1288 lines
56 KiB
Python
1288 lines
56 KiB
Python
"""Curated material snapshots built from generated ComfyUI images.
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The first material type intentionally stays small: one output image, its exact
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embedded UI workflow, and node-sized parameter blocks derived from that
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workflow. Personal material data lives below ComfyUI's user directory.
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"""
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import asyncio
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import copy
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import hashlib
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import json
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import os
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import re
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import shutil
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import tempfile
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import time
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import uuid
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import threading
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from functools import lru_cache
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from aiohttp import web
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import folder_paths
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from .recipes import (
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MAX_RECIPE_BYTES,
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_build_model_references,
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_embedded_workflow_payload,
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_normalise_source_image,
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_output_source_path,
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_read_recipe,
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_recipe_cover_webp_bytes,
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_parameter_signature,
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_validate_workflow,
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_volatile_widget_indexes,
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_workflow_fingerprint,
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get_recipes_dir,
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)
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from .parameters import get_parameters_dir
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from .notebooks import MAX_NOTEBOOK_BYTES
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from .utils import require_filename, resolve_within, atomic_write_json as _atomic_write_json
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MATERIAL_SCHEMA_VERSION = 1
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MAX_MATERIAL_NAME_LENGTH = 120
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MAX_SOURCE_IMAGE_BYTES = 64 * 1024 * 1024
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_material_write_lock = threading.RLock()
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MODEL_PRIORITY = {"checkpoint": 0, "unet": 1, "lora": 2}
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def get_materials_dir():
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user_dir = (
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folder_paths.get_user_directory()
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if hasattr(folder_paths, "get_user_directory")
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else None
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)
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if not user_dir:
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user_dir = os.path.join(folder_paths.base_path, "user", "default")
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materials_dir = os.path.join(user_dir, "workflows", "anomalous_materials")
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os.makedirs(materials_dir, exist_ok=True)
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return materials_dir
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def _material_assets_dir(materials_dir, filename, create=False):
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stem = os.path.splitext(require_filename(filename))[0]
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assets_dir = resolve_within(materials_dir, ".assets", stem)
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if create:
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os.makedirs(assets_dir, exist_ok=True)
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return assets_dir
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def _read_material(path):
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if os.path.getsize(path) > MAX_RECIPE_BYTES:
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raise ValueError("Material snapshot is too large")
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with open(path, "r", encoding="utf-8") as material_file:
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value = json.load(material_file)
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if not isinstance(value, dict):
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raise ValueError("Invalid material snapshot")
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if value.get("kind") == "prompt_plan":
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_normalise_prompt_plan(value.get("plan"))
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elif value.get("kind") in ("prompt_note_bundle", "prompt_text"):
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_normalise_prompt_note(value.get("note"), value["kind"] == "prompt_text")
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elif not isinstance(value.get("workflow"), dict):
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raise ValueError("Invalid material snapshot")
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return value
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def _node_blocks(workflow, include_values=True, selected_ids=None):
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blocks = []
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occurrences = {}
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for node in workflow.get("nodes", []):
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if not isinstance(node, dict):
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continue
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node_type = str(node.get("type") or "").strip()
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if not node_type:
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continue
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occurrences[node_type] = occurrences.get(node_type, 0) + 1
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if selected_ids is not None and str(node.get("id")) not in selected_ids:
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continue
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block = {
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"node_id": node.get("id"),
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"type": node_type,
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"title": str(node.get("title") or node_type),
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"occurrence": occurrences[node_type],
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"widget_count": len(node.get("widgets_values") or []),
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"volatile_widget_indexes": list(_volatile_widget_indexes(node)),
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}
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if include_values:
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block["widgets_values"] = copy.deepcopy(node.get("widgets_values") or [])
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block["properties"] = copy.deepcopy(node.get("properties") or {})
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if node.get("mode") is not None:
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block["mode"] = node.get("mode")
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blocks.append(block)
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return blocks
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def _normalise_selected_node_ids(workflow, raw_node_ids):
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"""Validate an optional node selection while preserving workflow ID types."""
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if raw_node_ids is None:
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return None
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if not isinstance(raw_node_ids, list) or not raw_node_ids:
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raise ValueError("Selected material nodes are required")
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workflow_nodes = [node for node in workflow.get("nodes", []) if isinstance(node, dict)]
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existing = {str(node.get("id")): node.get("id") for node in workflow_nodes if node.get("id") is not None}
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selected = []
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seen = set()
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for raw_node_id in raw_node_ids:
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key = str(raw_node_id)
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if key not in existing:
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raise ValueError("Selected material node does not exist")
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if key in seen:
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continue
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seen.add(key)
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selected.append(existing[key])
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if not selected:
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raise ValueError("Selected material nodes are required")
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return selected
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def _material_node_ids(material):
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selection = material.get("selection") if isinstance(material, dict) else None
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if not isinstance(selection, dict) or selection.get("scope") != "nodes":
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return None
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node_ids = selection.get("node_ids")
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if not isinstance(node_ids, list):
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return None
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return {str(node_id) for node_id in node_ids}
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def _material_node_blocks(material, include_values=True):
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if material.get("kind") in ("prompt_note_bundle", "prompt_text", "prompt_plan"):
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return []
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return _node_blocks(material.get("workflow") or {}, include_values=include_values,
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selected_ids=_material_node_ids(material))
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def _prompt_excerpt(workflow):
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for node in workflow.get("nodes", []):
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if not isinstance(node, dict) or "cliptextencode" not in str(node.get("type") or "").lower():
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continue
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for value in node.get("widgets_values") or []:
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if isinstance(value, str) and value.strip():
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compact = re.sub(r"\s+", " ", value).strip()
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return compact[:20]
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return ""
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def _extract_workflow_params(workflow):
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params = {}
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prompts = []
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if not isinstance(workflow, dict):
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return params, prompts
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for node in workflow.get("nodes", []):
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if not isinstance(node, dict):
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continue
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ntype = str(node.get("type") or "").strip()
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ntype_lower = ntype.lower()
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widgets = node.get("widgets_values") or []
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if ntype_lower in ("ksampler", "ksampleradvanced") and isinstance(widgets, (list, tuple)):
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is_adv = ntype_lower == "ksampleradvanced"
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offset = 1 if is_adv else 0
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if len(widgets) > offset and widgets[offset] is not None:
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params.setdefault("seed", widgets[offset])
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if len(widgets) > 2 + offset and widgets[2 + offset] is not None:
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params.setdefault("steps", widgets[2 + offset])
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if len(widgets) > 3 + offset and widgets[3 + offset] is not None:
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params.setdefault("cfg", widgets[3 + offset])
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if len(widgets) > 4 + offset and widgets[4 + offset] is not None:
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params.setdefault("sampler_name", widgets[4 + offset])
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if len(widgets) > 5 + offset and widgets[5 + offset] is not None:
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params.setdefault("scheduler", widgets[5 + offset])
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if len(widgets) > 6 + offset and widgets[6 + offset] is not None:
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params.setdefault("denoise", widgets[6 + offset])
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elif ntype_lower == "emptylatentimage" and isinstance(widgets, (list, tuple)):
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if len(widgets) >= 2 and widgets[0] and widgets[1]:
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params.setdefault("resolution", f"{widgets[0]}×{widgets[1]}")
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if "cliptextencode" in ntype_lower and isinstance(widgets, (list, tuple)):
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for val in widgets:
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if isinstance(val, str) and val.strip():
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cleaned = val.strip()
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if cleaned not in prompts:
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prompts.append(cleaned)
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return params, prompts
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_PROMPT_NODE_TYPES = {"cliptextencode"}
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_PROMPT_CONSUMERS = {
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"ksampler": {"positive": "positive", "negative": "negative"},
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"ksampleradvanced": {"positive": "positive", "negative": "negative"},
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"cfgguider": {"positive": "positive", "negative": "negative"},
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"basicguider": {"conditioning": "positive"},
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"dualcfgguider": {"cond1": "positive", "cond2": "positive", "negative": "negative"},
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}
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_PROMPT_PASSTHROUGH = {
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"conditioningaverage",
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"conditioningcombine",
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"conditioningconcat",
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"conditioningmultiply",
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"conditioningsetarea",
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"conditioningsetareapercentage",
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"conditioningsetareastrength",
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"conditioningsetmask",
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"conditioningsettimesteprange",
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"conditioningzeroout",
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}
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_PROMPT_ROLES = {"positive", "negative", "both", "ignored", "unknown"}
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_MAX_PROMPT_UPSTREAM = 96
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def _norm_node_name(value):
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return str(value or "").strip().lower()
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def _is_prompt_node_type(node_type):
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name = _norm_node_name(node_type)
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return name in _PROMPT_NODE_TYPES or "cliptextencode" in name
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def _first_prompt_text(node):
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for value in node.get("widgets_values") or []:
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if isinstance(value, str) and value.strip():
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return value.strip()
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return ""
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def _title_prompt_role(node):
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title = str(node.get("title") or "").lower()
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if "neg" in title or "负向" in title or "反向" in title:
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return "negative"
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if "pos" in title or "正向" in title:
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return "positive"
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return None
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def _workflow_link_origin(workflow, link_id):
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if link_id is None:
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return None
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links = workflow.get("links")
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if isinstance(links, list):
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for link in links:
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if isinstance(link, (list, tuple)) and len(link) > 1 and link[0] == link_id:
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return link[1]
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if isinstance(link, dict) and link.get("id") == link_id:
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return link.get("origin_id")
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elif isinstance(links, dict):
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link = links.get(link_id)
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if link is None:
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link = links.get(str(link_id))
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if isinstance(link, dict):
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return link.get("origin_id")
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if isinstance(link, (list, tuple)) and len(link) > 1:
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return link[1]
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return None
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def _collect_prompt_nodes(workflow, nodes_by_id, start_id):
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queue = [start_id]
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visited = set()
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found = []
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while queue and len(visited) < _MAX_PROMPT_UPSTREAM:
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node_id = queue.pop(0)
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if node_id is None or node_id in visited:
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continue
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visited.add(node_id)
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node = nodes_by_id.get(str(node_id))
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if not isinstance(node, dict):
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continue
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if _is_prompt_node_type(node.get("type")):
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if node not in found:
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found.append(node)
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continue
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if _norm_node_name(node.get("type")) not in _PROMPT_PASSTHROUGH:
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continue
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for inbound in node.get("inputs") or []:
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if not isinstance(inbound, dict):
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continue
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input_type = _norm_node_name(inbound.get("type"))
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input_name = _norm_node_name(inbound.get("name"))
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if input_type != "conditioning" and "conditioning" not in input_name:
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continue
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origin_id = _workflow_link_origin(workflow, inbound.get("link"))
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if origin_id is not None and origin_id not in visited:
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queue.append(origin_id)
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return found
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def _normalise_prompt_role_overrides(raw):
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if not isinstance(raw, dict):
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return {}
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result = {}
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for key, value in list(raw.items())[:80]:
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if not isinstance(value, dict):
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continue
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role = value.get("role")
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if role not in _PROMPT_ROLES:
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continue
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node_type = value.get("nodeType")
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if node_type is not None and (not isinstance(node_type, str) or len(node_type) > 200):
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continue
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result[str(key)] = {
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"role": role,
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"nodeType": node_type if isinstance(node_type, str) else None,
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"source": "manual",
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}
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return result
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def _override_prompt_role(node, overrides):
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if not isinstance(overrides, dict) or not isinstance(node, dict):
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return None
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entry = overrides.get(str(node.get("id")))
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if not isinstance(entry, dict) or entry.get("role") not in _PROMPT_ROLES:
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return None
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expected = entry.get("nodeType")
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if expected and expected != node.get("type"):
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return None
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return entry["role"]
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def _prompt_roles_for_workflow(workflow, overrides=None):
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roles = {}
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if not isinstance(workflow, dict):
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return roles
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nodes = [node for node in workflow.get("nodes") or [] if isinstance(node, dict)]
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nodes_by_id = {str(node.get("id")): node for node in nodes if node.get("id") is not None}
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positive_ids = set()
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negative_ids = set()
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for node in nodes:
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mapping = _PROMPT_CONSUMERS.get(_norm_node_name(node.get("type")))
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if not mapping:
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continue
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for input_name, role in mapping.items():
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for inbound in node.get("inputs") or []:
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||
if not isinstance(inbound, dict) or _norm_node_name(inbound.get("name")) != input_name:
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continue
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origin_id = _workflow_link_origin(workflow, inbound.get("link"))
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for prompt_node in _collect_prompt_nodes(workflow, nodes_by_id, origin_id):
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node_id = str(prompt_node.get("id"))
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||
if role == "negative":
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negative_ids.add(node_id)
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||
else:
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||
positive_ids.add(node_id)
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for node in nodes:
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||
if not _is_prompt_node_type(node.get("type")):
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||
continue
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||
node_id = str(node.get("id"))
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||
in_positive = node_id in positive_ids
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||
in_negative = node_id in negative_ids
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||
if in_positive and in_negative:
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||
automatic_role, automatic_source = "both", "topology"
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||
elif in_positive:
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||
automatic_role, automatic_source = "positive", "topology"
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||
elif in_negative:
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||
automatic_role, automatic_source = "negative", "topology"
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||
else:
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titled = _title_prompt_role(node)
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||
automatic_role = titled or "unknown"
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||
automatic_source = "title" if titled else "unresolved"
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||
override = _override_prompt_role(node, overrides)
|
||
roles[node_id] = {
|
||
"role": override or automatic_role,
|
||
"source": "manual" if override else automatic_source,
|
||
"automatic_role": automatic_role,
|
||
}
|
||
return roles
|
||
|
||
|
||
def _prompt_groups_from_roles(workflow, roles, selected_ids=None):
|
||
positive = []
|
||
negative = []
|
||
if not isinstance(workflow, dict) or not isinstance(roles, dict):
|
||
return {"positive": positive, "negative": negative}
|
||
for node in workflow.get("nodes") or []:
|
||
if not isinstance(node, dict):
|
||
continue
|
||
node_id = str(node.get("id"))
|
||
if selected_ids is not None and node_id not in selected_ids:
|
||
continue
|
||
info = roles.get(node_id)
|
||
if not isinstance(info, dict):
|
||
continue
|
||
text = _first_prompt_text(node)
|
||
if not text:
|
||
continue
|
||
role = info.get("role")
|
||
if role in ("positive", "both") and text not in positive:
|
||
positive.append(text)
|
||
if role in ("negative", "both") and text not in negative:
|
||
negative.append(text)
|
||
return {"positive": positive, "negative": negative}
|
||
|
||
|
||
def _display_model_name(reference):
|
||
value = str(reference.get("saved_value") or "").replace("\\", "/").split("/")[-1]
|
||
return re.sub(r"\.(?:safetensors|ckpt|pt|bin|sft)$", "", value, flags=re.IGNORECASE)
|
||
|
||
|
||
def _suggested_name(workflow, source_path, references=None):
|
||
if references is None:
|
||
references = _build_model_references({"workflow": workflow, "params": {}}, verify_identities=False)
|
||
references.sort(key=lambda item: MODEL_PRIORITY.get(item.get("category"), 99))
|
||
model_name = _display_model_name(references[0]) if references else "工作流快照"
|
||
excerpt = _prompt_excerpt(workflow)
|
||
date = time.strftime("%Y-%m-%d", time.localtime(os.path.getmtime(source_path)))
|
||
return " · ".join(part for part in (model_name, excerpt, date) if part)[:MAX_MATERIAL_NAME_LENGTH]
|
||
|
||
|
||
def _inspect_source_image(source_image):
|
||
source = _normalise_source_image(source_image)
|
||
if not source["filename"].lower().endswith(".png"):
|
||
raise ValueError("Only PNG output images can contain reusable workflow metadata")
|
||
source_path = _output_source_path(source)
|
||
payload = _embedded_workflow_payload(source_path)
|
||
workflow = payload.get("workflow") if isinstance(payload, dict) else None
|
||
if not isinstance(workflow, dict):
|
||
raise ValueError("Image has no reusable UI workflow")
|
||
_validate_workflow(workflow)
|
||
blocks = _node_blocks(workflow, include_values=False)
|
||
references = _build_model_references({"workflow": workflow, "params": {}}, verify_identities=False)
|
||
suggested_name = _suggested_name(workflow, source_path, references)
|
||
return source, source_path, workflow, blocks, references, suggested_name
|
||
|
||
|
||
def _read_parameter_source(recipe_filename, parameter_filename=None):
|
||
recipe_filename = require_filename(recipe_filename)
|
||
if not recipe_filename.endswith(".json") or recipe_filename.startswith("."):
|
||
raise ValueError("Invalid recipe filename")
|
||
recipe_path = resolve_within(get_recipes_dir(), recipe_filename)
|
||
if os.path.getsize(recipe_path) > MAX_RECIPE_BYTES:
|
||
raise ValueError("Recipe source is too large")
|
||
recipe = _read_recipe(recipe_path)
|
||
source = recipe
|
||
if parameter_filename:
|
||
parameter_filename = require_filename(parameter_filename)
|
||
if not parameter_filename.endswith(".json") or parameter_filename.startswith("."):
|
||
raise ValueError("Invalid parameter filename")
|
||
parameter_path = resolve_within(get_parameters_dir(), parameter_filename)
|
||
if os.path.getsize(parameter_path) > MAX_RECIPE_BYTES:
|
||
raise ValueError("Parameter notebook is too large")
|
||
with open(parameter_path, "r", encoding="utf-8") as parameter_file:
|
||
source = json.load(parameter_file)
|
||
if not isinstance(source, dict) or source.get("recipe_filename") != recipe_filename:
|
||
raise ValueError("Parameter notebook does not belong to recipe")
|
||
workflow = source.get("workflow") if isinstance(source, dict) else None
|
||
if not isinstance(workflow, dict):
|
||
raise ValueError("Parameter source has no workflow")
|
||
_validate_workflow(workflow)
|
||
return recipe_filename, parameter_filename, recipe, source, workflow
|
||
|
||
|
||
def _parameter_source_record(recipe_filename, parameter_filename, recipe, source, workflow):
|
||
record = {
|
||
"type": "recipe_parameter_notebook" if parameter_filename else "workflow_recipe",
|
||
**_snapshot_recipe_source(recipe_filename),
|
||
"parameter_signature": (_parameter_signature(workflow) or {}).get("value") or "",
|
||
}
|
||
if parameter_filename:
|
||
record["parameter_filename"] = parameter_filename
|
||
record["parameter_name"] = str(source.get("name") or "").strip()[:200]
|
||
elif isinstance(recipe, dict):
|
||
record["parameter_name"] = str(recipe.get("name") or "").strip()[:200]
|
||
return record
|
||
|
||
|
||
def _store_assets(materials_dir, filename, source_path):
|
||
source_size = os.path.getsize(source_path)
|
||
if source_size > MAX_SOURCE_IMAGE_BYTES:
|
||
raise ValueError("Source image is too large")
|
||
digest = hashlib.sha256()
|
||
with open(source_path, "rb") as source_file:
|
||
for block in iter(lambda: source_file.read(1024 * 1024), b""):
|
||
digest.update(block)
|
||
assets_dir = _material_assets_dir(materials_dir, filename, create=True)
|
||
source_asset = f"source-{digest.hexdigest()}.png"
|
||
source_target = resolve_within(assets_dir, source_asset)
|
||
if not os.path.exists(source_target):
|
||
fd, temp_path = tempfile.mkstemp(prefix=".source-", suffix=".tmp", dir=assets_dir)
|
||
os.close(fd)
|
||
try:
|
||
shutil.copyfile(source_path, temp_path)
|
||
os.replace(temp_path, source_target)
|
||
finally:
|
||
if os.path.exists(temp_path):
|
||
os.remove(temp_path)
|
||
|
||
preview = _recipe_cover_webp_bytes(source_path)
|
||
preview_asset = None
|
||
if preview:
|
||
data, width, height = preview
|
||
preview_asset = f"preview-{hashlib.sha256(data).hexdigest()}.webp"
|
||
preview_target = resolve_within(assets_dir, preview_asset)
|
||
if not os.path.exists(preview_target):
|
||
with open(preview_target, "wb") as preview_file:
|
||
preview_file.write(data)
|
||
else:
|
||
width = height = None
|
||
return {
|
||
"source_asset_id": source_asset,
|
||
"preview_asset_id": preview_asset,
|
||
"preview_width": width,
|
||
"preview_height": height,
|
||
"source_sha256": digest.hexdigest(),
|
||
"source_size": source_size,
|
||
}
|
||
|
||
|
||
def _recipe_link_fingerprint(recipe):
|
||
if not isinstance(recipe, dict):
|
||
return ""
|
||
fingerprint = recipe.get("workflow_fingerprint")
|
||
workflow_hash = fingerprint.get("value") if isinstance(fingerprint, dict) else ""
|
||
if not workflow_hash and isinstance(recipe.get("workflow"), dict):
|
||
workflow_hash = (_workflow_fingerprint(recipe["workflow"]) or {}).get("value") or ""
|
||
params = recipe.get("params") if isinstance(recipe.get("params"), dict) else {}
|
||
overrides = params.get("promptRoleOverrides") if isinstance(params.get("promptRoleOverrides"), dict) else {}
|
||
payload = json.dumps(
|
||
{"workflow": workflow_hash, "promptRoleOverrides": overrides},
|
||
ensure_ascii=False,
|
||
sort_keys=True,
|
||
separators=(",", ":"),
|
||
).encode("utf-8")
|
||
return hashlib.sha256(payload).hexdigest()
|
||
|
||
|
||
def _snapshot_recipe_source(recipe_filename):
|
||
if not recipe_filename:
|
||
return {}
|
||
record = {"recipe_filename": recipe_filename}
|
||
try:
|
||
path = resolve_within(get_recipes_dir(), require_filename(recipe_filename))
|
||
recipe = _read_recipe(path)
|
||
except (OSError, ValueError, json.JSONDecodeError, TypeError):
|
||
return record
|
||
if not isinstance(recipe, dict):
|
||
return record
|
||
name = str(recipe.get("name") or "").strip()
|
||
if name:
|
||
record["recipe_name"] = name[:120]
|
||
fingerprint = _recipe_link_fingerprint(recipe)
|
||
if fingerprint:
|
||
record["recipe_fingerprint"] = fingerprint
|
||
return record
|
||
|
||
|
||
def _live_recipe_source(source):
|
||
if not isinstance(source, dict):
|
||
return None
|
||
filename = source.get("recipe_filename")
|
||
if not isinstance(filename, str) or not filename:
|
||
return None
|
||
info = {
|
||
"filename": filename,
|
||
"name": str(source.get("recipe_name") or "").strip(),
|
||
"status": "missing",
|
||
}
|
||
try:
|
||
path = resolve_within(get_recipes_dir(), require_filename(filename))
|
||
if not os.path.isfile(path):
|
||
return info
|
||
recipe = _read_recipe(path)
|
||
except (OSError, ValueError, json.JSONDecodeError, TypeError):
|
||
return info
|
||
if isinstance(recipe, dict):
|
||
live_name = str(recipe.get("name") or "").strip()
|
||
if live_name:
|
||
info["name"] = live_name[:120]
|
||
snapshot = str(source.get("recipe_fingerprint") or "")
|
||
current = _recipe_link_fingerprint(recipe)
|
||
if snapshot and current and snapshot != current:
|
||
info["status"] = "modified"
|
||
else:
|
||
info["status"] = "current"
|
||
return info
|
||
|
||
|
||
def _material_summary(filename, material):
|
||
image = material.get("image") or {}
|
||
source = material.get("source") if isinstance(material.get("source"), dict) else {}
|
||
blocks = _material_node_blocks(material, include_values=False)
|
||
summary = {
|
||
"filename": filename,
|
||
"id": material.get("id"),
|
||
"name": material.get("name") or "未命名素材",
|
||
"kind": material.get("kind"),
|
||
"tags": _normalise_material_tags(material.get("tags") or []),
|
||
"source_sha256": image.get("source_sha256", ""),
|
||
"timestamp": material.get("timestamp", 0),
|
||
"node_count": len(blocks),
|
||
"node_types": sorted({block["type"] for block in blocks}),
|
||
"selection": copy.deepcopy(material.get("selection")),
|
||
"image": {
|
||
"preview_asset_id": image.get("preview_asset_id"),
|
||
"source_asset_id": image.get("source_asset_id"),
|
||
"width": image.get("preview_width"),
|
||
"height": image.get("preview_height"),
|
||
},
|
||
"capabilities": list(material.get("capabilities") or []),
|
||
"source": {
|
||
"type": source.get("type"),
|
||
"label": str(source.get("parameter_name") or source.get("recipe_name") or source.get("notebook_name") or "").strip(),
|
||
},
|
||
"source_fingerprint": str(source.get("parameter_signature") or image.get("source_sha256") or ""),
|
||
}
|
||
if source.get("recipe_filename"):
|
||
summary["source_recipe"] = {
|
||
"filename": source.get("recipe_filename"),
|
||
"name": str(source.get("recipe_name") or "").strip(),
|
||
"fingerprint": str(source.get("recipe_fingerprint") or ""),
|
||
}
|
||
return summary
|
||
|
||
|
||
def _workflow_hashes_for_blocks(workflow, blocks):
|
||
hashes = (workflow.get("extra") or {}).get("anomalous_hashes") if isinstance(workflow, dict) else None
|
||
if not isinstance(hashes, dict):
|
||
return {}
|
||
prefixes = tuple(f"{block.get('node_id')}_" for block in blocks)
|
||
return {
|
||
key: copy.deepcopy(value)
|
||
for key, value in hashes.items()
|
||
if isinstance(key, str) and key.startswith(prefixes)
|
||
}
|
||
|
||
|
||
@lru_cache(maxsize=4096)
|
||
def _cached_material_summary(path, signature):
|
||
return _material_summary(os.path.basename(path), _read_material(path))
|
||
|
||
|
||
def _with_live_recipe_source(summary):
|
||
snapshot = summary.get("source_recipe")
|
||
if not isinstance(snapshot, dict) or not snapshot.get("filename"):
|
||
return summary
|
||
summary["source_recipe"] = _live_recipe_source({
|
||
"recipe_filename": snapshot.get("filename"),
|
||
"recipe_name": snapshot.get("name"),
|
||
"recipe_fingerprint": snapshot.get("fingerprint"),
|
||
})
|
||
return summary
|
||
|
||
|
||
def _summary_for_path(path, stat=None):
|
||
stat = stat or os.stat(path)
|
||
signature = (stat.st_size, stat.st_mtime_ns, stat.st_ctime_ns)
|
||
return _with_live_recipe_source(copy.deepcopy(_cached_material_summary(path, signature)))
|
||
|
||
|
||
def _list_materials(materials_dir):
|
||
result = []
|
||
try:
|
||
materials_dir = os.path.realpath(materials_dir)
|
||
entries = os.scandir(materials_dir)
|
||
except OSError:
|
||
return result
|
||
with entries:
|
||
for entry in entries:
|
||
if not entry.is_file() or not entry.name.endswith(".json") or entry.name.startswith("."):
|
||
continue
|
||
try:
|
||
path = resolve_within(materials_dir, entry.name) if entry.is_symlink() else entry.path
|
||
result.append(copy.deepcopy(_summary_for_path(path, entry.stat())))
|
||
except (OSError, ValueError):
|
||
continue
|
||
result.sort(key=lambda item: (item.get("timestamp", 0), item["filename"]), reverse=True)
|
||
return result
|
||
|
||
|
||
async def api_inspect_image_material(request):
|
||
try:
|
||
payload = await request.json()
|
||
source, source_path, workflow, blocks, references, suggested_name = await asyncio.to_thread(
|
||
_inspect_source_image, payload.get("source_image")
|
||
)
|
||
except (AttributeError, ValueError, json.JSONDecodeError):
|
||
return web.json_response({"status": "error", "message": "Image has no reusable UI workflow"}, status=400)
|
||
except FileNotFoundError:
|
||
return web.json_response({"status": "error", "message": "Output image not found"}, status=404)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not inspect output image"}, status=500)
|
||
sampling_params, prompts = _extract_workflow_params(workflow)
|
||
prompt_roles = _prompt_roles_for_workflow(workflow)
|
||
return web.json_response({
|
||
"status": "success",
|
||
"source_image": source,
|
||
"suggested_name": suggested_name,
|
||
"node_count": len(blocks),
|
||
"node_blocks": blocks,
|
||
"workflow": workflow,
|
||
"model_references": references,
|
||
"prompt_excerpt": _prompt_excerpt(workflow),
|
||
"params": sampling_params,
|
||
"prompts": prompts,
|
||
"prompt_roles": prompt_roles,
|
||
"prompt_groups": _prompt_groups_from_roles(workflow, prompt_roles),
|
||
})
|
||
|
||
|
||
def _normalise_material_tags(tags):
|
||
if not isinstance(tags, list) or len(tags) > 20:
|
||
raise ValueError("Invalid material tags")
|
||
result = []
|
||
seen = set()
|
||
for tag in tags:
|
||
if not isinstance(tag, str) or not tag.strip() or len(tag.strip()) > 60:
|
||
raise ValueError("Invalid material tag")
|
||
tag = tag.strip()
|
||
if tag.casefold() not in seen:
|
||
result.append(tag)
|
||
seen.add(tag.casefold())
|
||
return result
|
||
|
||
|
||
def _persist_material(materials_dir, filename, source_path, material, allow_duplicate=False):
|
||
with _material_write_lock:
|
||
return _persist_material_files(materials_dir, filename, source_path, material, allow_duplicate)
|
||
|
||
|
||
def _persist_parameter_material(materials_dir, filename, material, allow_duplicate=False):
|
||
with _material_write_lock:
|
||
target = resolve_within(materials_dir, filename)
|
||
if os.path.exists(target):
|
||
raise ValueError("Material already exists")
|
||
if not allow_duplicate:
|
||
selection = sorted(str(value) for value in (material.get("selection") or {}).get("node_ids", []))
|
||
fingerprint = str((material.get("source") or {}).get("parameter_signature") or "")
|
||
for summary in _list_materials(materials_dir):
|
||
candidate_selection = sorted(str(value) for value in (summary.get("selection") or {}).get("node_ids", []))
|
||
if (summary.get("kind") == material.get("kind")
|
||
and summary.get("source_fingerprint") == fingerprint
|
||
and candidate_selection == selection):
|
||
return summary
|
||
_atomic_write_json(target, material)
|
||
return None
|
||
|
||
|
||
def _persist_material_files(materials_dir, filename, source_path, material, allow_duplicate):
|
||
target = resolve_within(materials_dir, filename)
|
||
assets_target = _material_assets_dir(materials_dir, filename)
|
||
if os.path.exists(target) or os.path.exists(assets_target):
|
||
raise ValueError("Material already exists")
|
||
with tempfile.TemporaryDirectory(prefix=".save-", dir=materials_dir) as staging:
|
||
material["image"] = _store_assets(staging, filename, source_path)
|
||
if not allow_duplicate:
|
||
selection = sorted(str(value) for value in (material.get("selection") or {}).get("node_ids", []))
|
||
for summary in _list_materials(materials_dir):
|
||
candidate_selection = sorted(str(value) for value in (summary.get("selection") or {}).get("node_ids", []))
|
||
if summary.get("source_sha256") == material["image"]["source_sha256"] and summary.get("kind") == material.get("kind") and candidate_selection == selection:
|
||
return summary
|
||
staged_json = resolve_within(staging, filename)
|
||
_atomic_write_json(staged_json, material)
|
||
os.makedirs(os.path.dirname(assets_target), exist_ok=True)
|
||
os.replace(_material_assets_dir(staging, filename), assets_target)
|
||
try:
|
||
os.replace(staged_json, target)
|
||
except OSError:
|
||
shutil.rmtree(assets_target)
|
||
raise
|
||
|
||
|
||
async def api_save_image_material(request):
|
||
try:
|
||
payload = await request.json()
|
||
source, source_path, workflow, blocks, references, suggested_name = await asyncio.to_thread(
|
||
_inspect_source_image, payload.get("source_image")
|
||
)
|
||
name = payload.get("name") or suggested_name
|
||
if not isinstance(name, str) or not (name := name.strip()) or len(name) > MAX_MATERIAL_NAME_LENGTH:
|
||
raise ValueError("Invalid material name")
|
||
tags = _normalise_material_tags(payload.get("tags", []))
|
||
allow_duplicate = payload.get("allow_duplicate", False)
|
||
if not isinstance(allow_duplicate, bool):
|
||
raise ValueError("Invalid duplicate preference")
|
||
selected_node_ids = _normalise_selected_node_ids(workflow, payload.get("selected_node_ids"))
|
||
selected_id_keys = {str(node_id) for node_id in selected_node_ids or []}
|
||
if selected_node_ids is not None:
|
||
blocks = [block for block in blocks if str(block.get("node_id")) in selected_id_keys]
|
||
references = [
|
||
reference for reference in references
|
||
if str(reference.get("node_id")) in selected_id_keys
|
||
]
|
||
material_id = uuid.uuid4().hex
|
||
filename = f"material_{int(time.time())}_{material_id}.json"
|
||
materials_dir = get_materials_dir()
|
||
now = int(time.time() * 1000)
|
||
source_record = {"type": "generated_image", "image": source}
|
||
recipe_filename = payload.get("recipe_filename")
|
||
if isinstance(recipe_filename, str) and recipe_filename.strip():
|
||
try:
|
||
recipe_filename = require_filename(recipe_filename.strip())
|
||
except (AttributeError, TypeError, ValueError):
|
||
recipe_filename = ""
|
||
if recipe_filename.endswith(".json"):
|
||
source_record.update(_snapshot_recipe_source(recipe_filename))
|
||
prompt_role_overrides = _normalise_prompt_role_overrides(payload.get("promptRoleOverrides"))
|
||
material = {
|
||
"schema_version": MATERIAL_SCHEMA_VERSION,
|
||
"id": material_id,
|
||
"kind": "image_node_selection" if selected_node_ids is not None else "image_workflow_snapshot",
|
||
"name": name,
|
||
"tags": tags,
|
||
"timestamp": now,
|
||
"source": source_record,
|
||
"workflow": workflow,
|
||
"model_references": references,
|
||
"capabilities": (
|
||
["apply_node_parameters", "reference_image"]
|
||
if selected_node_ids is not None
|
||
else ["open_workflow", "apply_node_parameters", "reference_image"]
|
||
),
|
||
}
|
||
if selected_node_ids is not None:
|
||
material["selection"] = {"scope": "nodes", "node_ids": selected_node_ids}
|
||
if prompt_role_overrides:
|
||
material["promptRoleOverrides"] = prompt_role_overrides
|
||
duplicate = await asyncio.to_thread(_persist_material, materials_dir, filename, source_path, material, allow_duplicate)
|
||
if duplicate:
|
||
return web.json_response({"status": "duplicate", "filename": duplicate["filename"], "name": duplicate["name"]}, status=409)
|
||
except (AttributeError, ValueError, json.JSONDecodeError):
|
||
return web.json_response({"status": "error", "message": "Could not save image material"}, status=400)
|
||
except FileNotFoundError:
|
||
return web.json_response({"status": "error", "message": "Output image not found"}, status=404)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not save image material"}, status=500)
|
||
return web.json_response({
|
||
"status": "success",
|
||
"filename": filename,
|
||
"material": _with_live_recipe_source(_material_summary(filename, material)),
|
||
"node_blocks": blocks,
|
||
})
|
||
|
||
|
||
async def api_save_parameter_material(request):
|
||
try:
|
||
payload = await request.json()
|
||
recipe_filename, parameter_filename, recipe, source, workflow = await asyncio.to_thread(
|
||
_read_parameter_source,
|
||
payload.get("recipe_filename", ""),
|
||
payload.get("parameter_filename"),
|
||
)
|
||
source_name = str(source.get("name") or recipe.get("name") or "参数素材").strip()
|
||
name = payload.get("name") or source_name
|
||
if not isinstance(name, str) or not (name := name.strip()) or len(name) > MAX_MATERIAL_NAME_LENGTH:
|
||
raise ValueError("Invalid material name")
|
||
tags = _normalise_material_tags(payload.get("tags", recipe.get("tags") or []))
|
||
allow_duplicate = payload.get("allow_duplicate", False)
|
||
if not isinstance(allow_duplicate, bool):
|
||
raise ValueError("Invalid duplicate preference")
|
||
|
||
reusable_ids = [
|
||
node.get("id") for node in workflow.get("nodes", [])
|
||
if isinstance(node, dict) and node.get("id") is not None
|
||
and isinstance(node.get("widgets_values"), list) and node.get("widgets_values")
|
||
]
|
||
raw_selection = payload.get("selected_node_ids")
|
||
selected_node_ids = _normalise_selected_node_ids(
|
||
workflow,
|
||
reusable_ids if raw_selection is None else raw_selection,
|
||
)
|
||
reusable_keys = {str(value) for value in reusable_ids}
|
||
if any(str(value) not in reusable_keys for value in selected_node_ids):
|
||
raise ValueError("Selected node has no reusable parameters")
|
||
selected_keys = {str(value) for value in selected_node_ids}
|
||
blocks = [
|
||
block for block in _node_blocks(workflow, include_values=False)
|
||
if str(block.get("node_id")) in selected_keys
|
||
]
|
||
references = [
|
||
reference for reference in _build_model_references(source, verify_identities=False)
|
||
if str(reference.get("node_id")) in selected_keys
|
||
]
|
||
source_record = _parameter_source_record(
|
||
recipe_filename, parameter_filename, recipe, source, workflow
|
||
)
|
||
material_id = uuid.uuid4().hex
|
||
filename = f"material_{int(time.time())}_{material_id}.json"
|
||
material = {
|
||
"schema_version": MATERIAL_SCHEMA_VERSION,
|
||
"id": material_id,
|
||
"kind": "recipe_parameter_selection",
|
||
"name": name,
|
||
"tags": tags,
|
||
"timestamp": int(time.time() * 1000),
|
||
"source": source_record,
|
||
"workflow": workflow,
|
||
"model_references": references,
|
||
"capabilities": ["apply_node_parameters"],
|
||
"selection": {"scope": "nodes", "node_ids": selected_node_ids},
|
||
}
|
||
params = source.get("params") if isinstance(source.get("params"), dict) else {}
|
||
prompt_role_overrides = _normalise_prompt_role_overrides(params.get("promptRoleOverrides"))
|
||
if prompt_role_overrides:
|
||
material["promptRoleOverrides"] = prompt_role_overrides
|
||
materials_dir = get_materials_dir()
|
||
duplicate = await asyncio.to_thread(
|
||
_persist_parameter_material, materials_dir, filename, material, allow_duplicate
|
||
)
|
||
if duplicate:
|
||
return web.json_response({
|
||
"status": "duplicate",
|
||
"filename": duplicate["filename"],
|
||
"name": duplicate["name"],
|
||
}, status=409)
|
||
except (AttributeError, TypeError, ValueError, json.JSONDecodeError):
|
||
return web.json_response({"status": "error", "message": "Could not save parameter material"}, status=400)
|
||
except FileNotFoundError:
|
||
return web.json_response({"status": "error", "message": "Parameter source not found"}, status=404)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not save parameter material"}, status=500)
|
||
return web.json_response({
|
||
"status": "success",
|
||
"filename": filename,
|
||
"material": _with_live_recipe_source(_material_summary(filename, material)),
|
||
"node_blocks": blocks,
|
||
})
|
||
|
||
|
||
def _normalise_prompt_note(data, prompt_only=False):
|
||
if not isinstance(data, dict):
|
||
raise ValueError("Invalid prompt note")
|
||
if len(json.dumps(data, ensure_ascii=False, allow_nan=False).encode("utf-8")) > MAX_NOTEBOOK_BYTES:
|
||
raise ValueError("Prompt note is too large")
|
||
result = {}
|
||
for key in ("promptEn", "promptZh", "targetLang"):
|
||
value = data.get(key, "")
|
||
if not isinstance(value, str):
|
||
raise ValueError("Invalid prompt text")
|
||
result[key] = value
|
||
translations = data.get("translations", {})
|
||
if not isinstance(translations, dict) or any(not isinstance(value, str) for value in translations.values()):
|
||
raise ValueError("Invalid prompt translations")
|
||
result["translations"] = copy.deepcopy(translations)
|
||
if not prompt_only:
|
||
base = data.get("baseModel", "")
|
||
main = data.get("mainModel")
|
||
loras = data.get("loras", [])
|
||
if not isinstance(base, str) or (main is not None and not isinstance(main, dict)):
|
||
raise ValueError("Invalid prompt models")
|
||
if not isinstance(loras, list) or len(loras) > 100 or any(not isinstance(model, dict) for model in loras):
|
||
raise ValueError("Invalid prompt LoRAs")
|
||
for model in ([main] if main is not None else []) + loras:
|
||
if not isinstance(model.get("filename"), str) or not model["filename"]:
|
||
raise ValueError("Invalid prompt model filename")
|
||
result.update(baseModel=base, mainModel=copy.deepcopy(main), loras=copy.deepcopy(loras))
|
||
return result
|
||
|
||
|
||
async def api_save_prompt_note_material(request):
|
||
try:
|
||
payload = await request.json()
|
||
scope = payload.get("scope", "note")
|
||
if scope not in ("note", "prompt"):
|
||
raise ValueError("Invalid prompt scope")
|
||
source_filename = require_filename(payload.get("notebook_filename", ""))
|
||
if not source_filename.endswith(".json") or source_filename.startswith("."):
|
||
raise ValueError("Invalid notebook filename")
|
||
name = payload.get("name", "")
|
||
if not isinstance(name, str) or not name.strip() or len(name.strip()) > MAX_MATERIAL_NAME_LENGTH:
|
||
raise ValueError("Invalid material name")
|
||
note = _normalise_prompt_note(payload.get("note"), scope == "prompt")
|
||
if scope == "prompt" and not note["promptEn"].strip():
|
||
raise ValueError("Prompt is empty")
|
||
tags = _normalise_material_tags(payload.get("tags", []))
|
||
allow_duplicate = payload.get("allow_duplicate", False)
|
||
if not isinstance(allow_duplicate, bool):
|
||
raise ValueError("Invalid duplicate preference")
|
||
signature = hashlib.sha256(json.dumps(note, ensure_ascii=False, sort_keys=True, allow_nan=False).encode("utf-8")).hexdigest()
|
||
material_id = uuid.uuid4().hex
|
||
filename = f"material_{int(time.time())}_{material_id}.json"
|
||
material = {
|
||
"schema_version": MATERIAL_SCHEMA_VERSION, "id": material_id,
|
||
"kind": "prompt_text" if scope == "prompt" else "prompt_note_bundle",
|
||
"name": name.strip(), "tags": tags, "timestamp": int(time.time() * 1000),
|
||
"source": {"type": "prompt_note", "notebook_filename": source_filename,
|
||
"notebook_name": name.strip(), "parameter_signature": signature},
|
||
"note": note, "selection": {"scope": scope},
|
||
"capabilities": ["copy_prompt", "restore_prompt_note"],
|
||
}
|
||
duplicate = await asyncio.to_thread(
|
||
_persist_parameter_material, get_materials_dir(), filename, material, allow_duplicate
|
||
)
|
||
if duplicate:
|
||
return web.json_response({"status": "duplicate", "filename": duplicate["filename"],
|
||
"name": duplicate["name"]}, status=409)
|
||
return web.json_response({"status": "success", "filename": filename,
|
||
"material": _material_summary(filename, material)})
|
||
except (AttributeError, TypeError, ValueError):
|
||
return web.json_response({"status": "error", "message": "Invalid prompt note material"}, status=400)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not save prompt note material"}, status=500)
|
||
|
||
|
||
def _normalise_prompt_plan(plan):
|
||
if not isinstance(plan, dict) or len(json.dumps(plan, ensure_ascii=False, allow_nan=False).encode("utf-8")) > MAX_NOTEBOOK_BYTES:
|
||
raise ValueError("Invalid prompt plan")
|
||
parts = plan.get("parts", [])
|
||
if not isinstance(parts, list) or len(parts) > 100:
|
||
raise ValueError("Invalid prompt parts")
|
||
result = {"parts": []}
|
||
for key in ("positive", "negative"):
|
||
if not isinstance(plan.get(key, ""), str):
|
||
raise ValueError("Invalid prompt text")
|
||
result[key] = plan.get(key, "")
|
||
for part in parts:
|
||
if not isinstance(part, dict) or part.get("category") not in ("general", "specific", "base", "style", "subject", "trigger") or not isinstance(part.get("enabled", True), bool):
|
||
raise ValueError("Invalid prompt part")
|
||
item = {"category": part["category"], "enabled": part.get("enabled", True)}
|
||
for key in ("name", "positive", "negative"):
|
||
if not isinstance(part.get(key, ""), str):
|
||
raise ValueError("Invalid prompt part text")
|
||
item[key] = part.get(key, "")
|
||
if len(item["name"]) > 120:
|
||
raise ValueError("Prompt part name is too long")
|
||
result["parts"].append(item)
|
||
return result
|
||
|
||
|
||
async def api_save_prompt_plan(request):
|
||
try:
|
||
payload = await request.json()
|
||
name = payload.get("name", "")
|
||
if not isinstance(name, str) or not name.strip() or len(name.strip()) > MAX_MATERIAL_NAME_LENGTH:
|
||
raise ValueError("Invalid plan name")
|
||
plan = _normalise_prompt_plan(payload.get("plan"))
|
||
tags = _normalise_material_tags(payload.get("tags", []))
|
||
allow_duplicate = payload.get("allow_duplicate", False)
|
||
if not isinstance(allow_duplicate, bool):
|
||
raise ValueError("Invalid duplicate preference")
|
||
signature = hashlib.sha256(json.dumps(plan, ensure_ascii=False, sort_keys=True).encode("utf-8")).hexdigest()
|
||
material_id = uuid.uuid4().hex
|
||
filename = f"material_{int(time.time())}_{material_id}.json"
|
||
material = {"schema_version": MATERIAL_SCHEMA_VERSION, "id": material_id,
|
||
"kind": "prompt_plan", "name": name.strip(), "tags": tags,
|
||
"timestamp": int(time.time() * 1000), "plan": plan,
|
||
"source": {"type": "prompt_plan", "parameter_signature": signature},
|
||
"capabilities": ["compose_prompt"], "selection": {"scope": "prompt_plan"}}
|
||
duplicate = await asyncio.to_thread(_persist_parameter_material, get_materials_dir(), filename, material, allow_duplicate)
|
||
if duplicate:
|
||
return web.json_response({"status": "duplicate", "filename": duplicate["filename"], "name": duplicate["name"]}, status=409)
|
||
return web.json_response({"status": "success", "filename": filename, "material": _material_summary(filename, material)})
|
||
except (AttributeError, TypeError, ValueError):
|
||
return web.json_response({"status": "error", "message": "Invalid prompt plan"}, status=400)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not save prompt plan"}, status=500)
|
||
|
||
|
||
def _material_category(material):
|
||
if material.get("kind") == "image_workflow_snapshot":
|
||
return "workflow"
|
||
if material.get("kind") in ("prompt_text", "prompt_note_bundle", "prompt_plan"):
|
||
return "prompts"
|
||
types = material.get("node_types", [])
|
||
if types and all(_is_prompt_node_type(value) for value in types):
|
||
return "prompts"
|
||
return "params"
|
||
|
||
|
||
def _query_materials(materials_dir, query):
|
||
materials = _list_materials(materials_dir)
|
||
all_tags = sorted({tag for material in materials for tag in material.get("tags", [])}, key=str.casefold)
|
||
search = query.get("q", "").strip().casefold()
|
||
tag = query.get("tag", "").strip().casefold()
|
||
kind = query.get("kind", "")
|
||
category = query.get("category", "all")
|
||
if category not in ("all", "workflow", "params", "prompts"):
|
||
raise ValueError("Invalid material category")
|
||
node_type = query.get("node_type", "")
|
||
if len(node_type) > 200:
|
||
raise ValueError("Invalid node type")
|
||
if len(search) > 200 or len(tag) > 60 or kind not in (
|
||
"", "image_workflow_snapshot", "image_node_selection", "recipe_parameter_selection", "prompt_note_bundle", "prompt_text", "prompt_plan"
|
||
):
|
||
raise ValueError("Invalid material filter")
|
||
materials = [material for material in materials
|
||
if (not search or search in " ".join([material["name"], *material["node_types"], *material.get("tags", [])]).casefold())
|
||
and (not tag or tag in [value.casefold() for value in material.get("tags", [])])
|
||
and (not kind or material["kind"] == kind)
|
||
and (category == "all" or _material_category(material) == category)
|
||
and (not node_type or node_type in material["node_types"])]
|
||
total = len(materials)
|
||
limit = min(100, max(1, int(query.get("limit", 48))))
|
||
pages = max(1, (total + limit - 1) // limit)
|
||
page = min(pages, max(1, int(query.get("page", 1))))
|
||
# Existing non-paginated callers retain their response; the library requests pages.
|
||
if "page" in query or "limit" in query:
|
||
materials = materials[(page - 1) * limit:page * limit]
|
||
return {"status": "success", "materials": materials, "total": total,
|
||
"page": page, "pages": pages, "tags": all_tags}
|
||
|
||
|
||
async def api_get_materials(request):
|
||
try:
|
||
payload = await asyncio.to_thread(_query_materials, get_materials_dir(), dict(request.query))
|
||
return web.json_response(payload)
|
||
except (TypeError, ValueError):
|
||
return web.json_response({"status": "error", "message": "Invalid material filter"}, status=400)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not list materials"}, status=500)
|
||
|
||
|
||
def _update_material_details(materials_dir, filename, name, tags, prompt_role_overrides=None,
|
||
update_prompt_roles=False):
|
||
with _material_write_lock:
|
||
path = resolve_within(materials_dir, filename)
|
||
material = _read_material(path)
|
||
material.update(name=name, tags=tags)
|
||
if update_prompt_roles:
|
||
if prompt_role_overrides:
|
||
material["promptRoleOverrides"] = prompt_role_overrides
|
||
else:
|
||
material.pop("promptRoleOverrides", None)
|
||
_atomic_write_json(path, material)
|
||
return _with_live_recipe_source(_material_summary(filename, material))
|
||
|
||
|
||
async def api_update_material(request):
|
||
try:
|
||
payload = await request.json()
|
||
filename = require_filename(payload.get("filename", ""))
|
||
name = payload.get("name", "")
|
||
if not filename.endswith(".json") or filename.startswith(".") or not isinstance(name, str) or not name.strip() or len(name.strip()) > MAX_MATERIAL_NAME_LENGTH:
|
||
raise ValueError("Invalid material details")
|
||
tags = _normalise_material_tags(payload.get("tags", []))
|
||
update_prompt_roles = "promptRoleOverrides" in payload
|
||
prompt_role_overrides = (
|
||
_normalise_prompt_role_overrides(payload.get("promptRoleOverrides"))
|
||
if update_prompt_roles else None
|
||
)
|
||
material = await asyncio.to_thread(
|
||
_update_material_details,
|
||
get_materials_dir(),
|
||
filename,
|
||
name.strip(),
|
||
tags,
|
||
prompt_role_overrides,
|
||
update_prompt_roles,
|
||
)
|
||
return web.json_response({"status": "success", "material": material})
|
||
except (AttributeError, TypeError, ValueError):
|
||
return web.json_response({"status": "error", "message": "Invalid material details"}, status=400)
|
||
except FileNotFoundError:
|
||
return web.json_response({"status": "error", "message": "Material not found"}, status=404)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not update material"}, status=500)
|
||
|
||
|
||
def _material_detail_response(path, include_workflow):
|
||
material = _read_material(path)
|
||
can_open = (material.get("kind") == "image_workflow_snapshot"
|
||
and (material.get("selection") or {}).get("scope") != "nodes"
|
||
and "open_workflow" in material.get("capabilities", []))
|
||
if include_workflow == "1" and not can_open:
|
||
return web.json_response({"status": "error", "message": "Material cannot open a full workflow"}, status=403)
|
||
workflow = material.get("workflow") or {}
|
||
prompt_roles = _prompt_roles_for_workflow(workflow, material.get("promptRoleOverrides"))
|
||
prompt_groups = _prompt_groups_from_roles(workflow, prompt_roles, _material_node_ids(material))
|
||
blocks = _material_node_blocks(material, include_values=True) if include_workflow != "1" else []
|
||
if include_workflow == "0" or not can_open:
|
||
material.pop("workflow", None)
|
||
return web.json_response({
|
||
"status": "success",
|
||
"data": material,
|
||
"source_recipe": _live_recipe_source(material.get("source") or {}),
|
||
"node_blocks": blocks,
|
||
"workflow_hashes": _workflow_hashes_for_blocks(workflow, blocks),
|
||
"prompt_roles": prompt_roles,
|
||
"prompt_groups": prompt_groups,
|
||
})
|
||
|
||
|
||
async def api_get_material_full(request):
|
||
try:
|
||
filename = require_filename(request.query.get("filename", ""))
|
||
if not filename.endswith(".json"):
|
||
raise ValueError("Invalid material filename")
|
||
include_workflow = request.query.get("include_workflow")
|
||
if include_workflow not in (None, "0", "1"):
|
||
raise ValueError("Invalid workflow inclusion flag")
|
||
return await asyncio.to_thread(_material_detail_response,
|
||
resolve_within(get_materials_dir(), filename), include_workflow)
|
||
except (AttributeError, ValueError, json.JSONDecodeError):
|
||
return web.json_response({"status": "error", "message": "Invalid material"}, status=400)
|
||
except FileNotFoundError:
|
||
return web.json_response({"status": "error", "message": "Material not found"}, status=404)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not read material"}, status=500)
|
||
|
||
|
||
async def api_get_materials_by_node_type(request):
|
||
node_type = request.query.get("type", "")
|
||
if not isinstance(node_type, str) or not node_type.strip() or len(node_type) > 200:
|
||
return web.json_response({"status": "error", "message": "Invalid node type"}, status=400)
|
||
materials_dir = get_materials_dir()
|
||
|
||
def collect():
|
||
matches = []
|
||
for summary in _list_materials(materials_dir):
|
||
if node_type not in summary["node_types"]:
|
||
continue
|
||
try:
|
||
material = _read_material(resolve_within(materials_dir, summary["filename"]))
|
||
except (OSError, ValueError, json.JSONDecodeError):
|
||
continue
|
||
blocks = [block for block in _material_node_blocks(material, include_values=True) if block["type"] == node_type]
|
||
if blocks:
|
||
matches.append({
|
||
"filename": summary["filename"],
|
||
"name": summary["name"],
|
||
"kind": summary["kind"],
|
||
"timestamp": summary["timestamp"],
|
||
"blocks": blocks,
|
||
"workflow_hashes": _workflow_hashes_for_blocks(material["workflow"], blocks),
|
||
})
|
||
return matches
|
||
|
||
matches = await asyncio.to_thread(collect)
|
||
return web.json_response({"status": "success", "materials": matches})
|
||
|
||
|
||
async def api_get_material_asset(request):
|
||
try:
|
||
filename = require_filename(request.query.get("filename", ""))
|
||
asset_id = require_filename(request.query.get("asset", ""))
|
||
if not filename.endswith(".json") or not asset_id.lower().endswith((".png", ".webp")):
|
||
raise ValueError("Invalid material asset")
|
||
materials_dir = get_materials_dir()
|
||
await asyncio.to_thread(_summary_for_path, resolve_within(materials_dir, filename))
|
||
asset_path = resolve_within(_material_assets_dir(materials_dir, filename), asset_id)
|
||
if not os.path.isfile(asset_path):
|
||
raise FileNotFoundError
|
||
except (AttributeError, ValueError, json.JSONDecodeError):
|
||
return web.json_response({"status": "error", "message": "Invalid material asset"}, status=400)
|
||
except FileNotFoundError:
|
||
return web.json_response({"status": "error", "message": "Material asset not found"}, status=404)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not read material asset"}, status=500)
|
||
return web.FileResponse(asset_path)
|
||
|
||
|
||
async def api_delete_material(request):
|
||
try:
|
||
payload = await request.json()
|
||
filename = require_filename(payload.get("filename", ""))
|
||
if not filename.endswith(".json"):
|
||
raise ValueError("Invalid material filename")
|
||
materials_dir = get_materials_dir()
|
||
path = resolve_within(materials_dir, filename)
|
||
await asyncio.to_thread(_delete_material, materials_dir, filename, path)
|
||
except (AttributeError, ValueError, json.JSONDecodeError):
|
||
return web.json_response({"status": "error", "message": "Invalid material"}, status=400)
|
||
except FileNotFoundError:
|
||
return web.json_response({"status": "error", "message": "Material not found"}, status=404)
|
||
except OSError:
|
||
return web.json_response({"status": "error", "message": "Could not delete material"}, status=500)
|
||
return web.json_response({"status": "success"})
|
||
|
||
|
||
def _delete_material(materials_dir, filename, path):
|
||
with _material_write_lock:
|
||
_read_material(path)
|
||
os.remove(path)
|
||
assets_dir = _material_assets_dir(materials_dir, filename)
|
||
if os.path.isdir(assets_dir):
|
||
shutil.rmtree(assets_dir)
|