_prompt_timestep = None
 
-        return [v_timestep, a_timestep, cross_av_timestep_ss], [
+        return [v_timestep, a_timestep, cross_av_timestep_ss, v_prompt_timestep, a_prompt_timestep], [
             v_embedded_timestep,
             a_embedded_timestep,
-        ]
+        ], None
 
     def _prepare_context(self, context, batch_size, x, attention_mask=None):
         vx = x[0]
         ax = x[1]
+        video_dim = vx.shape[-1]
+        audio_dim = ax.shape[-1]
+
+        v_context_dim = self.caption_channels if self.caption_proj_before_connector is False else video_dim
+        a_context_dim = self.caption_channels if self.caption_proj_before_connector is False else audio_dim
+
         v_context, a_context = torch.split(
-            context, int(context.shape[-1] / 2), len(context.shape) - 1
+            context, [v_context_dim, a_context_dim], len(context.shape) - 1
         )
 
         v_context, attention_mask = super()._prepare_context(
             v_context, batch_size, vx, attention_mask
         )
-        if self.audio_caption_projection is not None:
+        if self.caption_proj_before_connector is False:
             a_context = self.audio_caption_projection(a_context)
-            a_context = a_context.view(batch_size, -1, ax.shape[-1])
+        a_context = a_context.view(batch_size, -1, audio_dim)
 
         return [v_context, a_context], attention_mask
 
@@ -702,7 +848,7 @@ class LTXAVModel(LTXVModel):
         return [(v_pe, av_cross_video_freq_cis), (a_pe, av_cross_audio_freq_cis)]
 
     def _process_transformer_blocks(
-        self, x, context, attention_mask, timestep, pe, transformer_options={}, **kwargs
+        self, x, context, attention_mask, timestep, pe, transformer_options={}, self_attention_mask=None, **kwargs
     ):
         vx = x[0]
         ax = x[1]
@@ -720,6 +866,9 @@ class LTXAVModel(LTXVModel):
             av_ca_v2a_gate_noise_timestep,
         ) = timestep[2]
 
+        v_prompt_timestep = timestep[3]
+        a_prompt_timestep = timestep[4]
+
         """Process transformer blocks for LTXAV."""
         patches_replace = transformer_options.get("patches_replace", {})
         blocks_replace = patches_replace.get("dit", {})
@@ -746,6 +895,9 @@ class LTXAVModel(LTXVModel):
                         v_cross_gate_timestep=args["v_cross_gate_timestep"],
                         a_cross_gate_timestep=args["a_cross_gate_timestep"],
                         transformer_options=args["transformer_options"],
+                        self_attention_mask=args.get("self_attention_mask"),
+                        v_prompt_timestep=args.get("v_prompt_timestep"),
+                        a_prompt_timestep=args.get("a_prompt_timestep"),
                     )
                     return out
 
@@ -766,6 +918,9 @@ class LTXAVModel(LTXVModel):
                         "v_cross_gate_timestep": av_ca_a2v_gate_noise_timestep,
                         "a_cross_gate_timestep": av_ca_v2a_gate_noise_timestep,
                         "transformer_options": transformer_options,
+                        "self_attention_mask": self_attention_mask,
+                        "v_prompt_timestep": v_prompt_timestep,
+                        "a_prompt_timestep": a_prompt_timestep,
                     },
                     {"original_block": block_wrap},
                 )
@@ -787,6 +942,9 @@ class LTXAVModel(LTXVModel):
                     v_cross_gate_timestep=av_ca_a2v_gate_noise_timestep,
                     a_cross_gate_timestep=av_ca_v2a_gate_noise_timestep,
                     transformer_options=transformer_options,
+                    self_attention_mask=self_attention_mask,
+                    v_prompt_timestep=v_prompt_timestep,
+                    a_prompt_timestep=a_prompt_timestep,
                 )
 
         return [vx, ax]