Files
Azornes-Comfyui-Model-Resolver/__init__.py
T
Dariusz L 6f9aa9cc55 Improve Model Resolver dependency marker node compatibility and rendering
- Adopt ComfyUI's ComfyExtension/comfy_entrypoint API in __init__.py when
  available, falling back to legacy NODE_CLASS_MAPPINGS/DISPLAY_NAME_MAPPINGS
  on older runtimes so the node loads across ComfyUI versions.
- Hook into beforeRegisterNodeDef, loadedGraphNode, and afterConfigureGraph
  in web/resolver.js so marker nodes are patched during registration, graph
  load, and initial render.
- Teach model_resolver.js to recognise the marker node by every known class
  property shape, patch its type on creation, enforce a minimum size with
  setSize() when present, and dirty the canvas so changes are reflected.
2026-07-06 21:59:30 +02:00

5253 lines
247 KiB
Python

"""
@author: Azornes
@title: ComfyUI Model Resolver
@version: 1.0.0
@description: Extension for resolving missing models and downloading from HuggingFace/CivitAI
"""
import asyncio
import threading
import time
import sys
import os
if not __package__ or __package__ == "":
this_dir = os.path.dirname(os.path.abspath(__file__))
parent_dir = os.path.dirname(this_dir)
if parent_dir not in sys.path:
sys.path.insert(0, parent_dir)
package_name = os.path.basename(this_dir)
__package__ = package_name
current_module = sys.modules.get(__name__)
if current_module:
sys.modules[package_name] = current_module
if not hasattr(current_module, "__path__"):
current_module.__path__ = [this_dir]
from .core.log_system import LogLevel, create_module_logger, logger as backend_log_controller
from .core.log_system.config import LOG_LEVEL as BACKEND_DEFAULT_LOG_LEVEL
# Web directory for JavaScript interface
WEB_DIRECTORY = "./web"
MODEL_RESOLVER_DEPENDENCY_NODE_TYPE = "ModelResolverDependency"
MODEL_RESOLVER_DEPENDENCY_NODE_DISPLAY_NAME = "Model Resolver Opener"
MODEL_RESOLVER_DEPENDENCY_NODE_CATEGORY = "Model Resolver/Workflow"
MODEL_RESOLVER_DEPENDENCY_NODE_DESCRIPTION = (
"A passive opener node for workflows that intentionally depend on "
"Model Resolver metadata. It does not process images, models, or prompts."
)
try:
from comfy_api.latest import ComfyExtension, io
except Exception:
ComfyExtension = None
io = None
if ComfyExtension is not None and io is not None:
class ModelResolverDependencyNode(io.ComfyNode):
"""Canvas node that declares Model Resolver and opens its workflow tools."""
@classmethod
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id=MODEL_RESOLVER_DEPENDENCY_NODE_TYPE,
display_name=MODEL_RESOLVER_DEPENDENCY_NODE_DISPLAY_NAME,
category=MODEL_RESOLVER_DEPENDENCY_NODE_CATEGORY,
description=MODEL_RESOLVER_DEPENDENCY_NODE_DESCRIPTION,
inputs=[],
outputs=[],
)
@classmethod
def execute(cls) -> io.NodeOutput:
return io.NodeOutput()
class ModelResolverNodeExtension(ComfyExtension):
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [ModelResolverDependencyNode]
async def comfy_entrypoint() -> ComfyExtension:
return ModelResolverNodeExtension()
__all__ = ["WEB_DIRECTORY", "comfy_entrypoint"]
else:
class ModelResolverDependencyNode:
"""Legacy fallback for ComfyUI builds without the v3 custom-node API."""
DESCRIPTION = MODEL_RESOLVER_DEPENDENCY_NODE_DESCRIPTION
RETURN_TYPES = ()
FUNCTION = "noop"
CATEGORY = MODEL_RESOLVER_DEPENDENCY_NODE_CATEGORY
@classmethod
def INPUT_TYPES(cls):
return {"required": {}}
def noop(self):
return ()
NODE_CLASS_MAPPINGS = {
MODEL_RESOLVER_DEPENDENCY_NODE_TYPE: ModelResolverDependencyNode,
}
NODE_DISPLAY_NAME_MAPPINGS = {
MODEL_RESOLVER_DEPENDENCY_NODE_TYPE: MODEL_RESOLVER_DEPENDENCY_NODE_DISPLAY_NAME,
}
__all__ = ["WEB_DIRECTORY", "NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
class JobProgressTracker:
"""Helper class for thread-safe job progress tracking and cancellation management."""
def __init__(self, default_message="Processing..."):
self.lock = threading.Lock()
self.progress = {}
self.cancelled = set()
self.default_message = default_message
def cleanup(self, max_age_seconds=300):
cutoff = time.time() - max_age_seconds
with self.lock:
expired = [
pid
for pid, data in self.progress.items()
if data.get("updated_at", data.get("created_at", 0)) < cutoff
]
for pid in expired:
self.progress.pop(pid, None)
self.cancelled.difference_update(expired)
def update(self, progress_id, source=None, stage=None, message=None, percent=None, status=None, **payload):
if not progress_id:
return
if source is not None:
payload["source"] = source
if stage is not None:
payload["stage"] = stage
if message is not None:
payload["message"] = message
if percent is not None:
payload["percent"] = percent
if status is not None:
payload["status"] = status
now = time.time()
with self.lock:
current = self.progress.get(progress_id, {})
# If the job was cancelled, force it to remain cancelled.
if progress_id in self.cancelled and payload.get("status") != "cancelled":
payload["status"] = "cancelled"
payload["stage"] = "cancelled"
payload["message"] = "Cancelled"
payload["percent"] = 100
payload["cancelled"] = True
# Normalize percent if present
if "percent" in payload and payload["percent"] is not None:
try:
payload["percent"] = max(0.0, min(100.0, float(payload["percent"])))
except (TypeError, ValueError):
pass
self.progress[progress_id] = {
"created_at": now,
"message": self.default_message,
**current,
**payload,
"progress_id": progress_id,
"updated_at": now,
}
def is_cancelled(self, progress_id) -> bool:
if not progress_id:
return False
with self.lock:
return progress_id in self.cancelled
def mark_cancelled(self, progress_id, cancel_message="Cancelled") -> bool:
self.cleanup()
with self.lock:
current = self.progress.get(progress_id, {})
self.cancelled.add(progress_id)
self.progress[progress_id] = {
"created_at": time.time(),
**current,
"progress_id": progress_id,
"status": "cancelled",
"stage": "cancelled",
"message": cancel_message,
"percent": 100,
"cancelled": True,
"updated_at": time.time(),
}
return True
def get(self, progress_id):
with self.lock:
val = self.progress.get(progress_id)
return dict(val) if val else None
class ModelResolverExtension:
"""Main extension class for Model Resolver."""
def __init__(self):
self.routes_setup = False
self.logger = create_module_logger(__name__)
self.analysis_progress = JobProgressTracker("Analyzing...")
self.loaded_progress = JobProgressTracker("Loading loaded models...")
self.search_tracker = JobProgressTracker("Searching...")
self.hash_tracker = JobProgressTracker("Preparing hash calculation...")
self.metadata_builder_progress = JobProgressTracker("Building local metadata...")
self.search_result_timestamps = {}
def initialize(self):
"""Initialize the extension and set up API routes."""
try:
self.setup_routes()
self.logger.info("Model Resolver: Extension initialized successfully")
except Exception as e:
self.logger.error(
f"Model Resolver: Extension initialization failed: {e}", exc_info=True
)
def setup_routes(self):
"""Register API routes for the Model Resolver extension."""
if self.routes_setup:
return # Already set up
try:
from aiohttp import web
# Try to get routes from PromptServer
try:
from server import PromptServer
if (
not hasattr(PromptServer, "instance")
or PromptServer.instance is None
):
self.logger.debug("Model Resolver: PromptServer not available yet")
return False
routes = PromptServer.instance.routes
except (ImportError, AttributeError) as e:
self.logger.debug(f"Model Resolver: Could not access PromptServer: {e}")
return False
# Import resolver modules
try:
from .core.resolver import (
analyze_and_find_matches,
apply_resolution,
get_local_model_hash_metadata,
invalidate_local_hash_match_cache,
search_local_matches_by_hash,
search_local_matches,
)
from .core.workflow_analyzer import analyze_workflow_models
from .core.path_templates import infer_download_path_templates
from .core.metadata_audit import audit_metadata_sizes
from .core.metadata_builder import (
build_missing_local_metadata,
get_metadata_build_capabilities,
)
from .core.scanner import get_model_files, invalidate_model_files_cache, find_local_file_path
from .core.path_utils import (
extract_safetensors_header_sha256,
get_filename_from_path,
is_path_in_configured_model_roots,
read_json_safe,
write_json_atomic,
)
from .core.type_utils import (
first_non_empty,
to_int,
to_bool,
MODEL_EXTENSIONS,
format_size_bytes,
normalize_sha256,
extract_sha256_from_metadata,
fetch_remote_file_size_cached,
looks_like_model_file,
normalize_category_to_model_type,
get_category_folder_keys,
get_enabled_download_categories,
)
from .core.settings import (
TEMPLATE_KEY_ALIASES,
bool_setting as resolver_bool_setting,
get_default_root_for_category,
load_settings as load_resolver_settings,
resolve_download_subfolder,
save_settings as save_resolver_settings,
)
except ImportError as e:
self.logger.error(f"Model Resolver: Could not import core modules: {e}")
return False
# Import download modules
try:
from .core.downloader import (
start_background_download,
get_progress,
get_all_progress,
cancel_download,
pause_download,
resume_download,
get_aria2_status,
start_aria2_daemon,
stop_aria2_daemon,
get_download_directory,
get_metadata_sidecar_path,
normalize_download_category,
write_lora_manager_metadata,
sanitize_download_filename,
)
from .core.aria2_installer import Aria2InstallError, install_aria2_engine
from .core.sources.popular import (
get_popular_model_url,
search_popular_models,
reload_databases as reload_popular_databases,
)
from .core.sources.model_list import (
search_model_list,
search_model_list_multiple,
get_model_list_update_status,
update_model_list_from_remote,
reload_model_list,
)
from .core.sources.huggingface import (
search_huggingface_for_file,
parse_huggingface_url,
get_huggingface_download_url,
get_author_fallback_index_status,
refresh_author_fallback_index,
check_huggingface_token,
check_brave_search_api_key,
clear_search_cache as clear_huggingface_search_cache,
)
from .core.sources.civitai import (
search_civitai_for_file,
search_civitai,
parse_civitai_url,
get_civitai_download_url,
get_civitai_model_details,
resolve_urn,
check_civitai_api_key,
check_civitai_session_token,
clear_search_cache as clear_civitai_search_cache,
)
from .core.sources.civarchive import (
CivArchiveSearchError,
is_civarchive_available,
search_civarchive_for_file,
parse_civarchive_url,
resolve_civarchive_by_hash,
resolve_civarchive_model_version,
get_civarchive_model_details,
clear_search_cache as clear_civarchive_search_cache,
)
from .core.sources.lora_manager_archive import (
is_lora_manager_archive_available,
search_lora_manager_archive_for_file,
clear_search_cache as clear_lora_manager_archive_search_cache,
)
from .core.sources import clear_all_search_caches
download_available = True
except ImportError as e:
self.logger.warning(
f"Model Resolver: Download features not available: {e}"
)
download_available = False
def json_api_endpoint(error_prefix, return_success_on_error=False):
def decorator(func):
from functools import wraps
@wraps(func)
async def wrapper(request, *args, **kwargs):
try:
return await func(request, *args, **kwargs)
except Exception as e:
self.logger.error(
f"Model Resolver {error_prefix} error: {e}", exc_info=True
)
response_data = {"error": str(e)}
if return_success_on_error:
response_data["success"] = False
return web.json_response(response_data, status=500)
return wrapper
return decorator
def get_progress_response(tracker, request, param_name="progress_id", not_found_payload=None, not_found_status=200, found_wrapper=None):
job_id = request.match_info.get(param_name, "").strip()
if not job_id:
return web.json_response({"error": f"{param_name} is required"}, status=400)
tracker.cleanup()
progress = tracker.get(job_id)
if not progress:
payload = not_found_payload or {"error": "progress not found"}
return web.json_response(payload, status=not_found_status)
if found_wrapper:
return web.json_response(found_wrapper(progress))
return web.json_response(progress)
def cancel_progress_response(tracker, request, param_name="progress_id", cancel_message="Cancelled"):
job_id = request.match_info.get(param_name, "").strip()
if not job_id:
return web.json_response({"error": f"{param_name} is required"}, status=400)
cancelled = tracker.mark_cancelled(job_id, cancel_message)
return web.json_response({
"success": True,
"cancelled": cancelled,
"progress_id": job_id,
})
async def get_override_settings_from_request(request):
settings = await asyncio.to_thread(load_resolver_settings)
if request.method == "POST":
try:
payload = await request.json()
if isinstance(payload, dict) and "aria2c_path" in payload:
settings = dict(settings)
settings["aria2c_path"] = payload.get("aria2c_path", "")
except Exception:
pass
return settings
# ==================== BASE MODELS CONFIG ROUTE ====================
@routes.get("/model_resolver/base-models")
@json_api_endpoint("base-models")
async def get_base_models(request):
"""Return the base models config from metadata/base-models.json.
Returns {base_models: [{name, aliases}]} so the frontend
dropdown can populate correctly via baseModels.base_models.
"""
from .core.sources.popular import get_base_models_config
data = get_base_models_config()
return web.json_response(data)
@routes.get("/model_resolver/base-models/status")
@json_api_endpoint("base-models status")
async def get_base_models_status_route(request):
"""Get local and optional remote base models status."""
check_remote = request.query.get("check_remote") == "1"
from .core.sources.popular import get_base_models_status
status = await asyncio.to_thread(get_base_models_status, check_remote)
return web.json_response(status)
@routes.post("/model_resolver/base-models/update")
@json_api_endpoint("base-models update")
async def update_base_models_route(request):
"""Update base models list from CivitAI."""
from .core.sources.popular import update_base_models_from_remote
status = await asyncio.to_thread(update_base_models_from_remote)
return web.json_response(status)
# ==================== ANALYZE ROUTES ====================
@routes.post("/model_resolver/analyze")
async def analyze_workflow(request):
"""Analyze workflow and return missing models with matches."""
try:
data = await request.json()
workflow_json = data.get("workflow")
analysis_id = str(data.get("analysis_id") or "").strip()
force_rescan = to_bool(data.get("force_rescan"), False)
if force_rescan:
invalidate_local_hash_match_cache()
if workflow_json is None:
return web.json_response(
{"error": "Workflow JSON is required"}, status=400
)
if not isinstance(workflow_json, dict):
return web.json_response(
{"error": "Workflow JSON must be an object"}, status=400
)
if analysis_id:
self.analysis_progress.update(
analysis_id,
status="starting",
stage="starting",
message="Starting analysis...",
current=0,
total=0,
)
def update_analysis_progress(payload):
if not analysis_id:
return
status = "running" if payload.get("stage") != "completed" else "completed"
self.analysis_progress.update(
analysis_id,
status=status,
**payload
)
# Analyze and find matches
result = await asyncio.to_thread(
analyze_and_find_matches,
workflow_json,
0.0,
10,
update_analysis_progress if analysis_id else None,
force_rescan=force_rescan,
)
# Filter out LoraManager lorAs that already exist locally (exists=True)
# These should not appear in missing models at all
missing_models = result.get("missing_models", [])
filtered_missing = []
for missing in missing_models:
is_lora = missing.get("is_lora_v2")
exists = missing.get("exists")
name = missing.get("name") or missing.get("original_path", "")
self.logger.debug(
f"Filtering: {name} is_lora_v2={is_lora} exists={exists}"
)
# Skip LoraManager lorAs that already exist locally
if is_lora and exists:
self.logger.info(
f"Filtered out LoraManager lora: {name}"
)
continue
filtered_missing.append(missing)
result["missing_models"] = filtered_missing
result["total_missing"] = len(filtered_missing)
# If download available, check for download sources only from LOCAL sources
# (workflow_url, popular, model-list.json) - skip automatic online search
# Online search is now only triggered on-demand via search button
if download_available:
for missing in result.get("missing_models", []):
# Check if there's a 100% local match
matches = missing.get("matches", [])
has_perfect_match = any(
m.get("confidence", 0) == 100 for m in matches
)
if not has_perfect_match:
filename = get_filename_from_path(
missing.get("original_path", "")
)
# 0. Check workflow URL first (highest priority - directly from workflow)
workflow_url = missing.get("workflow_url", "")
if workflow_url:
# Determine source from URL
if "huggingface.co" in workflow_url:
source = "huggingface"
elif "civitai.com" in workflow_url:
source = "civitai"
else:
source = "workflow"
# Try to get file size using cached remote helper
file_size = fetch_remote_file_size_cached(workflow_url, timeout=5)
missing["download_source"] = {
"source": source,
"url": workflow_url,
"model_url": missing.get(
"workflow_model_url", workflow_url
),
"filename": filename,
"directory": missing.get(
"workflow_directory", ""
)
or missing.get("category", "checkpoints"),
"match_type": "exact",
"url_source": "workflow",
"size": file_size,
}
continue
# 1. Check popular models (always exact match)
popular_info = get_popular_model_url(filename)
if popular_info:
popular_model_list_result = search_model_list(
filename, exact_only=True
)
missing["download_source"] = {
"source": "popular",
"url": popular_info.get("url"),
"filename": filename,
"type": popular_info.get("type"),
"directory": popular_info.get("directory"),
"size": (
popular_model_list_result.get("size")
if popular_model_list_result
else None
)
or popular_info.get("size"),
"match_type": "exact",
}
continue
# 2. Check model list (ComfyUI Manager database)
# Use exact_only=True to avoid confusing fuzzy matches for downloads
model_list_result = search_model_list(
filename, exact_only=True
)
if model_list_result:
missing["download_source"] = {
"source": "model_list",
"url": model_list_result.get("url"),
"filename": model_list_result.get("filename"),
"name": model_list_result.get("name"),
"type": model_list_result.get("type"),
"directory": model_list_result.get("directory"),
"size": model_list_result.get("size"),
"match_type": model_list_result.get(
"match_type"
),
"confidence": model_list_result.get(
"confidence"
),
}
continue
# NOTE: Search for online sources (HuggingFace, CivitAI) is
# now done on-demand via /model_resolver/search endpoint
# when user clicks "Search Online" button, not automatically
if analysis_id:
self.analysis_progress.update(
analysis_id,
status="completed",
stage="completed",
message="Analysis complete",
current=result.get("total_missing", 0),
total=result.get("total_missing", 0),
)
return web.json_response(result)
except Exception as e:
if "analysis_id" in locals() and analysis_id:
self.analysis_progress.update(
analysis_id,
status="error",
stage="error",
message=str(e),
current=0,
total=0,
)
self.logger.error(f"Model Resolver analyze error: {e}", exc_info=True)
return web.json_response({"error": str(e)}, status=500)
@routes.get("/model_resolver/analyze-progress/{analysis_id}")
@json_api_endpoint("analyze-progress")
async def get_analyze_progress(request):
"""Get workflow analysis progress."""
return get_progress_response(
self.analysis_progress,
request,
param_name="analysis_id",
not_found_payload={
"status": "unknown",
"stage": "unknown",
"message": "No analysis progress available",
"current": 0,
"total": 0,
}
)
@routes.post("/model_resolver/resolve")
@json_api_endpoint("resolve", return_success_on_error=True)
async def resolve_models(request):
"""Apply model resolution and return updated workflow."""
data = await request.json()
workflow_json = data.get("workflow")
resolutions = data.get("resolutions", [])
if not workflow_json:
return web.json_response(
{"error": "Workflow JSON is required"}, status=400
)
if not resolutions:
return web.json_response(
{"error": "Resolutions array is required"}, status=400
)
# Apply resolutions
updated_workflow = apply_resolution(workflow_json, resolutions)
return web.json_response(
{"workflow": updated_workflow, "success": True}
)
@routes.post("/model_resolver/local-matches")
@json_api_endpoint("local-matches")
async def local_matches(request):
"""Search local model files by filename/path."""
data = await request.json()
filename = data.get("filename", "")
category = data.get("category", "")
force_rescan = to_bool(data.get("force_rescan"), False)
if force_rescan:
invalidate_local_hash_match_cache()
if not filename:
return web.json_response(
{"error": "filename is required"}, status=400
)
matches = search_local_matches(
filename,
category=category or None,
similarity_threshold=0.0,
max_matches_per_model=10,
force_rescan=force_rescan,
)
return web.json_response({"matches": matches})
@routes.post("/model_resolver/local-model-hashes")
@json_api_endpoint("local-model-hashes")
async def local_model_hashes(request):
"""Return SHA256 hashes already stored in local sidecar metadata."""
data = await request.json()
model = data.get("model") if isinstance(data.get("model"), dict) else {}
path = (
data.get("path")
or data.get("file_path")
or data.get("resolved_path")
or model.get("path")
or model.get("resolved_path")
or ""
)
if not path:
return web.json_response(
{"error": "path is required"}, status=400
)
return web.json_response(
get_local_model_hash_metadata(path, model=model)
)
@routes.post("/model_resolver/workflow-model-hashes")
@json_api_endpoint("workflow-model-hashes")
async def workflow_model_hashes(request):
"""Return hash metadata for existing local models used by a workflow."""
data = await request.json()
workflow_json = data.get("workflow")
if not isinstance(workflow_json, dict):
return web.json_response(
{"error": "Workflow JSON must be an object"}, status=400
)
settings = await asyncio.to_thread(load_resolver_settings)
if not resolver_bool_setting(
settings.get("workflow_hash_metadata_enabled"), True
):
return web.json_response(
{
"success": True,
"enabled": False,
"models": [],
"by_node": {},
"by_path": {},
"count": 0,
}
)
available_models = await asyncio.to_thread(get_model_files, False)
refs = await asyncio.to_thread(
analyze_workflow_models,
workflow_json,
available_models,
)
by_node = {}
by_path = {}
models = []
seen = set()
for ref in refs:
if not isinstance(ref, dict) or not ref.get("exists"):
continue
full_path = str(ref.get("full_path") or "").strip()
if not full_path:
continue
model_info = {
"path": full_path,
"filename": get_filename_from_path(full_path),
"relative_path": ref.get("original_path") or "",
"category": ref.get("category") or "",
}
metadata = get_local_model_hash_metadata(
full_path, model=model_info
)
sha256 = normalize_sha256(metadata.get("sha256"))
if not sha256:
continue
entry = {
"node_id": ref.get("node_id"),
"node_type": ref.get("node_type") or "",
"widget_index": ref.get("widget_index"),
"widget_name": ref.get("widget_name") or "",
"path": ref.get("original_path") or "",
"filename": get_filename_from_path(
ref.get("original_path") or full_path
),
"category": ref.get("category") or "",
"sha256": sha256,
"size": metadata.get("size") or 0,
}
entry_key = (
str(entry.get("node_id")),
str(entry.get("widget_index")),
entry.get("path"),
sha256,
)
if entry_key in seen:
continue
seen.add(entry_key)
models.append(entry)
path_key = str(entry.get("path") or entry.get("filename") or "")
if path_key:
by_path[path_key] = entry
by_path[get_filename_from_path(path_key)] = entry
node_key = f"{entry.get('node_id')}:{entry.get('widget_index')}"
by_node[node_key] = entry
return web.json_response(
{
"success": True,
"enabled": True,
"models": models,
"by_node": by_node,
"by_path": by_path,
"count": len(models),
}
)
@routes.post("/model_resolver/local-matches-by-hash")
@json_api_endpoint("local-matches-by-hash")
async def local_matches_by_hash(request):
"""Search local model metadata sidecars for a remote SHA256."""
data = await request.json()
sha256 = normalize_sha256(
data.get("sha256")
or data.get("hash")
or data.get("SHA256")
or ""
)
if not sha256:
return web.json_response(
{"error": "sha256 is required"}, status=400
)
category = data.get("category", "")
source = str(
data.get("source")
or data.get("hash_lookup_source")
or "download_source"
).strip().lower().replace("-", "_")
filename = (
data.get("filename")
or data.get("path")
or data.get("model_name")
or ""
)
max_matches = to_int(data.get("max_matches"), 20)
force_rescan = to_bool(data.get("force_rescan"), False)
matches = search_local_matches_by_hash(
sha256,
category=category or None,
max_matches=max_matches,
force_rescan=force_rescan,
)
enriched_matches = [
{
**match,
"hash_lookup_source": source or "download_source",
"hash_lookup_filename": filename,
"hash_lookup_sha256": sha256,
}
for match in matches
]
return web.json_response(
{
"sha256": sha256,
"local_hash_matches": enriched_matches,
"matches": enriched_matches,
}
)
@routes.post("/model_resolver/open-containing-folder")
@json_api_endpoint("open-containing-folder")
async def open_containing_folder(request):
"""Open Explorer at the folder containing the selected model."""
import os
import subprocess
data = await request.json()
target_path = data.get("path", "")
if not target_path:
return web.json_response(
{"error": "path is required"}, status=400
)
normalized_path = os.path.abspath(os.path.normpath(target_path))
if not os.path.exists(normalized_path):
return web.json_response(
{"error": "path does not exist"}, status=404
)
if not is_path_in_configured_model_roots(normalized_path):
return web.json_response(
{"error": "path is outside configured model directories"},
status=403,
)
if os.path.isfile(normalized_path):
subprocess.Popen(
["explorer.exe", "/select,", normalized_path],
shell=False,
)
else:
os.startfile(normalized_path)
return web.json_response({"success": True})
# cleanup_hash_progress, update_hash_progress, is_hash_progress_cancelled, and mark_hash_progress_cancelled removed
from .core.path_utils import HashCalculationCancelled
def resolve_hash_file_request(data):
import os as _os
file_path = (
data.get("file_path")
or data.get("resolved_path")
or data.get("path")
or ""
)
if not file_path:
return "", "file_path is required"
normalized_path = _os.path.abspath(_os.path.normpath(file_path))
if not _os.path.exists(normalized_path) or not _os.path.isfile(normalized_path):
return "", "file does not exist"
if not is_path_in_configured_model_roots(normalized_path):
return "", "file is outside configured model directories"
return normalized_path, ""
def write_calculated_hash_metadata(
normalized_path,
metadata_path,
sha256,
sha256_source="file",
):
import os as _os
model_dir = _os.path.abspath(_os.path.dirname(normalized_path))
resolved_metadata_path = ""
if metadata_path:
candidate_path = _os.path.abspath(_os.path.normpath(metadata_path))
try:
same_dir = _os.path.commonpath([model_dir, candidate_path]) == model_dir
except ValueError:
same_dir = False
if same_dir:
resolved_metadata_path = candidate_path
if not resolved_metadata_path:
resolved_metadata_path = get_metadata_sidecar_path(normalized_path)
metadata_updated = False
try:
metadata = read_json_safe(resolved_metadata_path, {})
if not isinstance(metadata, dict):
metadata = {}
filename = _os.path.basename(normalized_path)
stem, _ext = _os.path.splitext(filename)
hashes = metadata.get("hashes")
if not isinstance(hashes, dict):
hashes = {}
hashes["SHA256"] = sha256
metadata["sha256"] = sha256
metadata["hashes"] = hashes
metadata["hash_status"] = "completed"
metadata["sha256_source"] = sha256_source or "file"
metadata["last_checked_at"] = time.time()
metadata.setdefault("file_name", stem)
metadata.setdefault("model_name", stem)
metadata.setdefault("file_path", normalized_path.replace("\\", "/"))
try:
metadata.setdefault("size", _os.path.getsize(normalized_path))
except Exception:
pass
write_json_atomic(resolved_metadata_path, metadata, indent=2)
metadata_updated = True
self.logger.info(
f"Stored SHA256 and updated metadata: {resolved_metadata_path}"
)
except Exception as metadata_error:
self.logger.warning(
f"Could not update metadata with calculated SHA256 for {normalized_path}: {metadata_error}"
)
return resolved_metadata_path, metadata_updated
def calculate_sha256_with_progress(normalized_path, progress_id=""):
import os as _os
from .core.path_utils import calculate_file_sha256 as _calculate_file_sha256_core
total_bytes = max(0, _os.path.getsize(normalized_path))
self.hash_tracker.update(
progress_id,
status="running",
stage="header",
message="Checking safetensors header...",
percent=0,
bytes_read=0,
total_bytes=total_bytes,
)
if self.hash_tracker.is_cancelled(progress_id):
raise HashCalculationCancelled()
is_safetensors = normalized_path.lower().endswith(".safetensors")
if is_safetensors:
self.logger.info(
f"Checking safetensors header for SHA256: {normalized_path}"
)
else:
self.logger.info(
"Skipping safetensors header lookup for non-safetensors file; "
f"calculating full SHA256: {normalized_path}"
)
header_sha256 = extract_safetensors_header_sha256(normalized_path)
if header_sha256:
self.logger.info(
f"Found SHA256 in safetensors header: {normalized_path}"
)
self.hash_tracker.update(
progress_id,
status="running",
stage="header",
message="Found SHA256 in safetensors header",
percent=98,
bytes_read=0,
total_bytes=total_bytes,
sha256=header_sha256,
hash=header_sha256,
sha256_source="safetensors_header",
)
return header_sha256, "safetensors_header"
if is_safetensors:
self.logger.info(
"No SHA256 found in safetensors header; calculating full "
f"file SHA256: {normalized_path}"
)
self.hash_tracker.update(
progress_id,
status="running",
stage="hashing",
message="Calculating SHA256...",
percent=0,
bytes_read=0,
total_bytes=total_bytes,
)
_bytes_read = [0]
_last_update = [0.0]
def on_progress(bytes_read, total_bytes):
_bytes_read[0] = bytes_read
now = time.time()
if now - _last_update[0] >= 0.15 or bytes_read >= total_bytes:
percent = 98 if total_bytes <= 0 else min(
98,
(bytes_read / total_bytes) * 98,
)
self.hash_tracker.update(
progress_id,
status="running",
stage="hashing",
message="Calculating SHA256...",
percent=percent,
bytes_read=bytes_read,
total_bytes=total_bytes,
)
_last_update[0] = now
def is_cancelled():
if self.hash_tracker.is_cancelled(progress_id):
percent = 0 if total_bytes <= 0 else min(
98,
(_bytes_read[0] / total_bytes) * 98,
)
self.hash_tracker.update(
progress_id,
status="cancelled",
stage="cancelled",
message="Hash calculation cancelled",
percent=percent,
bytes_read=_bytes_read[0],
total_bytes=total_bytes,
)
return True
return False
sha256 = _calculate_file_sha256_core(
normalized_path,
chunk_size=1024 * 1024 * 4,
on_progress=on_progress,
is_cancelled=is_cancelled,
use_safetensors_header=False,
)
return sha256, "file"
@routes.post("/model_resolver/calculate-file-hash")
@json_api_endpoint("calculate-file-hash")
async def calculate_file_hash_route(request):
"""Calculate SHA256 for a local model and persist it to sidecar metadata."""
data = await request.json()
metadata_path = data.get("metadata_path") or ""
normalized_path, error = resolve_hash_file_request(data)
if error == "file_path is required":
return web.json_response(
{"error": "file_path is required"}, status=400
)
if error:
status = 403 if error == "file is outside configured model directories" else 404
return web.json_response(
{"error": error}, status=status
)
sha256, sha256_source = calculate_sha256_with_progress(normalized_path)
if not sha256:
return web.json_response(
{"error": "could not calculate hash"}, status=500
)
resolved_metadata_path, metadata_updated = write_calculated_hash_metadata(
normalized_path,
metadata_path,
sha256,
sha256_source,
)
return web.json_response(
{
"success": True,
"sha256": sha256,
"hash": sha256,
"sha256_source": sha256_source,
"file_path": normalized_path,
"metadata_path": resolved_metadata_path,
"metadata_updated": metadata_updated,
}
)
@routes.post("/model_resolver/calculate-file-hash/start")
@json_api_endpoint("calculate-file-hash-start")
async def calculate_file_hash_start_route(request):
"""Start SHA256 calculation in a background thread."""
import uuid
data = await request.json()
metadata_path = data.get("metadata_path") or ""
normalized_path, error = resolve_hash_file_request(data)
if error == "file_path is required":
return web.json_response(
{"error": "file_path is required"}, status=400
)
if error:
status = 403 if error == "file is outside configured model directories" else 404
return web.json_response(
{"error": error}, status=status
)
self.hash_tracker.cleanup()
progress_id = f"hash_{uuid.uuid4().hex}"
self.hash_tracker.update(
progress_id,
status="queued",
stage="queued",
message="Preparing hash calculation...",
percent=0,
file_path=normalized_path,
)
def run_hash_task():
try:
sha256, sha256_source = calculate_sha256_with_progress(
normalized_path,
progress_id=progress_id,
)
if self.hash_tracker.is_cancelled(progress_id):
raise HashCalculationCancelled()
self.hash_tracker.update(
progress_id,
status="running",
stage="metadata",
message="Saving metadata...",
percent=99,
)
resolved_metadata_path, metadata_updated = write_calculated_hash_metadata(
normalized_path,
metadata_path,
sha256,
sha256_source,
)
self.hash_tracker.update(
progress_id,
status="done",
stage="done",
message="Hash calculated",
percent=100,
sha256=sha256,
hash=sha256,
sha256_source=sha256_source,
file_path=normalized_path,
metadata_path=resolved_metadata_path,
metadata_updated=metadata_updated,
)
except HashCalculationCancelled:
self.hash_tracker.update(
progress_id,
status="cancelled",
stage="cancelled",
message="Hash calculation cancelled",
)
except Exception as exc:
self.logger.exception(f"Hash calculation failed for {normalized_path}: {exc}")
self.hash_tracker.update(
progress_id,
status="error",
stage="error",
message=str(exc) or "Hash calculation failed",
percent=100,
error=str(exc) or "Hash calculation failed",
)
threading.Thread(target=run_hash_task, daemon=True).start()
return web.json_response(
{
"success": True,
"progress_id": progress_id,
}
)
@routes.get("/model_resolver/calculate-file-hash/progress/{progress_id}")
@json_api_endpoint("calculate-file-hash-progress")
async def calculate_file_hash_progress_route(request):
"""Return progress for a background SHA256 calculation."""
return get_progress_response(
self.hash_tracker,
request,
not_found_status=404
)
@routes.post("/model_resolver/calculate-file-hash/cancel/{progress_id}")
@json_api_endpoint("calculate-file-hash-cancel")
async def calculate_file_hash_cancel_route(request):
"""Cancel a background SHA256 calculation."""
return cancel_progress_response(
self.hash_tracker,
request,
cancel_message="Stopping hash calculation..."
)
@routes.get("/model_resolver/models")
@json_api_endpoint("get_models")
async def get_models(request):
"""Get list of all available models."""
force_rescan = to_bool(
request.query.get("force") or request.query.get("force_rescan"),
False
)
if force_rescan:
invalidate_local_hash_match_cache()
models = get_model_files(force_rescan=force_rescan)
return web.json_response(models)
@routes.post("/model_resolver/metadata-size-audit")
@json_api_endpoint("metadata-size-audit")
async def metadata_size_audit_route(request):
"""Check local model .metadata.json sidecars for stale size values."""
payload = {}
try:
if request.can_read_body:
payload = await request.json()
except Exception:
payload = {}
if not isinstance(payload, dict):
payload = {}
force_rescan = to_bool(payload.get("force_rescan"), True)
result = await asyncio.to_thread(
audit_metadata_sizes,
force_rescan=force_rescan,
worker_count=payload.get("worker_count"),
batch_size=payload.get("batch_size"),
)
return web.json_response(result)
@routes.get("/model_resolver/metadata-build/capabilities")
@json_api_endpoint("metadata-build-capabilities")
async def metadata_build_capabilities_route(request):
"""Return local CPU and worker limits for the metadata builder."""
return web.json_response(get_metadata_build_capabilities())
@routes.post("/model_resolver/metadata-build/start")
@json_api_endpoint("metadata-build-start")
async def metadata_build_start_route(request):
"""Create missing local metadata sidecars and fill missing SHA256 values."""
import uuid
payload = {}
try:
if request.can_read_body:
payload = await request.json()
except Exception:
payload = {}
if not isinstance(payload, dict):
payload = {}
force_rescan = to_bool(payload.get("force_rescan"), True)
worker_count = to_int(payload.get("worker_count"), 0)
self.metadata_builder_progress.cleanup()
progress_id = f"metadata_build_{uuid.uuid4().hex}"
self.metadata_builder_progress.update(
progress_id,
status="queued",
stage="queued",
message="Preparing local metadata build...",
percent=0,
current=0,
total=0,
requested_worker_count=worker_count,
)
def update_metadata_build_progress(progress_payload):
if not isinstance(progress_payload, dict):
return
data = dict(progress_payload)
status = data.pop("status", None)
stage = data.get("stage") or ""
if not status:
if stage == "done":
status = "done"
elif stage == "cancelled":
status = "cancelled"
else:
status = "running"
self.metadata_builder_progress.update(
progress_id,
status=status,
**data,
)
def is_metadata_build_cancelled():
return self.metadata_builder_progress.is_cancelled(progress_id)
def run_metadata_build_task():
try:
result = build_missing_local_metadata(
force_rescan=force_rescan,
worker_count=worker_count,
progress_callback=update_metadata_build_progress,
is_cancelled=is_metadata_build_cancelled,
)
if result.get("cancelled") or is_metadata_build_cancelled():
self.metadata_builder_progress.update(
progress_id,
status="cancelled",
stage="cancelled",
message="Metadata build cancelled",
percent=100,
active_models=[],
active_worker_count=0,
current_model="",
current_path="",
bytes_read=0,
total_bytes=0,
result=result,
**result,
)
return
self.metadata_builder_progress.update(
progress_id,
status="done",
stage="done",
message="Local metadata build completed.",
percent=100,
active_models=[],
active_worker_count=0,
current_model="",
current_path="",
bytes_read=0,
total_bytes=0,
result=result,
**result,
)
except Exception as exc:
self.logger.exception(f"Metadata build failed: {exc}")
self.metadata_builder_progress.update(
progress_id,
status="error",
stage="error",
message=str(exc) or "Metadata build failed",
percent=100,
active_models=[],
active_worker_count=0,
current_model="",
current_path="",
bytes_read=0,
total_bytes=0,
error=str(exc) or "Metadata build failed",
)
threading.Thread(target=run_metadata_build_task, daemon=True).start()
return web.json_response(
{
"success": True,
"progress_id": progress_id,
}
)
@routes.get("/model_resolver/metadata-build/progress/{progress_id}")
@json_api_endpoint("metadata-build-progress")
async def metadata_build_progress_route(request):
"""Return progress for local metadata sidecar creation."""
return get_progress_response(
self.metadata_builder_progress,
request,
not_found_status=404,
)
@routes.post("/model_resolver/metadata-build/cancel/{progress_id}")
@json_api_endpoint("metadata-build-cancel")
async def metadata_build_cancel_route(request):
"""Cancel local metadata sidecar creation."""
return cancel_progress_response(
self.metadata_builder_progress,
request,
cancel_message="Stopping metadata build...",
)
@routes.post("/model_resolver/loaded")
@json_api_endpoint("get_loaded_models")
async def get_loaded_models(request):
"""Get all currently loaded models in the workflow."""
data = await request.json()
workflow_json = data.get("workflow")
loaded_id = str(
data.get("loaded_id") or data.get("progress_id") or ""
).strip()
if not workflow_json:
return web.json_response(
{"error": "Workflow JSON is required"}, status=400
)
if not isinstance(workflow_json, dict):
return web.json_response(
{"error": "Workflow JSON must be an object"}, status=400
)
def update_loaded_progress(
stage,
message,
percent=None,
status="running",
current=0,
total=0,
**payload,
):
if not loaded_id:
return
self.loaded_progress.update(
loaded_id,
status=status,
stage=stage,
message=message,
percent=percent,
current=current,
total=total,
**payload,
)
def get_workflow_node_count():
node_count = 0
nodes = workflow_json.get("nodes", [])
if isinstance(nodes, list):
node_count += len(nodes)
definitions = workflow_json.get("definitions", {})
subgraphs = (
definitions.get("subgraphs", [])
if isinstance(definitions, dict)
else []
)
if isinstance(subgraphs, list):
for subgraph in subgraphs:
if not isinstance(subgraph, dict):
continue
subgraph_nodes = subgraph.get("nodes", [])
if isinstance(subgraph_nodes, list):
node_count += len(subgraph_nodes)
return node_count
def interpolate_percent(start, end, current, total):
if not total:
return start
try:
ratio = max(0.0, min(1.0, float(current) / float(total)))
except (TypeError, ValueError, ZeroDivisionError):
ratio = 0.0
return start + ((end - start) * ratio)
def build_loaded_models_response():
from .core.workflow_analyzer import (
analyze_workflow_models,
URN_TYPE_MAP,
)
update_loaded_progress(
"scanning",
"Scanning local model index...",
percent=5,
)
# Get available models for existence checking
available_models = get_model_files()
# Create lookup for full paths by filename (with and without extension)
path_by_filename = {}
total_local_models = len(available_models)
update_loaded_progress(
"indexing",
f"Indexing {total_local_models} local models...",
percent=15,
current=0,
total=total_local_models,
)
for index, model_info in enumerate(available_models, start=1):
rel_path = model_info.get("relative_path", "")
if rel_path:
filename = get_filename_from_path(rel_path)
path_by_filename[filename] = model_info.get("path")
# Also add without extension for matching (simple approach)
if "." in filename:
filename_no_ext = filename.rsplit(".", 1)[0]
if filename_no_ext not in path_by_filename:
path_by_filename[filename_no_ext] = model_info.get("path")
# Add the full relative path as key too
path_by_filename[rel_path] = model_info.get("path")
if (
total_local_models
and (index == total_local_models or index % 250 == 0)
):
update_loaded_progress(
"indexing",
f"Indexing local model {index} of {total_local_models}",
percent=interpolate_percent(
15, 25, index, total_local_models
),
current=index,
total=total_local_models,
)
# Also use folder_paths.get_full_path() to get paths
try:
import folder_paths
except Exception:
folder_paths = None
folder_categories = [
"loras",
"checkpoints",
"vae",
"controlnet",
"upscale_models",
]
if folder_paths:
for index, category_name in enumerate(folder_categories, start=1):
update_loaded_progress(
"indexing",
f"Reading {category_name} model list...",
percent=interpolate_percent(
25, 35, index - 1, len(folder_categories)
),
current=index - 1,
total=len(folder_categories),
)
try:
filenames = folder_paths.get_filename_list(category_name)
for filename in filenames:
full_path = folder_paths.get_full_path(
category_name, filename
)
if (
full_path
and full_path not in path_by_filename.values()
):
path_by_filename[filename] = full_path
filename_no_ext = (
filename.rsplit(".", 1)[0]
if "." in filename
else filename
)
if filename_no_ext not in path_by_filename:
path_by_filename[filename_no_ext] = full_path
except Exception:
pass
workflow_node_count = get_workflow_node_count()
update_loaded_progress(
"analyzing",
"Analyzing workflow nodes...",
percent=35,
current=0,
total=workflow_node_count,
)
def update_workflow_analysis_progress(payload):
progress_payload = dict(payload or {})
current = progress_payload.pop("current", 0)
total = progress_payload.pop("total", workflow_node_count)
stage = progress_payload.pop("stage", "analyzing")
message = progress_payload.pop(
"message", "Analyzing workflow nodes..."
)
progress_payload.pop("percent", None)
update_loaded_progress(
stage,
message,
percent=interpolate_percent(35, 78, current, total),
current=current,
total=total,
**progress_payload,
)
# Analyze workflow to get all model references
all_model_refs = analyze_workflow_models(
workflow_json,
available_models=available_models,
progress_callback=update_workflow_analysis_progress,
)
# Also extract from node.properties.models
workflow_nodes = workflow_json.get("nodes", [])
nodes = list(workflow_nodes) if isinstance(workflow_nodes, list) else []
definitions = workflow_json.get("definitions", {})
subgraphs = (
definitions.get("subgraphs", [])
if isinstance(definitions, dict)
else []
)
for subgraph in subgraphs:
if isinstance(subgraph, dict):
subgraph_nodes = subgraph.get("nodes", [])
if isinstance(subgraph_nodes, list):
nodes.extend(subgraph_nodes)
# Collect all loaded models with their values
loaded_models = []
total_refs = len(all_model_refs)
update_loaded_progress(
"building",
"Building loaded models list...",
percent=78,
current=0,
total=total_refs,
)
# Process each model reference from analyze_workflow_models
for index, ref in enumerate(all_model_refs, start=1):
if total_refs and (index == total_refs or index % 50 == 0):
update_loaded_progress(
"building",
f"Building loaded model {index} of {total_refs}",
percent=interpolate_percent(78, 94, index, total_refs),
current=index,
total=total_refs,
)
original_path = ref.get("original_path", "")
node_id = ref.get("node_id")
widget_index = ref.get("widget_index")
node_type = ref.get("node_type", "")
category = ref.get("category", "unknown")
# Determine model name and strength
model_name = get_filename_from_path(original_path)
strength = None
# For standard LoraLoader nodes, strength is in next widget_value
if (
node_type in ["LoraLoader", "LoraLoaderModelOnly"]
and isinstance(widget_index, int)
):
# Find the node in workflow to get strength value
for node in nodes:
if str(node.get("id")) == str(node_id):
widgets_values = node.get("widgets_values", [])
if (
isinstance(widgets_values, list)
and len(widgets_values) > widget_index + 1
):
try:
strength = float(
widgets_values[widget_index + 1]
)
except (ValueError, TypeError):
strength = 1.0
break
if ref.get("strength") is not None:
strength = ref.get("strength")
# For text-based lora loaders (LoraLoaderV2, LoraManager), get strength from ref
if ref.get("is_lora_v2"):
strength = ref.get("strength")
model_name = ref.get("name", model_name)
# Check if model exists locally
exists = ref.get("exists", False)
# If URN, resolve to display name
if ref.get("is_urn"):
urn = ref.get("urn", {})
# Use model name from URN as display name
model_name = (
f"urn:{urn.get('type', 'model')}:{urn.get('model_id')}"
)
category = urn.get("type", category)
if category in URN_TYPE_MAP:
category = URN_TYPE_MAP[category]
loaded_models.append(
{
"name": model_name,
"category": category,
"node_id": node_id,
"widget_index": widget_index,
"node_type": node_type,
"exists": exists,
"strength": strength,
"original_path": original_path,
"is_urn": ref.get("is_urn", False),
"is_lora_v2": ref.get("is_lora_v2", False),
"active": ref.get("active"),
"connected": ref.get("connected", True),
"resolved_path": (
path_by_filename.get(model_name)
or path_by_filename.get(original_path)
),
}
)
# Also check node.properties.models for embedded models
total_nodes = len(nodes)
for node_index, node in enumerate(nodes, start=1):
if total_nodes and (
node_index == total_nodes or node_index % 50 == 0
):
update_loaded_progress(
"embedded",
"Checking embedded model metadata...",
percent=interpolate_percent(
94, 98, node_index, total_nodes
),
current=node_index,
total=total_nodes,
)
node_type = node.get("type", "")
properties = node.get("properties", {})
if not isinstance(properties, dict):
properties = {}
models_list = properties.get("models", [])
if not isinstance(models_list, list):
models_list = []
for model_info in models_list:
if isinstance(model_info, dict):
name = model_info.get("name", "")
directory = model_info.get("directory", "")
if name:
# Check if this model is already in loaded_models
existing = next(
(
model
for model in loaded_models
if model.get("original_path") == name
),
None,
)
if not existing:
loaded_models.append(
{
"name": get_filename_from_path(name),
"category": directory or "checkpoints",
"node_id": node.get("id"),
"widget_index": None,
"node_type": node_type,
"exists": True, # Embedded models are loaded
"strength": None,
"original_path": name,
"is_urn": False,
}
)
update_loaded_progress(
"finalizing",
"Loaded models ready",
percent=99,
current=len(loaded_models),
total=len(loaded_models),
)
return {
"loaded_models": loaded_models,
"total": len(loaded_models),
}
update_loaded_progress(
"starting",
"Preparing loaded model scan...",
percent=0,
status="starting",
current=0,
total=0,
)
try:
result = await asyncio.to_thread(build_loaded_models_response)
except Exception as e:
update_loaded_progress(
"error",
str(e),
percent=100,
status="error",
current=0,
total=0,
)
self.logger.error(
f"Model Resolver loaded models error: {e}", exc_info=True
)
return web.json_response({"error": str(e)}, status=500)
update_loaded_progress(
"completed",
"Loaded models ready",
percent=100,
status="completed",
current=result.get("total", 0),
total=result.get("total", 0),
)
return web.json_response(result)
@routes.get("/model_resolver/loaded-progress/{loaded_id}")
@json_api_endpoint("loaded-progress")
async def get_loaded_models_progress(request):
"""Get loaded models inspection progress."""
return get_progress_response(
self.loaded_progress,
request,
param_name="loaded_id",
not_found_payload={
"status": "unknown",
"stage": "unknown",
"message": "No loaded models progress available",
"percent": 0,
"current": 0,
"total": 0,
}
)
# ==================== MODEL METADATA LOOKUP ROUTE ====================
@routes.post("/model_resolver/civitai-search")
@json_api_endpoint("civitai-search")
async def civitai_search(request):
"""Fetch model metadata from trusted exact-match sources."""
data = await request.json()
filename = data.get("filename", "")
category = data.get("category", "")
resolved_path = data.get("resolved_path", "")
local_only = to_bool(data.get("local_only"), False)
force_refresh = to_bool(
data.get("force_refresh") or data.get("force"), False
)
provided_hash = normalize_sha256(
data.get("sha256")
or data.get("hash")
or data.get("file_hash")
or ""
)
hf_token = data.get("hf_token", "")
brave_search_api_key = data.get("brave_search_api_key", "")
hf_use_brave_fallback = to_bool(
data.get("hf_use_brave_fallback", True),
True,
)
if not filename:
return web.json_response(
{"error": "Filename is required"}, status=400
)
# Clean filename for display
import os as _os
clean_name = _os.path.splitext(filename)[0]
local_metadata_fields = (
"author",
"creator",
"license",
"usage_hint",
"usage_tips",
"preview_url",
"metadata_source",
"from_safetensors_header",
"local_metadata_available",
"header_metadata_keys",
"metadata_summary",
"base_model_raw",
"sha256_source",
"hashes",
"hash_status",
)
def add_local_metadata_fields(payload, result):
if not isinstance(payload, dict) or not isinstance(result, dict):
return payload
for key in local_metadata_fields:
value = result.get(key)
if value in (None, "", [], {}):
continue
payload[key] = value
return payload
# Get the file path to hash
file_path = resolved_path if resolved_path else None
file_location = ""
if not file_path:
file_path = find_local_file_path(filename, category)
if file_path and _os.path.exists(file_path):
file_location = _os.path.dirname(file_path).replace("\\", "/")
if file_location and not file_location.endswith("/"):
file_location += "/"
def infer_model_type_from_category(value):
return normalize_category_to_model_type(value)
def build_info_response(
result=None,
*,
metadata_path="",
metadata_saved=False,
civitai_checked=False,
local_payload=False,
):
result = result or {}
size_value = result.get("size")
if not size_value and file_path and _os.path.exists(file_path):
try:
size_value = _os.path.getsize(file_path)
except Exception:
size_value = None
model_type = (
result.get("model_type")
or result.get("type")
or infer_model_type_from_category(category)
)
response = {
"filename": result.get("filename") or filename,
"category": category,
"file_path": result.get("file_path") or file_path or "",
"resolved_path": result.get("resolved_path") or file_path or "",
"metadata_path": metadata_path
or result.get("metadata_path")
or "",
"metadata_saved": bool(metadata_saved),
"location": result.get("location") or file_location,
"source": result.get("source") or "",
"details_source": result.get("details_source")
or result.get("source")
or "",
"url": result.get("url"),
"version_url": result.get("version_url"),
"download_url": result.get("download_url"),
"platform_url": result.get("platform_url"),
"repo_id": result.get("repo_id"),
"path": result.get("path"),
"model_id": result.get("model_id"),
"model_name": result.get("model_name") or clean_name,
"model_type": model_type,
"version_id": result.get("version_id"),
"version_name": result.get("version_name", ""),
"sha256": result.get("sha256") or provided_hash,
"size": size_value,
"base_model": result.get("base_model"),
"base_model_source": result.get("base_model_source"),
"base_model_inferred": bool(result.get("base_model_inferred")),
"tags": result.get("tags", []),
"trained_words": result.get("trained_words", []),
"images": result.get("images", []),
"clip_skip": result.get("clip_skip"),
"description": result.get("description", ""),
"model_description": result.get("model_description", ""),
"from_metadata": bool(result.get("from_metadata")),
"local_only": bool(local_payload),
"metadata_checked": bool(civitai_checked),
"civitai_checked": bool(civitai_checked),
}
return add_local_metadata_fields(response, result)
def extract_result_sha256(result):
return extract_sha256_from_metadata(result)
def result_filename_matches(result):
if not isinstance(result, dict):
return False
expected = _os.path.basename(filename or "").lower()
candidates = [
result.get("filename"),
result.get("path"),
result.get("file_path"),
]
for candidate in candidates:
basename = _os.path.basename(str(candidate or "")).lower()
if basename and basename == expected:
return True
return False
def result_hash_matches(result, *, require_filename=False):
if not provided_hash or not isinstance(result, dict):
return False
result_hash = extract_result_sha256(result)
if result_hash != provided_hash:
return False
if require_filename and not result_filename_matches(result):
return False
return True
def huggingface_page_url(result):
try:
from urllib.parse import quote as _quote
except Exception:
_quote = None
repo_id = str(
result.get("repo_id") or result.get("repo") or ""
).strip()
hf_path = str(
result.get("path") or result.get("filename") or ""
).strip()
if not repo_id or not hf_path:
return ""
if _quote:
hf_path = _quote(hf_path.replace("\\", "/"), safe="/")
return f"https://huggingface.co/{repo_id}/blob/main/{hf_path}"
def prepare_remote_result(result, source_name):
result = dict(result or {})
source_name = str(source_name or result.get("source") or "").lower()
if source_name == "huggingface":
download_url = result.get("download_url") or result.get("url")
page_url = result.get("page_url") or huggingface_page_url(result)
if page_url:
result["url"] = page_url
result["version_url"] = page_url
result["download_url"] = download_url
result["model_name"] = (
result.get("model_name")
or result.get("name")
or result.get("repo_id")
or clean_name
)
result["model_type"] = (
result.get("model_type")
or infer_model_type_from_category(category)
)
else:
result["model_name"] = (
result.get("model_name")
or result.get("name")
or clean_name
)
if result.get("url") and not result.get("version_url"):
result["version_url"] = result.get("url")
result["source"] = source_name or result.get("source") or ""
result["details_source"] = (
result.get("details_source")
or source_name
or result.get("source")
or ""
)
result["file_path"] = file_path or result.get("file_path") or ""
result["resolved_path"] = (
file_path or result.get("resolved_path") or ""
)
result["location"] = result.get("location") or file_location
result["filename"] = result.get("filename") or filename
result["sha256"] = (
extract_result_sha256(result)
or provided_hash
or result.get("sha256")
)
if not result.get("size") and file_path and _os.path.exists(file_path):
try:
result["size"] = _os.path.getsize(file_path)
except Exception:
pass
return result
def result_has_remote_identity(result):
if not isinstance(result, dict):
return False
return bool(
result.get("url")
or result.get("version_url")
or result.get("download_url")
or result.get("platform_url")
or result.get("repo_id")
or result.get("model_id")
or result.get("version_id")
or result.get("from_metadata")
)
def remote_link_is_marked_dead(item):
if not isinstance(item, dict):
return False
status = str(item.get("status") or "").lower()
return bool(
item.get("deletedAt")
or item.get("deleted_at")
or item.get("is_dead")
or item.get("isDead")
or item.get("likelyDead")
or item.get("likely_dead")
or item.get("dead")
or status in {"dead", "deleted", "unavailable", "missing"}
)
def collect_result_download_urls(result):
urls = []
if remote_link_is_marked_dead(result):
return urls
expected_filename = result.get("filename") or filename
dead_urls = set()
mirrors = result.get("mirrors") or []
if not isinstance(mirrors, list):
mirrors = [mirrors]
for mirror in mirrors:
if not isinstance(mirror, dict):
continue
if remote_link_is_marked_dead(mirror):
dead_url = str(mirror.get("url") or "").strip()
if dead_url.startswith(("http://", "https://")):
dead_urls.add(dead_url)
continue
url = str(mirror.get("url") or "").strip()
mirror_filename = (
mirror.get("filename")
or mirror.get("name")
or expected_filename
)
if (
looks_like_model_file(url, mirror_filename)
and url not in urls
):
urls.append(url)
raw_urls = result.get("download_urls") or []
if not isinstance(raw_urls, list):
raw_urls = [raw_urls]
for raw_url in raw_urls:
url = str(raw_url or "").strip()
if (
looks_like_model_file(url, expected_filename)
and url not in dead_urls
and url not in urls
):
urls.append(url)
for key in ("download_url", "downloadUrl"):
url = str(result.get(key) or "").strip()
if (
looks_like_model_file(url, expected_filename)
and url not in dead_urls
and url not in urls
):
urls.append(url)
return urls
def remote_download_url_is_alive(url):
try:
import requests
except Exception:
return True
headers = {
"User-Agent": "ComfyUI-Model-Resolver/1.0",
"Accept": "*/*",
}
try:
response = requests.head(
url,
headers=headers,
allow_redirects=True,
timeout=8,
)
try:
if response.status_code < 400:
return True
if response.status_code in {401, 403, 404, 410}:
return False
finally:
response.close()
except Exception:
pass
try:
response = requests.get(
url,
headers={**headers, "Range": "bytes=0-0"},
allow_redirects=True,
stream=True,
timeout=8,
)
try:
return response.status_code < 400
finally:
response.close()
except Exception:
return False
def civarchive_result_has_live_download(result):
urls = collect_result_download_urls(result)
if not urls:
return False
for url in urls[:3]:
if remote_download_url_is_alive(url):
result["download_url"] = url
result["download_urls"] = [
url,
*[other for other in urls if other != url],
]
return True
return False
def save_remote_metadata(result, source_name):
metadata_path = result.get("metadata_path") or ""
metadata_saved = False
if (
result.get("from_metadata")
or not file_path
or not _os.path.exists(file_path)
):
return metadata_path, metadata_saved
try:
metadata_payload = {
"source": source_name,
"details_source": result.get("details_source")
or source_name,
"filename": filename,
"category": category,
"model_name": result.get("model_name", clean_name),
"name": result.get("model_name", clean_name),
"model_type": result.get("model_type", "")
or result.get("type", ""),
"type": result.get("model_type", "")
or result.get("type", ""),
"model_id": result.get("model_id"),
"version_id": result.get("version_id"),
"version_name": result.get("version_name", ""),
"sha256": result.get("sha256") or provided_hash,
"size": result.get("size"),
"base_model": result.get("base_model"),
"base_model_source": result.get("base_model_source"),
"base_model_inferred": bool(result.get("base_model_inferred")),
"tags": result.get("tags", []),
"trained_words": result.get("trained_words", []),
"images": result.get("images", []),
"clip_skip": result.get("clip_skip"),
"description": result.get("description", ""),
"model_description": result.get("model_description", ""),
"download_url": result.get("download_url"),
"source_url": result.get("version_url") or result.get("url"),
"version_url": result.get("version_url") or result.get("url"),
"model_url": result.get("url"),
"url": result.get("version_url") or result.get("url"),
"platform_url": result.get("platform_url"),
"repo_id": result.get("repo_id"),
"path": result.get("path"),
"path_metadata": {
"filename": filename,
"category": category,
"source": source_name,
"model_id": result.get("model_id"),
"version_id": result.get("version_id"),
"repo_id": result.get("repo_id"),
"path": result.get("path"),
},
}
add_local_metadata_fields(metadata_payload, result)
metadata_path = write_lora_manager_metadata(
file_path,
metadata_payload,
category,
result.get("version_url")
or result.get("url")
or result.get("platform_url")
or result.get("download_url")
or "",
) or ""
metadata_saved = bool(metadata_path)
if metadata_path:
result["metadata_path"] = metadata_path
except Exception as metadata_error:
self.logger.warning(
f"{source_name} metadata sidecar save failed: {metadata_error}"
)
return metadata_path, metadata_saved
if local_only:
result = None
metadata_path = ""
metadata_saved = False
if download_available and file_path and _os.path.exists(file_path):
try:
from .core.sources.civitai import (
get_model_info_for_file,
)
result = get_model_info_for_file(
file_path,
local_only=True,
)
source_metadata_path = (
result.get("metadata_path")
if isinstance(result, dict)
else ""
)
canonical_metadata_path = get_metadata_sidecar_path(file_path)
if (
isinstance(result, dict)
and result.get("from_metadata")
and source_metadata_path
and canonical_metadata_path
and _os.path.abspath(source_metadata_path)
!= _os.path.abspath(canonical_metadata_path)
and not _os.path.exists(canonical_metadata_path)
):
preview_url = result.get("preview_url") or ""
if not preview_url:
model_base_path, _model_ext = _os.path.splitext(file_path)
for preview_ext in (
".preview.png",
".preview.jpg",
".preview.jpeg",
".preview.webp",
):
preview_path = f"{model_base_path}{preview_ext}"
if _os.path.exists(preview_path):
preview_url = preview_path.replace("\\", "/")
break
metadata_payload = {
"source": "metadata_import",
"details_source": result.get("source") or "metadata",
"filename": filename,
"category": category,
"model_name": result.get("model_name", clean_name),
"name": result.get("model_name", clean_name),
"model_type": result.get("model_type", ""),
"type": result.get("model_type", ""),
"model_id": result.get("model_id"),
"version_id": result.get("version_id"),
"version_name": result.get("version_name", ""),
"sha256": result.get("sha256"),
"size": result.get("size"),
"base_model": result.get("base_model"),
"base_model_source": result.get("base_model_source"),
"base_model_inferred": bool(result.get("base_model_inferred")),
"tags": result.get("tags", []),
"trained_words": result.get("trained_words", []),
"images": result.get("images", []),
"clip_skip": result.get("clip_skip"),
"description": result.get("description", ""),
"model_description": result.get("model_description", ""),
"download_url": result.get("download_url"),
"preview_url": preview_url,
"source_url": result.get("version_url")
or result.get("url"),
"version_url": result.get("version_url")
or result.get("url"),
"model_url": result.get("url"),
"url": result.get("version_url") or result.get("url"),
"path_metadata": {
"filename": filename,
"category": category,
"source": "metadata_import",
"model_id": result.get("model_id"),
"version_id": result.get("version_id"),
"imported_from": source_metadata_path,
},
}
add_local_metadata_fields(metadata_payload, result)
metadata_path = write_lora_manager_metadata(
file_path,
metadata_payload,
category,
result.get("version_url")
or result.get("url")
or result.get("download_url")
or "",
) or ""
metadata_saved = bool(metadata_path)
if metadata_path:
result["metadata_path"] = metadata_path
result["metadata_imported_from"] = source_metadata_path
except Exception as e:
self.logger.warning(f"Local model info error: {e}")
return web.json_response(
build_info_response(
result,
metadata_path=metadata_path,
metadata_saved=metadata_saved,
local_payload=True,
civitai_checked=False,
)
)
# Search remote metadata. CivitAI and CivArchive are hash-only;
# HuggingFace name results must still confirm the exact SHA.
if download_available and file_path and _os.path.exists(file_path):
try:
from .core.sources.civitai import (
get_model_info_by_hash,
get_model_info_for_file,
)
if provided_hash:
result = get_model_info_by_hash(
provided_hash,
use_cache=not force_refresh,
)
if result:
result["file_path"] = file_path
result["resolved_path"] = file_path
result["location"] = file_location
if not result.get("size"):
try:
result["size"] = _os.path.getsize(file_path)
except Exception:
pass
if not extract_result_sha256(result):
result["sha256"] = provided_hash
elif not force_refresh:
result = get_model_info_for_file(file_path)
else:
result = None
if result and (
result.get("url")
or result.get("version_url")
or result.get("from_metadata")
or result.get("trained_words")
or result.get("base_model_inferred")
or result.get("local_metadata_available")
or result.get("from_safetensors_header")
) and (
result.get("from_metadata")
or not provided_hash
or result_hash_matches(result)
):
result_source = (
"local"
if result.get("source") == "local"
and not result_has_remote_identity(result)
else "civitai"
)
result = prepare_remote_result(result, result_source)
metadata_path, metadata_saved = save_remote_metadata(
result,
result_source,
)
return web.json_response(
build_info_response(
result,
metadata_path=metadata_path,
metadata_saved=metadata_saved,
civitai_checked=True,
)
)
except Exception as e:
self.logger.warning(f"CivitAI search error: {e}")
if provided_hash:
try:
result = resolve_civarchive_by_hash(
provided_hash,
query=filename,
exact_only=False,
model_type=infer_model_type_from_category(category),
)
if result:
if not extract_result_sha256(result):
result["sha256"] = provided_hash
result = prepare_remote_result(result, "civarchive")
if result_hash_matches(result) and civarchive_result_has_live_download(result):
metadata_path, metadata_saved = save_remote_metadata(
result,
"civarchive",
)
return web.json_response(
build_info_response(
result,
metadata_path=metadata_path,
metadata_saved=metadata_saved,
civitai_checked=True,
)
)
if result_hash_matches(result):
self.logger.info(
f"CivArchive metadata candidate rejected: "
f"no live download link for {filename}"
)
except Exception as e:
self.logger.warning(f"CivArchive hash lookup error: {e}")
if provided_hash:
hf_attempts = [
{
"label": "HuggingFace",
"use_api_search": True,
"use_comfy_org_fallback": True,
"use_brave_fallback": False,
}
]
if hf_use_brave_fallback and brave_search_api_key:
hf_attempts.append(
{
"label": "HuggingFace Brave",
"use_api_search": False,
"use_comfy_org_fallback": False,
"use_brave_fallback": True,
}
)
for hf_attempt in hf_attempts:
try:
result = search_huggingface_for_file(
filename,
token=hf_token or None,
exact_only=True,
brave_api_key=brave_search_api_key or None,
use_api_search=hf_attempt["use_api_search"],
use_comfy_org_fallback=hf_attempt[
"use_comfy_org_fallback"
],
use_brave_fallback=hf_attempt[
"use_brave_fallback"
],
force_refresh=force_refresh,
)
if result and result_hash_matches(
result,
require_filename=True,
):
result = prepare_remote_result(
result,
"huggingface",
)
metadata_path, metadata_saved = save_remote_metadata(
result,
"huggingface",
)
return web.json_response(
build_info_response(
result,
metadata_path=metadata_path,
metadata_saved=metadata_saved,
civitai_checked=True,
)
)
if result:
self.logger.info(
f"{hf_attempt['label']} metadata candidate rejected: "
f"filename/hash mismatch for {filename}"
)
except Exception as e:
self.logger.warning(
f"{hf_attempt['label']} metadata lookup error: {e}"
)
# No remote result found. Keep any useful local safetensors
# header metadata, including base-model fingerprints, model
# titles, descriptions, tags, trigger words, and author data.
local_fallback_result = None
if file_path and _os.path.exists(file_path):
try:
from .core.sources.civitai import get_model_info_for_file
local_candidate = get_model_info_for_file(
file_path,
local_only=True,
)
if (
isinstance(local_candidate, dict)
and (
local_candidate.get("base_model")
or local_candidate.get("local_metadata_available")
or local_candidate.get("from_safetensors_header")
)
):
local_fallback_result = local_candidate
except Exception as local_fallback_error:
self.logger.debug(
f"Local base model inference fallback failed: {local_fallback_error}"
)
response = build_info_response(
local_fallback_result,
civitai_checked=True,
local_payload=bool(local_fallback_result),
)
response["url"] = None
if force_refresh and file_path and _os.path.exists(file_path):
try:
metadata_payload = {
"filename": filename,
"category": category,
"model_name": response.get("model_name") or clean_name,
"name": response.get("model_name") or clean_name,
"model_type": response.get("model_type")
or infer_model_type_from_category(category),
"sha256": response.get("sha256") or provided_hash,
"size": response.get("size") or _os.path.getsize(file_path),
"base_model": response.get("base_model"),
"base_model_source": response.get("base_model_source"),
"base_model_inferred": bool(response.get("base_model_inferred")),
"civitai_deleted": True,
"civitai_checked": True,
"remote_metadata_missing": True,
"source": "local",
"details_source": response.get("details_source") or "",
}
add_local_metadata_fields(metadata_payload, response)
metadata_path = write_lora_manager_metadata(
file_path,
metadata_payload,
category,
"",
) or ""
response["metadata_path"] = metadata_path
response["metadata_saved"] = bool(metadata_path)
except Exception as metadata_error:
self.logger.warning(
f"Remote metadata no-match sidecar save failed: {metadata_error}"
)
return web.json_response(response)
def _select_custom_url_file(files, expected_filename=""):
"""Pick the most likely downloadable model file from provider details."""
if not isinstance(files, list):
files = [files] if files else []
candidates = [item for item in files if isinstance(item, dict)]
if not candidates:
return {}
expected = os.path.basename(str(expected_filename or "")).lower()
def file_name(file_info):
return str(
file_info.get("name")
or file_info.get("filename")
or file_info.get("path")
or ""
).strip()
def has_download(file_info):
return bool(
file_info.get("download_url")
or file_info.get("downloadUrl")
or file_info.get("url")
)
if expected:
for file_info in candidates:
if os.path.basename(file_name(file_info)).lower() == expected:
return file_info
for file_info in candidates:
if file_info.get("primary") and has_download(file_info):
return file_info
for file_info in candidates:
if str(file_info.get("type") or "").lower() == "model" and has_download(file_info):
return file_info
for file_info in candidates:
if has_download(file_info):
return file_info
return candidates[0]
def _custom_result_timestamp():
return time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
def _quote_url_path(value):
from urllib.parse import quote as _quote
return _quote(str(value or "").replace("\\", "/"), safe="/")
def _build_civitai_custom_result(details, expected_filename="", api_key=None):
if not isinstance(details, dict):
return None
selected_version = (
details.get("selected_version")
if isinstance(details.get("selected_version"), dict)
else {}
)
version_id = details.get("version_id") or selected_version.get("id")
model_id = details.get("model_id")
file_info = _select_custom_url_file(
selected_version.get("files") or [],
expected_filename,
)
filename = (
file_info.get("name")
or file_info.get("filename")
or os.path.basename(str(expected_filename or ""))
or details.get("name")
or f"civitai-{version_id or model_id}"
)
download_url = (
file_info.get("download_url")
or file_info.get("downloadUrl")
or (get_civitai_download_url(version_id, api_key) if version_id else "")
)
if not download_url:
return None
hashes = (
file_info.get("hashes")
if isinstance(file_info.get("hashes"), dict)
else {}
)
sha256 = (
file_info.get("sha256")
or file_info.get("hash")
or hashes.get("SHA256")
or hashes.get("sha256")
)
version_url = (
details.get("version_url")
or selected_version.get("url")
or (
f"https://civitai.com/models/{model_id}?modelVersionId={version_id}"
if model_id and version_id
else details.get("url")
)
)
return {
"source": "civitai",
"details_source": "civitai",
"model_id": model_id,
"version_id": version_id,
"name": details.get("name") or filename,
"version_name": selected_version.get("name") or "",
"type": details.get("type") or file_info.get("type") or "",
"filename": filename,
"url": version_url or details.get("url"),
"version_url": version_url or details.get("url"),
"download_url": download_url,
"size": file_info.get("size"),
"base_model": selected_version.get("base_model"),
"tags": details.get("tags") or [],
"trained_words": selected_version.get("trained_words") or [],
"images": details.get("images") or selected_version.get("images") or [],
"description": selected_version.get("description")
or details.get("description")
or "",
"model_description": details.get("description") or "",
"sha256": sha256,
"hashes": hashes,
"match_type": "custom_url",
"custom_url": True,
}
def _resolve_civitai_version_custom_result(version_id, expected_filename="", api_key=None):
try:
import requests
except Exception:
requests = None
if not requests or not version_id:
return None
headers = {}
if api_key:
headers["Authorization"] = f"Bearer {api_key}"
try:
response = requests.get(
f"https://civitai.com/api/v1/model-versions/{version_id}",
headers=headers,
timeout=20,
)
try:
if response.status_code != 200:
return None
data = response.json()
finally:
response.close()
except Exception as e:
self.logger.warning(
f"CivitAI custom URL version lookup failed: version_id={version_id}, error={e}"
)
return None
model_block = data.get("model") if isinstance(data.get("model"), dict) else {}
model_id = data.get("modelId") or data.get("model_id") or model_block.get("id")
if model_id:
try:
details = get_civitai_model_details(model_id, version_id, api_key)
result = _build_civitai_custom_result(
details,
expected_filename=expected_filename,
api_key=api_key,
)
if result:
return result
except Exception as e:
self.logger.warning(
f"CivitAI custom URL details lookup failed: model_id={model_id}, version_id={version_id}, error={e}"
)
file_info = _select_custom_url_file(data.get("files") or [], expected_filename)
hashes = (
file_info.get("hashes")
if isinstance(file_info.get("hashes"), dict)
else {}
)
sha256 = (
file_info.get("sha256")
or file_info.get("hash")
or hashes.get("SHA256")
or hashes.get("sha256")
)
filename = (
file_info.get("name")
or file_info.get("filename")
or os.path.basename(str(expected_filename or ""))
or f"civitai-{version_id}"
)
download_url = (
file_info.get("downloadUrl")
or file_info.get("download_url")
or get_civitai_download_url(version_id, api_key)
)
model_url = (
f"https://civitai.com/models/{model_id}?modelVersionId={version_id}"
if model_id
else f"https://civitai.com/api/download/models/{version_id}"
)
return {
"source": "civitai",
"details_source": "civitai",
"model_id": model_id,
"version_id": version_id,
"name": model_block.get("name") or data.get("modelName") or filename,
"version_name": data.get("name") or "",
"type": model_block.get("type") or data.get("modelType") or file_info.get("type") or "",
"filename": filename,
"url": model_url,
"version_url": model_url,
"download_url": download_url,
"size": file_info.get("size")
or ((file_info.get("sizeKB") or 0) * 1024 if file_info.get("sizeKB") else None),
"base_model": data.get("baseModel"),
"tags": model_block.get("tags") or [],
"trained_words": data.get("trainedWords") or data.get("trained_words") or [],
"images": data.get("images") or [],
"description": data.get("description") or "",
"sha256": sha256,
"hashes": hashes,
"match_type": "custom_url",
"custom_url": True,
}
def _build_civarchive_custom_result(details, expected_filename=""):
if not isinstance(details, dict):
return None
selected_version = (
details.get("selected_version")
if isinstance(details.get("selected_version"), dict)
else {}
)
file_info = _select_custom_url_file(
selected_version.get("files") or [],
expected_filename,
)
download_urls = file_info.get("download_urls") or []
if not isinstance(download_urls, list):
download_urls = [download_urls]
download_url = (
file_info.get("download_url")
or file_info.get("downloadUrl")
or (download_urls[0] if download_urls else "")
)
if not download_url:
return None
filename = (
file_info.get("name")
or file_info.get("filename")
or os.path.basename(str(expected_filename or ""))
or details.get("name")
or "model"
)
hashes = (
file_info.get("hashes")
if isinstance(file_info.get("hashes"), dict)
else {}
)
sha256 = (
file_info.get("sha256")
or file_info.get("hash")
or hashes.get("SHA256")
or hashes.get("sha256")
)
version_id = details.get("version_id") or selected_version.get("id")
model_id = details.get("model_id")
version_url = (
details.get("version_url")
or selected_version.get("url")
or (
f"https://civarchive.com/models/{model_id}?modelVersionId={version_id}"
if model_id and version_id
else details.get("url")
)
)
return {
"source": "civarchive",
"details_source": "civarchive",
"model_id": model_id,
"version_id": version_id,
"name": details.get("name") or filename,
"version_name": selected_version.get("name") or "",
"type": details.get("type") or file_info.get("type") or "",
"filename": filename,
"url": version_url or details.get("url"),
"version_url": version_url or details.get("url"),
"platform_url": details.get("platform_url")
or selected_version.get("platform_url"),
"download_url": download_url,
"download_urls": [url for url in download_urls if url],
"size": file_info.get("size"),
"base_model": selected_version.get("base_model"),
"tags": details.get("tags") or [],
"trained_words": selected_version.get("trained_words") or [],
"images": details.get("images") or selected_version.get("images") or [],
"description": selected_version.get("description")
or details.get("description")
or "",
"sha256": sha256,
"hash": sha256,
"hashes": hashes,
"platform": details.get("platform"),
"match_type": "custom_url",
"custom_url": True,
}
def _build_huggingface_custom_result(url, expected_filename="", token=None):
from urllib.parse import unquote
parsed = parse_huggingface_url(url)
if not parsed:
return None
repo_id = parsed.get("repo") or ""
branch = parsed.get("branch") or "main"
file_path = unquote(parsed.get("filename") or "")
if not repo_id or not file_path:
return None
filename = os.path.basename(file_path.replace("\\", "/"))
download_url = get_huggingface_download_url(repo_id, file_path, branch)
if not looks_like_model_file(download_url, expected_filename or filename):
return None
headers = {}
if token:
headers["Authorization"] = f"Bearer {token}"
size = fetch_remote_file_size_cached(
download_url,
headers=headers,
timeout=10,
)
page_url = (
f"https://huggingface.co/{repo_id}/blob/{branch}/{_quote_url_path(file_path)}"
)
return {
"source": "huggingface",
"details_source": "huggingface",
"repo_id": repo_id,
"repo": repo_id,
"path": file_path,
"filename": filename,
"name": repo_id,
"url": download_url,
"download_url": download_url,
"page_url": page_url,
"version_url": page_url,
"size": size,
"match_type": "custom_url",
"custom_url": True,
}
def _build_direct_custom_download_result(url, source, expected_filename=""):
from urllib.parse import urlparse
if not looks_like_model_file(url, expected_filename):
return None
parsed = urlparse(url)
filename = (
os.path.basename(parsed.path)
or os.path.basename(str(expected_filename or ""))
or "model"
)
if expected_filename and "." in os.path.basename(str(expected_filename)):
filename = os.path.basename(str(expected_filename))
source = str(source or "custom").strip().lower()
source_label = {
"civarchive": "CivArchive",
"civitai": "CivitAI",
"huggingface": "HuggingFace",
}.get(source, "Custom URL")
return {
"source": source,
"details_source": source,
"name": source_label,
"filename": filename,
"url": url,
"version_url": url,
"download_url": url,
"match_type": "custom_url",
"custom_url": True,
}
def _collect_custom_url_local_hash_matches(result, category):
source_key = str(result.get("source") or "custom").strip().lower()
sha256 = normalize_sha256(extract_sha256_from_metadata(result))
if not sha256:
return []
try:
matches = search_local_matches_by_hash(
sha256,
category=category or None,
max_matches=20,
)
except Exception as hash_error:
self.logger.warning(
f"Custom URL local metadata hash lookup failed for {source_key}:{sha256}: {hash_error}"
)
return []
return [
{
**match,
"hash_lookup_source": source_key,
"hash_lookup_filename": result.get("filename")
or result.get("path")
or "",
"hash_lookup_sha256": sha256,
}
for match in matches
]
@routes.post("/model_resolver/custom-url")
@json_api_endpoint("custom-url")
async def custom_url(request):
"""Resolve a user-provided provider URL into a normal search result."""
data = await request.json()
raw_url = str(data.get("url") or data.get("custom_url") or "").strip()
if not raw_url:
return web.json_response(
{"error": "URL is required"}, status=400
)
if raw_url.startswith("hf://"):
normalized_url = raw_url
else:
from urllib.parse import urlparse
parsed_input = urlparse(raw_url)
if parsed_input.scheme not in {"http", "https"}:
return web.json_response(
{"error": "Only http, https, and hf:// URLs are supported"},
status=400,
)
normalized_url = raw_url
category = data.get("category") or ""
expected_filename = (
data.get("filename")
or get_filename_from_path(data.get("original_path") or "")
or ""
)
civitai_key = data.get("civitai_key", "")
hf_token = data.get("hf_token", "")
result = None
source = ""
try:
civitai_parsed = parse_civitai_url(normalized_url)
except Exception:
civitai_parsed = None
try:
civarchive_parsed = parse_civarchive_url(normalized_url)
except Exception:
civarchive_parsed = None
if civitai_parsed:
source = "civitai"
model_id = civitai_parsed.get("model_id")
version_id = civitai_parsed.get("version_id")
if model_id:
details = await asyncio.to_thread(
get_civitai_model_details,
model_id,
version_id,
civitai_key or None,
)
result = _build_civitai_custom_result(
details,
expected_filename=expected_filename,
api_key=civitai_key or None,
)
elif version_id:
result = await asyncio.to_thread(
_resolve_civitai_version_custom_result,
version_id,
expected_filename,
civitai_key or None,
)
if not result and version_id:
result = {
"source": "civitai",
"details_source": "civitai",
"version_id": version_id,
"name": expected_filename or f"CivitAI version {version_id}",
"filename": expected_filename or f"civitai-{version_id}",
"url": normalized_url,
"version_url": normalized_url,
"download_url": get_civitai_download_url(
version_id,
civitai_key or None,
),
"match_type": "custom_url",
"custom_url": True,
}
elif civarchive_parsed:
source = "civarchive"
if civarchive_parsed.get("sha256"):
result = await asyncio.to_thread(
resolve_civarchive_by_hash,
civarchive_parsed.get("sha256"),
expected_filename,
False,
normalize_category_to_model_type(category),
)
else:
model_id = civarchive_parsed.get("model_id")
version_id = civarchive_parsed.get("version_id")
if model_id:
result = await asyncio.to_thread(
resolve_civarchive_model_version,
model_id,
version_id,
expected_filename or str(model_id),
False,
True,
)
if not result:
details = await asyncio.to_thread(
get_civarchive_model_details,
model_id,
version_id,
True,
)
result = _build_civarchive_custom_result(
details,
expected_filename=expected_filename,
)
if result:
result = dict(result)
result["source"] = "civarchive"
result["details_source"] = "civarchive"
result["match_type"] = "custom_url"
result["custom_url"] = True
else:
from urllib.parse import urlparse
parsed_direct = urlparse(normalized_url)
direct_host = parsed_direct.netloc.lower()
if (
direct_host.endswith("civarchive.com")
and "/api/download/" in parsed_direct.path
):
source = "civarchive"
result = _build_direct_custom_download_result(
normalized_url,
"civarchive",
expected_filename,
)
else:
result = await asyncio.to_thread(
_build_huggingface_custom_result,
normalized_url,
expected_filename,
hf_token or None,
)
if result:
source = "huggingface"
if not result:
return web.json_response(
{
"error": (
"Unsupported or unresolved URL. Use a HuggingFace file URL, "
"CivitAI model/download URL, or CivArchive model/hash URL."
)
},
status=400,
)
result = dict(result)
result["provided_url"] = normalized_url
result["url_source"] = "custom"
result["searched_at"] = result.get("searched_at") or _custom_result_timestamp()
result.setdefault("category", category)
if expected_filename and not result.get("filename"):
result["filename"] = expected_filename
if not (result.get("download_url") or result.get("url")):
return web.json_response(
{"error": "The URL resolved, but no download URL was found"},
status=400,
)
source = source or result.get("source") or "custom"
local_hash_matches = _collect_custom_url_local_hash_matches(
result,
category,
)
response = {
"success": True,
"source": source,
"result": result,
"custom": [result],
"searched_sources": ["custom"],
"local_hash_matches": local_hash_matches,
}
response[source] = result
return web.json_response(response)
@routes.post("/model_resolver/model-details")
@json_api_endpoint("model-details")
async def model_details(request):
"""Return normalized full model details for sources that expose model pages."""
data = await request.json()
source = str(data.get("source", "")).strip().lower()
model_id = data.get("model_id")
version_id = data.get("version_id")
civitai_key = data.get("civitai_key", "")
if not download_available:
return web.json_response(
{"error": "Download providers are not available"}, status=503
)
try:
model_id = (
int(model_id)
if model_id is not None and str(model_id).strip()
else None
)
except (TypeError, ValueError):
model_id = None
try:
version_id = (
int(version_id)
if version_id is not None and str(version_id).strip()
else None
)
except (TypeError, ValueError):
version_id = None
if source == "lora_manager_archive":
source = "civitai"
if source not in {"civitai", "civarchive"}:
return web.json_response(
{"error": "Unsupported model details source"}, status=400
)
if not model_id:
return web.json_response(
{"error": "model_id is required"}, status=400
)
if source == "civitai":
details = await asyncio.to_thread(
get_civitai_model_details,
model_id,
version_id,
civitai_key or None,
)
else:
details = await asyncio.to_thread(
get_civarchive_model_details,
model_id,
version_id,
)
if not details:
return web.json_response(
{"error": "Model details not found"}, status=404
)
return web.json_response(details)
# ==================== DOWNLOAD ROUTES ====================
if download_available:
from .core.path_utils import (
get_path_abs as get_local_path_abs,
get_path_key as get_local_path_key,
get_path_identity as get_local_path_identity,
get_comfy_root_path,
is_path_within as is_local_path_within,
prefer_local_base_directory,
dedupe_local_base_directories,
)
# cleanup_search_progress, is_search_progress_cancelled, mark_search_progress_cancelled, and update_search_progress removed
@routes.get("/model_resolver/search-progress/{progress_id}")
@json_api_endpoint("search-progress")
async def get_search_progress_route(request):
"""Return live progress for an in-flight source search."""
return get_progress_response(
self.search_tracker,
request,
not_found_payload={"exists": False},
found_wrapper=lambda prog: {"exists": True, **prog}
)
@routes.post("/model_resolver/search-cancel/{progress_id}")
@json_api_endpoint("search-cancel", return_success_on_error=True)
async def cancel_search_progress_route(request):
"""Mark an in-flight source search as cancelled."""
return cancel_progress_response(
self.search_tracker,
request,
cancel_message="Cancelled"
)
@routes.post("/model_resolver/search")
async def search_sources(request):
"""Search for model download sources."""
try:
class SearchCancelled(BaseException):
# Progress helpers swallow ordinary callback errors; cancellation
# must bubble out of source loops and stop follow-up requests.
pass
def raise_if_search_cancelled(source=""):
if self.search_tracker.is_cancelled(progress_id):
raise SearchCancelled("Search cancelled")
def format_log_value(value):
if value is None or value == "":
return None
if isinstance(value, bool):
return "yes" if value else "no"
if isinstance(value, (list, tuple, set)):
return ",".join(str(item) for item in value)
text = str(value)
if any(char.isspace() for char in text):
return '"' + text.replace("\\", "\\\\").replace('"', '\\"') + '"'
return text
def format_log_size(value):
return format_size_bytes(value, include_space=False)
def format_log_fields(**fields):
parts = []
for key, value in fields.items():
formatted = format_log_value(value)
if formatted is not None:
parts.append(f"{key}={formatted}")
return " ".join(parts)
def normalize_result_extra(extra):
if not extra:
return {}
normalized = dict(extra)
model_id = normalized.pop("model_id", None)
version_id = normalized.pop("version_id", None)
if model_id or version_id:
normalized["ids"] = (
f"{model_id}@{version_id}"
if model_id and version_id
else model_id or version_id
)
if "files_count" in normalized:
normalized["files"] = normalized.pop("files_count")
return normalized
def format_result_details(result, extra=None):
if isinstance(result, list):
return format_log_fields(count=len(result))
if not isinstance(result, dict):
fields = {"result": "none" if result is None else result}
fields.update(normalize_result_extra(extra))
return format_log_fields(**fields)
model_id = result.get("model_id")
version_id = result.get("version_id")
ids = (
f"{model_id}@{version_id}"
if model_id and version_id
else model_id or version_id
)
fields = {
"name": result.get("name"),
"file": result.get("filename") or result.get("path"),
"match": result.get("match_type"),
"repo": result.get("repo_id") or result.get("repo"),
"ids": ids,
"size": format_log_size(result.get("size")),
"files": result.get("files_count"),
}
fields.update(normalize_result_extra(extra))
return format_log_fields(**fields)
def log_search_result(source_name, result, extra=None):
details = format_result_details(result, extra)
if result and (
not isinstance(result, list) or len(result) > 0
):
self.logger.info(f"Search [{source_name}] found {details}")
else:
self.logger.info(f"Search [{source_name}] miss {details}")
data = await request.json()
filename = data.get("filename", "")
category = data.get("category", "")
base_model_context = data.get("base_model_context", "")
progress_id = str(data.get("progress_id") or "").strip()
progress_source = str(data.get("progress_source") or "").strip()
civitai_candidate_limit = to_int(data.get("civitai_candidate_limit"), 5)
civitai_candidate_limit = max(
1, min(civitai_candidate_limit, 20)
)
civarchive_candidate_limit = to_int(data.get("civarchive_candidate_limit"), 10)
civarchive_candidate_limit = max(
1, min(civarchive_candidate_limit, 30)
)
# Handle both boolean and string forms
is_urn_raw = data.get("is_urn", False)
civitai_key = data.get("civitai_key", "")
civitai_session_token = data.get("civitai_session_token", "")
hf_token = data.get("hf_token", "")
brave_search_api_key = data.get("brave_search_api_key", "")
civitai_use_trpc_search = data.get(
"civitai_use_trpc_search", True
)
civitai_use_api_search = data.get(
"civitai_use_api_search", True
)
civitai_use_html_fallback = data.get(
"civitai_use_html_fallback", True
)
hf_use_api_search = data.get("hf_use_api_search", True)
hf_use_comfy_org_fallback = data.get(
"hf_use_comfy_org_fallback", True
)
hf_use_brave_fallback = data.get(
"hf_use_brave_fallback", True
)
is_urn = to_bool(is_urn_raw, False)
hf_use_api_search = to_bool(hf_use_api_search, True)
civitai_use_trpc_search = to_bool(civitai_use_trpc_search, True)
civitai_use_api_search = to_bool(civitai_use_api_search, True)
civitai_use_html_fallback = to_bool(civitai_use_html_fallback, True)
hf_use_comfy_org_fallback = to_bool(hf_use_comfy_org_fallback, True)
hf_use_brave_fallback = to_bool(hf_use_brave_fallback, True)
# For URN-only requests, model_id and version_id are required instead of filename
model_id = data.get("model_id")
version_id = data.get("version_id")
if not filename and not (is_urn and model_id and version_id):
return web.json_response(
{
"error": "Filename is required for non-URN, or model_id+version_id for URN"
},
status=400,
)
raw_sources = data.get("sources", ["all"])
if isinstance(raw_sources, str):
raw_sources = [raw_sources]
elif not isinstance(raw_sources, list):
raw_sources = ["all"]
normalized_sources = {
str(source).strip().lower()
for source in raw_sources
if str(source).strip()
}
if not normalized_sources:
normalized_sources = {"all"}
if "all" in normalized_sources:
normalized_sources = {
"local",
"huggingface",
"civitai",
"civarchive",
"lora_manager_archive",
}
search_local = "local" in normalized_sources
search_huggingface_source = "huggingface" in normalized_sources
search_civitai_source = "civitai" in normalized_sources
search_civarchive_source = "civarchive" in normalized_sources
search_lora_manager_archive_source = (
"lora_manager_archive" in normalized_sources
)
if not progress_source:
progress_source = (
next(iter(normalized_sources))
if len(normalized_sources) == 1
else "all"
)
force_search = to_bool(data.get("force_search"), False)
self.search_tracker.update(
progress_id,
progress_source,
"starting",
"Preparing search",
8,
)
raise_if_search_cancelled(progress_source)
if force_search:
self.search_tracker.update(
progress_id,
progress_source,
"cache",
"Refreshing search caches",
12,
)
if search_local:
reload_popular_databases()
reload_model_list()
if search_huggingface_source:
clear_huggingface_search_cache()
if search_civitai_source:
clear_civitai_search_cache()
if search_civarchive_source:
clear_civarchive_search_cache()
if search_lora_manager_archive_source:
clear_lora_manager_archive_search_cache()
self.logger.debug(
"Force search enabled: cleared cache "
+ format_log_fields(sources=sorted(normalized_sources))
)
raise_if_search_cancelled(progress_source)
self.logger.info(
f"Search [{','.join(sorted(normalized_sources))}] request "
+ format_log_fields(
file=filename,
cat=category,
urn=is_urn,
ids=(
f"{data.get('model_id')}@{data.get('version_id')}"
if data.get("model_id") and data.get("version_id")
else data.get("model_id")
or data.get("version_id")
),
base=base_model_context,
force=force_search,
)
)
results = {
"popular": None,
"model_list": None,
"huggingface": None,
"civitai": None,
"civarchive": None,
"lora_manager_archive": None,
"local_hash_matches": [],
"found": False,
"searched_sources": sorted(normalized_sources),
"source_errors": {},
}
def current_search_timestamp():
from datetime import datetime, timezone
return (
datetime.now(timezone.utc)
.replace(microsecond=0)
.isoformat()
)
def get_search_result_signature(source_key, result):
if isinstance(result, list):
return "|".join(
get_search_result_signature(source_key, item)
for item in result
)
if not isinstance(result, dict):
return ""
parts = [
source_key,
result.get("download_url")
or result.get("url")
or result.get("model_url")
or "",
result.get("filename") or result.get("path") or "",
result.get("repo_id") or result.get("repo") or "",
result.get("model_id") or "",
result.get("version_id") or "",
result.get("name") or "",
]
return "::".join(str(part).strip() for part in parts)
def stamp_search_result(source_key, result):
if isinstance(result, list):
return [
stamp_search_result(source_key, item)
for item in result
]
if not isinstance(result, dict):
return result
signature = get_search_result_signature(source_key, result)
if not signature:
return result
timestamp = (
result.get("searched_at")
or result.get("searchedAt")
or (
None
if force_search
else self.search_result_timestamps.get(signature)
)
)
if not timestamp:
timestamp = current_search_timestamp()
if force_search:
self.search_result_timestamps[signature] = timestamp
else:
self.search_result_timestamps.setdefault(
signature, timestamp
)
result["searched_at"] = timestamp
return result
def stamp_search_results(payload):
for source_key in (
"popular",
"model_list",
"huggingface",
"civitai",
"civarchive",
"lora_manager_archive",
):
if payload.get(source_key):
payload[source_key] = stamp_search_result(
source_key, payload[source_key]
)
return payload
def mark_any_model_fallback(result):
if isinstance(result, list):
return [
mark_any_model_fallback(item)
for item in result
]
if not isinstance(result, dict):
return result
marked = dict(result)
marked["any_model_match"] = True
marked["base_model_fallback"] = True
marked["requested_base_model"] = base_model_context
return marked
def iter_result_items(result):
if isinstance(result, list):
for item in result:
if isinstance(item, dict):
yield item
elif isinstance(result, dict):
yield result
def collect_local_hash_matches(payload):
matches = []
seen_match_paths = set()
seen_hashes = set()
for source_key in (
"huggingface",
"civitai",
"civarchive",
"lora_manager_archive",
"popular",
"model_list",
):
for source_result in iter_result_items(payload.get(source_key)):
raise_if_search_cancelled(source_key)
sha256 = extract_sha256_from_metadata(source_result)
if not sha256:
continue
if sha256 in seen_hashes:
continue
seen_hashes.add(sha256)
self.search_tracker.update(
progress_id,
progress_source,
"local_hash",
"Checking local metadata hashes",
94,
)
try:
hash_matches = search_local_matches_by_hash(
sha256,
category=category or None,
max_matches=20,
force_rescan=force_search,
)
except Exception as hash_error:
self.logger.warning(
f"Local metadata hash lookup failed for {source_key}:{sha256}: {hash_error}"
)
continue
for match in hash_matches:
model_path = (
match.get("model", {}).get("path")
or match.get("path")
or ""
)
path_key = model_path.lower()
if path_key and path_key in seen_match_paths:
continue
if path_key:
seen_match_paths.add(path_key)
enriched = {
**match,
"hash_lookup_source": source_key,
"hash_lookup_filename": source_result.get("filename")
or source_result.get("path")
or filename,
"hash_lookup_sha256": sha256,
}
matches.append(enriched)
if matches:
self.logger.info(
"Search local hash matches "
+ format_log_fields(count=len(matches))
)
return matches
def make_source_progress_callback(
source_key,
percent_min=None,
percent_max=None,
):
def source_progress_callback(payload):
raise_if_search_cancelled(source_key)
if not isinstance(payload, dict):
return
progress_payload = dict(payload)
stage = progress_payload.pop("stage", "running")
message = progress_payload.pop(
"message", "Searching..."
)
percent = progress_payload.pop("percent", None)
status = progress_payload.pop("status", "running")
progress_payload.pop("source", None)
if (
percent is not None
and percent_min is not None
and percent_max is not None
):
try:
normalized_percent = max(
0.0, min(100.0, float(percent))
)
percent = percent_min + (
normalized_percent / 100.0
) * (percent_max - percent_min)
except (TypeError, ValueError):
percent = None
self.search_tracker.update(
progress_id,
source_key,
stage,
message,
percent,
status=status,
**progress_payload,
)
return source_progress_callback
def run_source_search(
source_key,
search_task_fn,
initial_stage="query",
initial_message=None,
initial_percent=30,
log_start_fields=None,
error_handlers=None,
):
if initial_message is None:
initial_message = f"Querying {source_key.capitalize()}"
raise_if_search_cancelled(source_key)
self.search_tracker.update(
progress_id,
source_key,
initial_stage,
initial_message,
initial_percent,
)
start_fields = log_start_fields or {"file": filename}
self.logger.info(
f"Search [{source_key}] start "
+ format_log_fields(**start_fields)
)
try:
raise_if_search_cancelled(source_key)
source_results, source_found = search_task_fn()
raise_if_search_cancelled(source_key)
done_messages = {
"local": "Local database checked",
"huggingface": "HuggingFace checked",
"civitai": "CivitAI checked",
"civarchive": "CivArchive checked",
"lora_manager_archive": "LoRA Manager archive checked",
}
done_msg = done_messages.get(source_key, f"{source_key} checked")
self.search_tracker.update(
progress_id,
source_key,
"done",
done_msg,
92,
)
return source_results, source_found
except Exception as e:
if error_handlers:
for exc_type, handler_fn in error_handlers.items():
if isinstance(e, exc_type):
return handler_fn(e)
raise e
def execute_search_with_fallback(
source_key,
search_fn,
any_model_label,
):
raise_if_search_cancelled(source_key)
res = search_fn(
base_model_context or None,
make_source_progress_callback(source_key),
)
raise_if_search_cancelled(source_key)
log_search_result(source_key, res)
if not res and base_model_context:
raise_if_search_cancelled(source_key)
self.search_tracker.update(
progress_id,
source_key,
"any_model",
f"Retrying {any_model_label} any model",
72,
)
self.logger.info(
f"Search [{source_key}] retry any model "
+ format_log_fields(
file=filename,
cat=category,
base=base_model_context,
)
)
res = search_fn(
None,
make_source_progress_callback(source_key, 72, 92),
)
raise_if_search_cancelled(source_key)
log_search_result(f"{source_key}/any_model", res)
if res:
res = mark_any_model_fallback(res)
return res
def search_local_sources():
def task():
source_results = {"popular": None, "model_list": None}
source_found = False
popular_info = get_popular_model_url(filename)
log_search_result("popular", popular_info)
self.search_tracker.update(
progress_id,
"local",
"model_list",
"Checking local model database",
58,
)
model_list_result = search_model_list(filename)
log_search_result(
"model_list",
model_list_result,
{
"confidence": model_list_result.get("confidence")
if model_list_result
else None
},
)
if popular_info:
popular_result = {
"source": "popular",
"filename": filename,
**popular_info,
}
if (
model_list_result
and model_list_result.get("filename", "").lower()
== filename.lower()
and model_list_result.get("size")
):
popular_result["size"] = model_list_result.get(
"size"
)
source_results["popular"] = popular_result
source_found = True
if model_list_result:
confidence = model_list_result.get("confidence", 0)
if is_urn and confidence >= 70:
source_results["model_list"] = model_list_result
source_found = True
elif not is_urn:
source_results["model_list"] = model_list_result
source_found = True
return source_results, source_found
return run_source_search(
"local",
task,
initial_stage="popular",
initial_message="Checking popular models",
initial_percent=28,
log_start_fields={"file": filename, "cat": category},
)
def search_huggingface_source_task():
def task():
hf_result = search_huggingface_for_file(
filename,
token=hf_token or None,
brave_api_key=brave_search_api_key or None,
use_api_search=hf_use_api_search,
use_comfy_org_fallback=hf_use_comfy_org_fallback,
use_brave_fallback=hf_use_brave_fallback,
force_refresh=force_search,
progress_callback=make_source_progress_callback(
"huggingface"
),
)
log_search_result("huggingface", hf_result)
return {"huggingface": hf_result}, bool(hf_result)
return run_source_search(
"huggingface",
task,
initial_stage="query",
initial_message="Querying HuggingFace",
initial_percent=32,
log_start_fields={"file": filename},
)
def search_civitai_source_task():
def task():
source_results = {"civitai": None}
source_found = False
if is_urn:
model_id_val = data.get("model_id")
version_id_val = data.get("version_id")
if model_id_val and version_id_val:
self.search_tracker.update(
progress_id,
"civitai",
"urn",
"Resolving CivitAI URN",
46,
)
model_info = resolve_urn(model_id_val, version_id_val)
if model_info:
self.search_tracker.update(
progress_id,
"civitai",
"file",
"Selecting CivitAI file",
76,
)
primary_file = None
for file_info in model_info.get("files", []):
if (
file_info.get("name")
== model_info.get("expected_filename")
):
primary_file = file_info
break
if primary_file is None:
primary_file = (
model_info.get("files") or [{}]
)[0]
download_url = get_civitai_download_url(
version_id_val
)
source_results["civitai"] = {
"source": "civitai",
"name": model_info.get("model_name"),
"version_name": model_info.get(
"version_name"
),
"filename": model_info.get(
"expected_filename"
),
"type": category,
"download_url": download_url,
"url": f"https://civitai.com/models/{model_id_val}?modelVersionId={version_id_val}",
"model_id": model_id_val,
"version_id": version_id_val,
"size": primary_file.get("size"),
"base_model": model_info.get("base_model"),
"tags": model_info.get("tags", []),
"sha256": primary_file.get("sha256")
or (primary_file.get("hashes") or {}).get("SHA256")
or (primary_file.get("hashes") or {}).get("sha256"),
"hashes": primary_file.get("hashes") or {},
"match_type": "exact",
"confidence": 100.0,
}
log_search_result(
"civitai/urn",
source_results["civitai"],
{
"files_count": len(
model_info.get("files", [])
)
},
)
source_found = True
else:
log_search_result(
"civitai/urn",
None,
{
"model_id": model_id_val,
"version_id": version_id_val,
},
)
elif category:
self.search_tracker.update(
progress_id,
"civitai",
"fallback",
"Searching CivitAI fallback",
58,
)
self.logger.info(
"Search [civitai] URN ids missing; falling back"
)
civitai_results = search_civitai(
filename,
model_type=category,
)
log_search_result(
"civitai/fallback",
civitai_results[0] if civitai_results else None,
{
"results_count": len(civitai_results),
},
)
if civitai_results:
first_result = civitai_results[0]
source_results["civitai"] = {
"source": "civitai",
"name": first_result.get("name"),
"filename": first_result.get("filename"),
"type": first_result.get("type"),
"download_url": first_result.get(
"download_url"
),
"url": first_result.get("url"),
"size": first_result.get("size"),
"base_model": first_result.get("base_model"),
"tags": first_result.get("tags", []),
}
source_found = True
else:
civitai_result = execute_search_with_fallback(
"civitai",
lambda base_ctx, cb: search_civitai_for_file(
filename,
api_key=civitai_key or None,
model_type=category,
base_model_context=base_ctx,
session_token=civitai_session_token or None,
candidate_limit=civitai_candidate_limit,
use_trpc_search=civitai_use_trpc_search,
use_api_search=civitai_use_api_search,
use_html_fallback=civitai_use_html_fallback,
progress_callback=cb,
),
"CivitAI"
)
if civitai_result:
source_results["civitai"] = civitai_result
source_found = True
return source_results, source_found
return run_source_search(
"civitai",
task,
initial_stage="query",
initial_message="Querying CivitAI",
initial_percent=30,
log_start_fields={
"file": filename,
"cat": category,
"urn": is_urn,
},
)
def search_civarchive_source_task():
def task():
source_results = {"civarchive": None}
source_found = False
if is_urn:
model_id_val = data.get("model_id")
version_id_val = data.get("version_id")
if model_id_val and version_id_val:
self.search_tracker.update(
progress_id,
"civarchive",
"urn",
"Resolving CivArchive version",
50,
)
civarchive_result = resolve_civarchive_model_version(
model_id_val,
version_id_val,
query=filename,
)
log_search_result(
"civarchive/urn",
civarchive_result,
{
"model_id": model_id_val,
"version_id": version_id_val,
},
)
if civarchive_result:
source_results["civarchive"] = civarchive_result
source_found = True
else:
log_search_result(
"civarchive/urn",
None,
{
"model_id": model_id_val,
"version_id": version_id_val,
},
)
else:
civarchive_result = execute_search_with_fallback(
"civarchive",
lambda base_ctx, cb: search_civarchive_for_file(
filename,
model_type=category,
base_model_context=base_ctx,
limit=civarchive_candidate_limit,
progress_callback=cb,
),
"CivArchive"
)
if civarchive_result:
source_results["civarchive"] = civarchive_result
source_found = True
return source_results, source_found
def handle_civarchive_error(e):
error_message = f"CivArchive search failed: {e}"
self.logger.warning(error_message)
self.search_tracker.update(
progress_id,
"civarchive",
"error",
error_message,
100,
status="error",
)
return {
"civarchive": None,
"source_errors": {"civarchive": error_message},
}, False
return run_source_search(
"civarchive",
task,
initial_stage="query",
initial_message="Querying CivArchive",
initial_percent=30,
log_start_fields={
"file": filename,
"cat": category,
"urn": is_urn,
},
error_handlers={CivArchiveSearchError: handle_civarchive_error},
)
def search_lora_manager_archive_source_task():
def task():
lora_manager_archive_result = execute_search_with_fallback(
"lora_manager_archive",
lambda base_ctx, cb: search_lora_manager_archive_for_file(
filename,
model_type=category,
base_model_context=base_ctx,
progress_callback=cb,
),
"LoRA archive"
)
return (
{
"lora_manager_archive": lora_manager_archive_result
},
bool(lora_manager_archive_result),
)
return run_source_search(
"lora_manager_archive",
task,
initial_stage="query",
initial_message="Searching LoRA Manager archive",
initial_percent=36,
log_start_fields={"file": filename, "cat": category},
)
search_tasks = []
if search_local:
search_tasks.append(
asyncio.to_thread(search_local_sources)
)
if search_huggingface_source:
search_tasks.append(
asyncio.to_thread(search_huggingface_source_task)
)
if search_civitai_source:
search_tasks.append(
asyncio.to_thread(search_civitai_source_task)
)
if search_civarchive_source and (
filename or (is_urn and model_id and version_id)
):
search_tasks.append(
asyncio.to_thread(search_civarchive_source_task)
)
if search_lora_manager_archive_source and filename:
search_tasks.append(
asyncio.to_thread(
search_lora_manager_archive_source_task
)
)
if len(search_tasks) > 1:
self.logger.debug(
"Search sources async "
+ format_log_fields(count=len(search_tasks))
)
self.search_tracker.update(
progress_id,
progress_source,
"running",
"Waiting for search sources",
18,
)
raise_if_search_cancelled(progress_source)
for source_results, source_found in await asyncio.gather(
*search_tasks
):
raise_if_search_cancelled(progress_source)
for source_key, source_result in source_results.items():
if source_key == "source_errors":
results["source_errors"].update(source_result or {})
continue
if source_result:
results[source_key] = source_result
if source_found:
results["found"] = True
raise_if_search_cancelled(progress_source)
results["local_hash_matches"] = collect_local_hash_matches(results)
raise_if_search_cancelled(progress_source)
self.logger.info(
f"Search [{','.join(results['searched_sources'])}] done "
+ format_log_fields(
found=results["found"],
)
)
self.search_tracker.update(
progress_id,
progress_source,
"completed",
"Search complete",
100,
status="completed",
)
stamp_search_results(results)
return web.json_response(results)
except SearchCancelled:
self.search_tracker.update(
progress_id if "progress_id" in locals() else "",
progress_source if "progress_source" in locals() else "",
"cancelled",
"Cancelled",
100,
status="cancelled",
cancelled=True,
)
self.logger.info(
"Search cancelled "
+ format_log_fields(
source=progress_source if "progress_source" in locals() else "",
progress_id=progress_id if "progress_id" in locals() else "",
)
)
return web.json_response(
{
"cancelled": True,
"found": False,
"searched_sources": sorted(normalized_sources)
if "normalized_sources" in locals()
else [],
"source_errors": {},
}
)
except Exception as e:
self.search_tracker.update(
progress_id if "progress_id" in locals() else "",
progress_source if "progress_source" in locals() else "",
"error",
str(e),
100,
status="error",
)
self.logger.exception(f"Model Resolver search error: {e}")
return web.json_response({"error": str(e)}, status=500)
@routes.post("/model_resolver/clear-search-cache")
@json_api_endpoint("Clear search cache")
async def clear_search_cache_route(request):
"""Clear backend search caches after token/settings changes."""
clear_all_search_caches()
reload_popular_databases()
reload_model_list()
invalidate_model_files_cache()
invalidate_local_hash_match_cache()
self.search_result_timestamps.clear()
self.logger.info("Cleared backend search caches")
return web.json_response({"success": True, "cleared": "all"})
async def _check_credential_helper(request, payload_key, check_func, log_name):
try:
data = await request.json()
val = data.get(payload_key, "")
result = await asyncio.to_thread(check_func, val)
return web.json_response(result)
except Exception as e:
self.logger.exception(f"{log_name} check error: {e}")
return web.json_response({"error": str(e)}, status=500)
@routes.post("/model_resolver/civitai/session-token/check")
async def civitai_session_token_check_route(request):
"""Check whether a CivitAI browser session token is valid."""
return await _check_credential_helper(
request, "civitai_session_token", check_civitai_session_token, "CivitAI session token"
)
@routes.post("/model_resolver/civitai/api-key/check")
async def civitai_api_key_check_route(request):
"""Check whether a CivitAI API key is valid."""
return await _check_credential_helper(
request, "civitai_key", check_civitai_api_key, "CivitAI API key"
)
@routes.post("/model_resolver/huggingface/token/check")
async def huggingface_token_check_route(request):
"""Check whether a HuggingFace token is valid."""
return await _check_credential_helper(
request, "hf_token", check_huggingface_token, "HuggingFace token"
)
@routes.post("/model_resolver/brave/api-key/check")
async def brave_api_key_check_route(request):
"""Check whether a Brave Search API key is valid."""
return await _check_credential_helper(
request, "brave_search_api_key", check_brave_search_api_key, "Brave Search API key"
)
@routes.get("/model_resolver/huggingface/author-index/status")
@json_api_endpoint("HuggingFace author index status")
async def huggingface_author_index_status_route(request):
"""Return local HuggingFace author fallback index status."""
return web.json_response(get_author_fallback_index_status())
@routes.post("/model_resolver/huggingface/author-index/refresh")
@json_api_endpoint("HuggingFace author index refresh")
async def huggingface_author_index_refresh_route(request):
"""Refresh HuggingFace author fallback index."""
data = await request.json()
hf_token = data.get("hf_token", "")
result = await asyncio.to_thread(
refresh_author_fallback_index, hf_token or None
)
clear_huggingface_search_cache()
return web.json_response(result)
@routes.get("/model_resolver/model-list/status")
@json_api_endpoint("Model list status")
async def model_list_status_route(request):
"""Return local model-list status and optionally compare with GitHub."""
check_remote = (
str(request.query.get("check_remote", "")).lower()
in {"1", "true", "yes"}
)
return web.json_response(
get_model_list_update_status(check_remote=check_remote)
)
@routes.post("/model_resolver/model-list/update")
@json_api_endpoint("Model list update")
async def model_list_update_route(request):
"""Download latest ComfyUI-Manager model-list.json."""
result = await asyncio.to_thread(update_model_list_from_remote)
clear_all_search_caches()
self.search_result_timestamps.clear()
return web.json_response(result)
@routes.post("/model_resolver/download")
@json_api_endpoint("download", return_success_on_error=True)
async def download_model(request):
"""Start downloading a model."""
data = await request.json()
url = data.get("url", "")
filename = data.get("filename", "")
category = data.get("category", "checkpoints")
category = normalize_download_category(category)
subfolder = data.get("subfolder", "")
base_directory = data.get("base_directory", "")
path_metadata = data.get("path_metadata", {})
if not isinstance(path_metadata, dict):
path_metadata = {}
download_metadata = data.get("download_metadata") or data.get(
"metadata", {}
)
if not isinstance(download_metadata, dict):
download_metadata = {}
download_metadata = dict(download_metadata)
settings = load_resolver_settings()
if not base_directory:
base_directory = get_default_root_for_category(category, settings)
subfolder = resolve_download_subfolder(
category,
subfolder,
path_metadata,
settings,
)
if not url:
return web.json_response(
{"error": "URL is required"}, status=400
)
if not filename:
# Extract filename from URL
from urllib.parse import urlparse, unquote
parsed = urlparse(url)
filename = unquote(parsed.path.split("/")[-1])
filename = sanitize_download_filename(filename)
if not filename:
return web.json_response(
{"error": "Could not determine filename"}, status=400
)
# Build headers if needed
headers = {}
if "huggingface.co" in url:
hf_token = data.get("hf_token", "")
if hf_token:
headers["Authorization"] = f"Bearer {hf_token}"
elif "civitai.com" in url or "civitai.red" in url:
civitai_key = data.get("civitai_key", "")
if civitai_key and "token=" not in url:
url += (
f"{'&' if '?' in url else '?'}token={civitai_key}"
)
civitai_session_token = str(
data.get("civitai_session_token", "") or ""
).strip()
if civitai_session_token:
headers["Cookie"] = (
f"__Secure-civitai-token={civitai_session_token}"
)
def _first_metadata_value(*values):
return first_non_empty(*values)
def _metadata_int(value):
return to_int(value)
inferred_source = ""
if "civitai.com" in url:
inferred_source = "civitai"
elif "huggingface.co" in url:
inferred_source = "huggingface"
download_metadata.setdefault("filename", filename)
download_metadata.setdefault("category", category)
download_metadata.setdefault("download_url", url)
download_metadata.setdefault("source_url", url)
download_metadata.setdefault("path_metadata", path_metadata)
download_metadata.setdefault(
"source",
_first_metadata_value(
download_metadata.get("details_source"),
path_metadata.get("source"),
inferred_source,
),
)
model_id = _metadata_int(
_first_metadata_value(
download_metadata.get("model_id"),
download_metadata.get("modelId"),
path_metadata.get("model_id"),
)
)
version_id = _metadata_int(
_first_metadata_value(
download_metadata.get("version_id"),
download_metadata.get("versionId"),
path_metadata.get("version_id"),
)
)
source_name = str(
_first_metadata_value(
download_metadata.get("details_source"),
download_metadata.get("source"),
)
).lower()
try:
if (
source_name == "civitai"
and model_id
and not download_metadata.get("civitai_details")
):
details = await asyncio.to_thread(
get_civitai_model_details,
model_id,
version_id,
data.get("civitai_key", ""),
)
if details:
download_metadata["civitai_details"] = details
elif (
source_name == "civarchive"
and model_id
and not download_metadata.get("civitai_details")
):
details = await asyncio.to_thread(
get_civarchive_model_details,
model_id,
version_id,
)
if details:
download_metadata["civitai_details"] = details
except Exception as metadata_error:
self.logger.warning(
f"Model metadata lookup failed: {metadata_error}"
)
target_directory = ""
target_path = ""
try:
import os as _download_os
target_directory = (
get_download_directory(category, base_directory) or ""
)
if target_directory and subfolder:
target_directory = _download_os.path.join(
target_directory, subfolder
)
if target_directory:
target_path = _download_os.path.join(
target_directory, filename
)
except Exception:
target_directory = ""
target_path = ""
# Start background download
download_id = start_background_download(
url=url,
filename=filename,
category=category,
headers=headers if headers else None,
subfolder=subfolder,
base_directory=base_directory,
metadata=download_metadata,
)
return web.json_response(
{
"success": True,
"download_id": download_id,
"filename": filename,
"category": category,
"path": target_path,
"directory": target_directory,
"download_backend": settings.get("download_backend", "python"),
}
)
@routes.get("/model_resolver/progress/{download_id}")
@json_api_endpoint("progress")
async def get_download_progress(request):
"""Get progress for a specific download."""
download_id = request.match_info["download_id"]
progress = get_progress(download_id)
if progress:
return web.json_response(progress)
else:
return web.json_response(
{"error": "Download not found"}, status=404
)
@routes.get("/model_resolver/progress")
@json_api_endpoint("progress")
async def get_all_downloads_progress(request):
"""Get progress for all downloads."""
progress = get_all_progress()
return web.json_response(progress)
@routes.post("/model_resolver/cancel/{download_id}")
@json_api_endpoint("cancel", return_success_on_error=True)
async def cancel_download_route(request):
"""Cancel a download in progress."""
download_id = request.match_info["download_id"]
cancel_download(download_id)
return web.json_response({"success": True})
@routes.post("/model_resolver/pause/{download_id}")
@json_api_endpoint("pause", return_success_on_error=True)
async def pause_download_route(request):
"""Pause an aria2 download."""
download_id = request.match_info["download_id"]
result = pause_download(download_id)
status = 200 if result.get("success") else 400
return web.json_response(result, status=status)
@routes.post("/model_resolver/resume/{download_id}")
@json_api_endpoint("resume", return_success_on_error=True)
async def resume_download_route(request):
"""Resume an aria2 download."""
download_id = request.match_info["download_id"]
result = resume_download(download_id)
status = 200 if result.get("success") else 400
return web.json_response(result, status=status)
@routes.get("/model_resolver/aria2/status")
@routes.post("/model_resolver/aria2/status")
@json_api_endpoint("aria2 status")
async def aria2_status_route(request):
"""Report aria2 availability using saved settings, with optional override via POST."""
settings = await get_override_settings_from_request(request)
return web.json_response(await asyncio.to_thread(get_aria2_status, settings))
@routes.post("/model_resolver/aria2/start")
@json_api_endpoint("aria2 start", return_success_on_error=True)
async def aria2_start_route(request):
"""Start the aria2 daemon without starting a download."""
settings = await get_override_settings_from_request(request)
result = await asyncio.to_thread(start_aria2_daemon, settings)
status = 200 if result.get("success") else 400
return web.json_response(result, status=status)
@routes.get("/model_resolver/aria2/stop")
@routes.post("/model_resolver/aria2/stop")
@json_api_endpoint("aria2 stop", return_success_on_error=True)
async def aria2_stop_route(request):
"""Stop the aria2 daemon started by Model Resolver."""
result = await asyncio.to_thread(stop_aria2_daemon)
status = 200 if result.get("success") else 400
return web.json_response(result, status=status)
@routes.post("/model_resolver/aria2/install")
@json_api_endpoint("aria2 install")
async def aria2_install_route(request):
"""Download official aria2c binary and save its path."""
try:
payload = await request.json()
except Exception:
payload = {}
force = False
if isinstance(payload, dict):
force = to_bool(payload.get("force"), False)
try:
install_result = await asyncio.to_thread(install_aria2_engine, force)
except Aria2InstallError as exc:
self.logger.warning(f"Model Resolver aria2 install failed: {exc}")
return web.json_response({"success": False, "error": str(exc)}, status=500)
settings = await asyncio.to_thread(
save_resolver_settings,
{
"aria2c_path": install_result.get("aria2c_path", ""),
"download_backend": "aria2",
},
)
install_result["settings"] = settings
return web.json_response(install_result)
@routes.get("/model_resolver/directories")
@json_api_endpoint("directories")
async def get_directories(request):
"""Get available model directories."""
import folder_paths
categories = get_enabled_download_categories(list(folder_paths.folder_names_and_paths.keys()))
directories = {}
for cat in categories:
path = get_download_directory(cat)
if path:
directories[cat] = path
return web.json_response(directories)
@routes.get("/model_resolver/root-directories")
@json_api_endpoint("root directories")
async def get_root_directories(request):
"""Get configured ComfyUI root directories for path settings."""
import os
import folder_paths
known_categories = set(folder_paths.folder_names_and_paths.keys())
skip_categories = {"custom_nodes", "configs"}
categories = get_enabled_download_categories(list(known_categories))
category_source_keys = {}
for cat in [*known_categories]:
folder_key = normalize_download_category(cat)
if folder_key:
category_source_keys.setdefault(folder_key, []).append(cat)
roots = {}
settings = load_resolver_settings()
comfy_root = get_comfy_root_path(folder_paths)
for cat in categories:
folder_key = normalize_download_category(cat)
if folder_key in known_categories:
raw_candidate_keys = [folder_key]
else:
raw_candidate_keys = [
folder_key,
*TEMPLATE_KEY_ALIASES.get(folder_key, ()),
*category_source_keys.get(folder_key, []),
]
if folder_key == "ultralytics":
raw_candidate_keys = [
candidate_key
for candidate_key in raw_candidate_keys
if str(candidate_key or "").strip().lower() != "yolo"
]
candidate_keys = []
for candidate_key in raw_candidate_keys:
if (
candidate_key
and candidate_key in known_categories
and candidate_key not in candidate_keys
):
candidate_keys.append(candidate_key)
paths = []
for candidate_key in candidate_keys:
paths.extend(folder_paths.get_folder_paths(candidate_key) or [])
if folder_key == "ultralytics":
normalized_ultralytics_paths = []
for path in paths:
normalized_path = os.path.normpath(str(path or ""))
basename = os.path.basename(normalized_path).lower()
if basename == "yolo":
continue
parent_dir = os.path.dirname(normalized_path)
if (
basename in {"bbox", "segm"}
and os.path.basename(parent_dir).lower()
== "ultralytics"
):
normalized_path = parent_dir
normalized_ultralytics_paths.append(normalized_path)
paths = normalized_ultralytics_paths
preferred_directory = get_default_root_for_category(
folder_key, settings
)
normalized_paths = dedupe_local_base_directories(
paths,
preferred_directory=preferred_directory,
comfy_root=comfy_root,
)
roots[folder_key] = normalized_paths
for raw_key in known_categories:
if (
not raw_key
or raw_key in skip_categories
or raw_key in roots
):
continue
raw_paths = folder_paths.get_folder_paths(raw_key) or []
roots[raw_key] = dedupe_local_base_directories(
raw_paths,
comfy_root=comfy_root,
)
return web.json_response(roots)
@routes.get("/model_resolver/path-template-suggestions")
@json_api_endpoint("path template suggestions")
async def get_path_template_suggestions(request):
"""Infer path template presets from existing local model folders."""
from .core.sources.popular import get_base_models_config
force_rescan = request.query.get("force") == "1"
models = await asyncio.to_thread(get_model_files, force_rescan)
base_models_config = get_base_models_config()
suggestions = await asyncio.to_thread(
infer_download_path_templates,
models,
base_models_config,
)
return web.json_response(suggestions)
@routes.get("/model_resolver/capabilities")
@json_api_endpoint("capabilities")
async def get_capabilities(request):
"""Get optional source capabilities available in this install."""
return web.json_response(
{
"sources": {
"civarchive": is_civarchive_available(),
"lora_manager_archive": is_lora_manager_archive_available()
}
}
)
@routes.get("/model_resolver/subfolders/{category}")
@json_api_endpoint("subfolders")
async def get_subfolders(request):
"""Get known subfolders for a category using ComfyUI folder_paths."""
import os
import folder_paths
raw_category = (request.match_info.get("category") or "").strip()
category = normalize_download_category(raw_category)
if not category or category == "unknown":
return web.json_response([])
known_categories = set(folder_paths.folder_names_and_paths.keys())
folder_keys = get_category_folder_keys(category)
available_folder_keys = [
folder_key for folder_key in folder_keys if folder_key in known_categories
]
if not available_folder_keys:
self.logger.debug(
f"Model Resolver: skipping subfolder lookup for unknown category '{raw_category}' -> '{category}'"
)
return web.json_response([])
subfolders = {}
settings = load_resolver_settings()
comfy_root = get_comfy_root_path(folder_paths)
preferred_directory = (
get_default_root_for_category(category, settings)
or get_download_directory(category)
or ""
)
def add_subfolder(rel_path, base_dir=""):
rel_path = os.path.normpath(str(rel_path or "")).replace(
os.sep, "\\"
)
if not rel_path or rel_path == ".":
return
base_dir = os.path.abspath(base_dir) if base_dir else ""
base_identity = (
get_local_path_identity(base_dir) if base_dir else ""
)
key = (rel_path.lower(), base_identity)
base_label = (
os.path.basename(os.path.normpath(base_dir))
if base_dir
else ""
)
current = subfolders.get(key)
if current and not prefer_local_base_directory(
base_dir,
current.get("base_directory", ""),
preferred_directory,
comfy_root,
):
return
subfolders[key] = {
"value": rel_path,
"label": rel_path,
"base_label": base_label,
"base_directory": base_dir,
}
raw_base_dirs = []
for folder_key in available_folder_keys:
for base_dir in folder_paths.get_folder_paths(folder_key) or []:
if not base_dir or not os.path.isdir(base_dir):
continue
raw_base_dirs.append(base_dir)
base_dirs = dedupe_local_base_directories(
raw_base_dirs,
preferred_directory=preferred_directory,
comfy_root=comfy_root,
)
def find_base_dir(full_path):
if not full_path:
return ""
full_path_identity = get_local_path_identity(full_path)
for base_dir in base_dirs:
base_identity = get_local_path_identity(base_dir)
try:
if (
os.path.commonpath(
[full_path_identity, base_identity]
)
== base_identity
):
return base_dir
except Exception:
continue
return ""
for folder_key in available_folder_keys:
filenames = folder_paths.get_filename_list(folder_key) or []
for rel_path in filenames:
if not isinstance(rel_path, str):
continue
base_dir = ""
try:
base_dir = find_base_dir(
folder_paths.get_full_path(folder_key, rel_path)
)
except Exception:
base_dir = ""
parts = [p for p in rel_path.replace("/", "\\").split("\\") if p]
if len(parts) <= 1:
continue
current = ""
for part in parts[:-1]:
current = f"{current}\\{part}" if current else part
add_subfolder(current, base_dir)
for base_dir in base_dirs:
for root, dirs, _files in os.walk(base_dir):
rel_root = os.path.relpath(root, base_dir)
for dirname in dirs:
rel_path = (
dirname
if rel_root in ("", ".")
else os.path.join(rel_root, dirname)
)
add_subfolder(rel_path, base_dir)
value_counts = {}
for item in subfolders.values():
value_key = item.get("value", "").lower()
value_counts[value_key] = value_counts.get(value_key, 0) + 1
response_items = []
for item in subfolders.values():
value = item.get("value", "")
base_label = item.get("base_label", "")
label = (
f"{value} ({base_label})"
if base_label and value_counts.get(value.lower(), 0) > 1
else value
)
response_items.append(
{
"value": value,
"label": label,
"base_directory": item.get("base_directory", ""),
}
)
return web.json_response(
sorted(
response_items,
key=lambda item: (
item.get("value", "").lower(),
item.get("base_directory", "").lower(),
),
)
)
# ==================== SETTINGS (server-side persistence) ====================
def _flush_backend_log_handlers():
for handler in getattr(backend_log_controller, "file_handlers", {}).values():
try:
handler.flush()
except Exception:
pass
def _backend_log_sort_key(path):
name = os.path.basename(path)
rotation = 0
if ".log." in name:
base_name, rotation_text = name.rsplit(".log.", 1)
try:
rotation = int(rotation_text)
except ValueError:
rotation = 999
elif name.endswith(".log"):
base_name = name[:-4]
else:
base_name = name
return (base_name.lower(), rotation)
def _collect_backend_log_files(log_dir):
if not log_dir or not os.path.isdir(log_dir):
return []
files = []
for entry in os.listdir(log_dir):
name = str(entry or "")
if not name.startswith("azlogs_"):
continue
if not (name.endswith(".log") or ".log." in name):
continue
path = os.path.abspath(os.path.join(log_dir, name))
try:
if os.path.commonpath([log_dir, path]) != log_dir:
continue
except ValueError:
continue
if os.path.isfile(path):
files.append(path)
return sorted(files, key=_backend_log_sort_key)
def _build_backend_log_export():
_flush_backend_log_handlers()
raw_log_dir = str(backend_log_controller.config.get("log_dir") or "")
log_dir = os.path.abspath(raw_log_dir) if raw_log_dir else ""
exported_at = time.strftime("%Y-%m-%d %H:%M:%S")
lines = [
"Model Resolver Backend Logs",
f"Exported: {exported_at}",
f"Log directory: {log_dir or 'not configured'}",
f"File logging: {bool(backend_log_controller.config.get('log_to_file'))}",
"",
]
log_files = _collect_backend_log_files(log_dir)
if not log_files:
lines.append("No backend log files found.")
lines.append("")
return "\n".join(lines)
for path in log_files:
name = os.path.basename(path)
try:
stat = os.stat(path)
modified_at = time.strftime(
"%Y-%m-%d %H:%M:%S",
time.localtime(stat.st_mtime),
)
lines.append(
f"===== {name} ({stat.st_size} bytes, modified {modified_at}) ====="
)
with open(path, "r", encoding="utf-8", errors="replace") as log_file:
lines.append(log_file.read().rstrip())
except OSError as exc:
lines.append(f"===== {name} =====")
lines.append(f"Could not read log file: {exc}")
lines.append("")
return "\n".join(lines)
@routes.get("/model_resolver/logs/backend/export")
@json_api_endpoint("backend log export")
async def export_backend_logs_route(request):
"""Download Model Resolver backend logs as a text file."""
content = await asyncio.to_thread(_build_backend_log_export)
filename = f"model_resolver_backend_logs_{time.strftime('%Y%m%d_%H%M%S')}.txt"
return web.Response(
text=content,
content_type="text/plain",
headers={
"Content-Disposition": f'attachment; filename="{filename}"',
"Cache-Control": "no-store",
},
)
def _log_level_setting(value, default: str = BACKEND_DEFAULT_LOG_LEVEL) -> LogLevel:
normalized = str(value or default or "INFO").strip().upper()
if hasattr(LogLevel, normalized):
return getattr(LogLevel, normalized)
fallback = str(default or "INFO").strip().upper()
return getattr(LogLevel, fallback, LogLevel.INFO)
def _apply_backend_logging_settings(settings: dict) -> None:
enabled = resolver_bool_setting(settings.get("backend_logs_enabled"), True)
level = _log_level_setting(settings.get("backend_log_level"))
backend_log_controller.set_enabled(enabled)
backend_log_controller.set_global_level(level)
_apply_backend_logging_settings(load_resolver_settings())
@routes.get("/model_resolver/settings")
@json_api_endpoint("settings GET")
async def get_settings_route(request):
"""Return persisted settings (API keys, preferences)."""
data = await asyncio.to_thread(load_resolver_settings)
return web.json_response(data)
@routes.post("/model_resolver/settings")
@json_api_endpoint("settings POST")
async def save_settings_route(request):
"""Persist settings (API keys, preferences) to disk."""
payload = await request.json()
if not isinstance(payload, dict):
return web.json_response({"error": "Expected JSON object"}, status=400)
settings = await asyncio.to_thread(save_resolver_settings, payload)
_apply_backend_logging_settings(settings)
return web.json_response({"success": True})
self.routes_setup = True
self.logger.info("Model Resolver: API routes registered successfully")
return True
except ImportError as e:
self.logger.warning(
f"Model Resolver: Could not register routes (missing dependency): {e}"
)
return False
except Exception as e:
self.logger.error(
f"Model Resolver: Error setting up routes: {e}", exc_info=True
)
return False
# Initialize the extension
_module_log = create_module_logger(__name__)
try:
extension = ModelResolverExtension()
extension.initialize()
except Exception as e:
_module_log.error(
f"ComfyUI Model Resolver extension initialization failed: {e}", exc_info=True
)