* fix(history): count cached re-runs of runtime-linked text as tracked runs (#403) Since #347 a cached re-run of runtime-linked prompt text (PreviewAny or an LLM into a PromptManager text input) counts in the Library, but its history capture had no raw text, so the history page's "tracked runs" stayed at the number of jobs in which the node executed. The #347 receipt now also keeps the raw, prepend and append text the node gave the history capture. When a cached node's graph inference leaves a field unknown, the capture takes it from the receipt that matches the cache entry, labeled inferred/graph_semantics, so the job joins the prompt's history scope and gets its prompt hint. No schema change and no new evidence vocabulary; no backfill. Fails closed on no receipt, a disagreeing known field, equal outputs with different fields, oversized or invalid text and a full budget (least recently used receipts give up their fields first; counting stays). * docs(testing): link the whitespace history gap to #438
473 lines
18 KiB
Python
473 lines
18 KiB
Python
"""
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PromptManagerBase: Shared logic for PromptManager node variants.
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Provides database initialization, prompt saving, hashing, tag parsing,
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search, gallery system management, and cleanup — extracted from the
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duplicate code in prompt_manager.py and prompt_manager_text.py.
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"""
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import os
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from typing import Any, Dict, List, Optional
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try:
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from .utils.logging_config import get_logger
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except ImportError:
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import sys
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from utils.logging_config import get_logger
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try:
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from .database.operations import PromptDatabase
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from .utils.comfyui_integration import get_comfyui_integration
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from .utils.image_monitor import get_image_monitor
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from .utils.prompt_tracker import get_prompt_tracker
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from .utils.hashing import generate_prompt_hash
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from .utils.prompt_graph import resolve_text, run_prompt_nodes, save_setting
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from .utils.run_keys import executing_run_id, prompt_node_key
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from .utils.usage_tracking import PENDING_FIRST_USE
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from .utils.cached_runs import (
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CACHED_RUNS,
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Role,
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Seen,
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own_counts,
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stored_facts,
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)
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except ImportError:
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import sys
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from database.operations import PromptDatabase
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from utils.comfyui_integration import get_comfyui_integration
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from utils.image_monitor import get_image_monitor
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from utils.prompt_tracker import get_prompt_tracker
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from utils.hashing import generate_prompt_hash
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from utils.prompt_graph import resolve_text, run_prompt_nodes, save_setting
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from utils.run_keys import executing_run_id, prompt_node_key
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from utils.usage_tracking import PENDING_FIRST_USE
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from utils.cached_runs import (
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CACHED_RUNS,
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Role,
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Seen,
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own_counts,
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stored_facts,
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)
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# The optional input every PromptManager node declares last (#90): declared
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# last so no widget value of a workflow saved before it shifts.
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SAVE_TO_LIBRARY_INPUT = (
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"BOOLEAN",
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{
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"default": True,
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"label_on": "save",
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"label_off": "skip",
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"tooltip": (
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"Save this node's prompt to the library, count its runs and link its "
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"images. Off: PromptManager ignores the run; the output is unchanged."
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),
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},
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)
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class PromptManagerBase:
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"""Mixin providing shared prompt management logic for ComfyUI nodes.
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Handles database connection, prompt saving with deduplication,
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tag parsing, search, gallery system lifecycle, and cleanup.
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Subclasses only need to define ComfyUI-specific class attributes
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(INPUT_TYPES, RETURN_TYPES, FUNCTION) and their execution method.
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"""
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def __init__(self, logger_name: str = "prompt_manager.node"):
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self.logger = get_logger(logger_name)
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self.logger.debug(f"Initializing {self.__class__.__name__} node")
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self.db = PromptDatabase()
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self.prompt_tracker = get_prompt_tracker(self.db)
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self.image_monitor = get_image_monitor(self.db, self.prompt_tracker)
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self.comfyui_integration = get_comfyui_integration()
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self._start_gallery_system()
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self.logger.debug(f"{self.__class__.__name__} node initialization completed")
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def _save_prompt_to_database(
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self,
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text: str,
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category: Optional[str] = None,
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tags: Optional[list] = None,
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count_run: bool = False,
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) -> Optional[int]:
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"""Save the prompt to the SQLite database.
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Runs are normally counted by the queue hook (utils/usage_tracking.py), so a
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save only counts one when asked to (text the hook could not see, unless
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this job already counted the node from ComfyUI's cache) or when the hook
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queued this prompt before it existed. The two are independent: the
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pending catch-up is written even when ``count_run`` is False.
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Args:
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text: The prompt text
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category: Optional category
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tags: List of tags
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count_run: Count this execution as a run of the prompt
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Returns:
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The prompt ID if saved successfully, None otherwise
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"""
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try:
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prompt_hash = self._generate_hash(text)
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self.logger.debug(f"Generated hash for prompt: {prompt_hash[:16]}...")
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existing = self.db.get_prompt_by_hash(prompt_hash)
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if existing:
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self.logger.info(
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f"Found existing prompt with ID {existing['id']}, updating metadata"
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)
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if any([category, tags]):
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self.db.update_prompt_metadata(
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prompt_id=existing["id"], category=category, tags=tags
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)
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self.logger.debug("Updated metadata for existing prompt")
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if count_run:
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self._record_use(existing["id"])
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return existing["id"]
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self.logger.debug(
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f"Saving new prompt with category: {category}, tags: {tags}"
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)
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prompt_id = self.db.save_prompt(
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text=text, category=category, tags=tags, prompt_hash=prompt_hash
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)
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if prompt_id:
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self.logger.debug(f"Successfully saved new prompt with ID: {prompt_id}")
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pending = getattr(self, "pending_first_use", PENDING_FIRST_USE)
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runs = pending.consume(prompt_hash) + (1 if count_run else 0)
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if runs:
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self._record_use(prompt_id, times=runs)
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else:
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self.logger.warning("Failed to save prompt - no ID returned")
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return prompt_id
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except Exception as e:
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self.logger.error(f"Error saving prompt to database: {e}")
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return None
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def _prompt_role(
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self, prompt_graph: Any, unique_id: Any, text: str
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) -> Dict[str, bool]:
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"""How this node's execution relates to the run, from the queued graph.
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Returns flags:
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is_run_prompt: feeds a sampler's positive input (images belong to it)
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seen_at_queue: the queue hook resolved exactly this text, so it already
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counted the run and the image's metadata can identify the prompt
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known: the graph and node id were available
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"""
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if not isinstance(prompt_graph, dict) or unique_id is None:
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return {"is_run_prompt": True, "seen_at_queue": False, "known": False}
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node_id = str(unique_id)
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resolved = resolve_text(prompt_graph, node_id)
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return {
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"is_run_prompt": node_id in run_prompt_nodes(prompt_graph),
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# The hook skips a switch it cannot read (#90): the node counts
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"seen_at_queue": resolved is not None
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and save_setting(prompt_graph, node_id) is True
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and generate_prompt_hash(resolved) == generate_prompt_hash(text),
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"known": True,
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}
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def _track_prompt_execution(
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self,
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text: str,
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encoding_text: str,
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category: Optional[str],
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tags: Optional[list],
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additional_data: Dict[str, Any],
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prompt_graph: Any = None,
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unique_id: Any = None,
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) -> Optional[int]:
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"""Save the prompt and, for the run's positive prompt, register it for linking.
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Negative-prompt nodes are saved but never become the prompt their images are
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linked to. Text the queue hook could resolve is counted there and linked from
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the image's own metadata; anything else (PromptSearchList batches, unknown
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text nodes, or a resolution that doesn't match) is counted here and pushed
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onto the FIFO queue. Without graph context the pre-3.2.4 behaviour is kept.
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"""
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role = self._prompt_role(prompt_graph, unique_id, text)
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batch_item = (
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role["known"] and role["is_run_prompt"] and not role["seen_at_queue"]
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)
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counts = own_counts(
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type(self).__name__,
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stored_facts(text),
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Role(
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frozenset({"text"} if role["known"] and role["is_run_prompt"] else ())
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),
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Seen(text=role["seen_at_queue"]),
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)
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prompt_id = self._save_prompt_to_database(
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text=text,
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category=category,
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tags=tags,
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count_run=bool(counts) and not self._replayed(unique_id),
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)
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if role["is_run_prompt"] and not prompt_id:
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# The save failed: an older entry of this key must not stand in (#342)
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self._mark_untracked(prompt_graph, unique_id)
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elif role["is_run_prompt"]:
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self.prompt_tracker.set_current_prompt(
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prompt_text=encoding_text,
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additional_data={**additional_data, "prompt_id": prompt_id},
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push_to_queue=batch_item or not role["known"],
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**self._run_identity(prompt_graph, unique_id),
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)
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return prompt_id
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def _cached_runs(self) -> Any:
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return getattr(self, "cached_runs", CACHED_RUNS)
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def _replayed(self, unique_id: Any) -> bool:
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"""This job already counted the node from ComfyUI's cache (#347).
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A RAM-pressure cache can free the entry after ``execution_cached``, so
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the node executes in a job that replayed it: its own count is skipped.
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"""
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try:
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return unique_id is not None and self._cached_runs().replayed(unique_id)
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except Exception as error:
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self.logger.debug(f"Could not check the cached-run replay: {error}")
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return False
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def _record_cached_item(
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self,
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unique_id: Any,
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outputs: tuple,
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text: Any,
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negative_text: Any = None,
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fields: Optional[tuple] = None,
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) -> None:
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"""Remember this execution's outputs and stored text for cached jobs (#347).
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``fields`` are the ``(raw, prepend, append)`` texts this execution gave
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``record_runtime_context`` for each output, so a cached job's history
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can record them too (#403).
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"""
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if unique_id is None:
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return
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try:
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self._cached_runs().record_item(
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unique_id, outputs, stored_facts(text, negative_text), fields
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)
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except Exception as error:
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self.logger.debug(f"Could not record the cached-run receipt: {error}")
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@staticmethod
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def _run_identity(prompt_graph: Any, unique_id: Any) -> Dict[str, Any]:
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"""The tracker's proof that an image belongs to this execution (#342)."""
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return {
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"run_key": prompt_node_key(prompt_graph, unique_id),
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"run_id": executing_run_id(),
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}
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def _skip_not_saved(self, prompt_graph: Any = None, unique_id: Any = None) -> None:
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"""``save_to_library`` is off: nothing is saved, counted or tracked (#90).
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A literal off makes the node no run prompt (``utils.prompt_graph``), so
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no image looks up its run key. A switch wired from a node the graph
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cannot read keeps the node a run prompt: its run key is marked like an
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empty editor's, so an earlier run's entry of that key never links this
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run's images.
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"""
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message = (
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"Save to library is off for this node: its prompt is not saved, the "
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"run is not counted and its images are not linked"
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)
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if isinstance(prompt_graph, dict) and unique_id is not None:
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self._mark_untracked(prompt_graph, unique_id, message)
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else:
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self.logger.info(message)
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def _skip_empty_prompt(self, prompt_graph: Any, unique_id: Any) -> None:
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"""The ``text`` editor is empty: save and track nothing (#342).
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Prepend and append text are deliberately never stored as the prompt, so
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an empty editor has no prompt to save, count or link. For the run's
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positive node this is logged at info and the node's run key is marked
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empty (``_mark_untracked``).
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"""
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self._mark_untracked(
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prompt_graph,
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unique_id,
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"Prompt text is empty (prepend and append text are not stored): "
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"nothing saved or tracked, and this run's images stay unlinked",
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)
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def _mark_untracked(
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self, prompt_graph: Any, unique_id: Any, message: Optional[str] = None
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) -> None:
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"""This execution of a positive node has no prompt to link (#342).
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An empty editor, or a save or tracking failure. The node's run key is
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marked with a placeholder, so no earlier prompt of that key can be
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linked to this run's images, and a batch item keeps its queue place.
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``message`` is logged at info for a positive node.
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"""
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try:
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role = self._prompt_role(prompt_graph, unique_id, "")
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if not role["is_run_prompt"]:
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if message:
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self.logger.debug("Empty text on a non-positive node; not saved")
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return
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if message:
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self.logger.info(message)
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self.prompt_tracker.mark_empty(
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push_to_queue=role["known"],
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**self._run_identity(prompt_graph, unique_id),
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)
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except Exception as error:
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# Tracking must never block generation
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self.logger.warning(f"Could not mark the untracked prompt: {error}")
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def _record_use(self, prompt_id: int, times: int = 1) -> None:
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"""Count runs; a tracking failure must never block generation."""
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try:
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self.db.record_prompt_use(prompt_id, times=times)
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except Exception as e:
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self.logger.warning(f"Could not record use of prompt {prompt_id}: {e}")
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def _inject_lora_trigger_words(self, text: str) -> str:
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"""Append LoRA trigger words if integration is enabled.
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Returns the text unchanged if the integration is disabled or
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LoraManager is not installed.
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"""
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try:
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from .py.config import IntegrationConfig
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except ImportError:
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try:
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from py.config import IntegrationConfig
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except ImportError:
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return text
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if (
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not IntegrationConfig.LORA_MANAGER_ENABLED
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or not IntegrationConfig.LORA_TRIGGER_WORDS_ENABLED
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):
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return text
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try:
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from .py.lora_utils import get_trigger_cache, inject_trigger_words
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except ImportError:
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try:
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from py.lora_utils import get_trigger_cache, inject_trigger_words
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except ImportError:
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return text
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cache = get_trigger_cache()
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# Lazy-load cache on first use; a failed load waits before the next try
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# (#355: never a rescan of LoraManager's folders on every run).
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retry_due = getattr(cache, "retry_due", lambda: True)
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if not cache.is_loaded and IntegrationConfig.LORA_MANAGER_PATH and retry_due():
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cache.load(IntegrationConfig.LORA_MANAGER_PATH)
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modified, injected = inject_trigger_words(text, cache)
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if injected:
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self.logger.info(f"Injected trigger words: {', '.join(injected)}")
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return modified
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def _generate_hash(self, text: str) -> str:
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"""The prompt's deduplication hash (see utils.hashing.generate_prompt_hash)."""
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return generate_prompt_hash(text)
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def _parse_tags(self, tags_string: str) -> Optional[list]:
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"""Parse comma-separated tags string into a list.
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|
Args:
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tags_string: Comma-separated string of tags
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|
Returns:
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List of parsed tags, or None if no valid tags found
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"""
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if not tags_string or not tags_string.strip():
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return None
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tags = [tag.strip() for tag in tags_string.split(",") if tag.strip()]
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return tags if tags else None
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def _search_prompts(self, search_text: str = "") -> List[Dict[str, Any]]:
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"""Search for past prompts by text content.
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|
|
Args:
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search_text: Text to search for in prompt database
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|
|
Returns:
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List of matching prompt dictionaries with metadata
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"""
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try:
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if not search_text or not search_text.strip():
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return []
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|
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try:
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from .py.config import PromptManagerConfig
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max_results = PromptManagerConfig.MAX_SEARCH_RESULTS
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except Exception:
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|
max_results = 100
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|
results = self.db.search_prompts(
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text=search_text.strip(),
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category=None,
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tags=None,
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|
rating_min=None,
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limit=max_results,
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)
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return results
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|
|
except Exception as e:
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|
self.logger.error(f"Error searching prompts: {e}")
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|
return []
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|
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def search_prompts_api(self, search_text: str = "") -> List[Dict[str, Any]]:
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|
"""API method for JavaScript UI to search prompts."""
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|
return self._search_prompts(search_text=search_text)
|
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|
|
def get_recent_prompts_api(self, limit: int = 20) -> List[Dict[str, Any]]:
|
|
"""API method for JavaScript UI to get recent prompts."""
|
|
try:
|
|
return self.db.get_recent_prompts(limit=limit)
|
|
except Exception as e:
|
|
self.logger.error(f"Error getting recent prompts: {e}")
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|
return []
|
|
|
|
def _start_gallery_system(self):
|
|
"""Initialize and start the gallery monitoring system."""
|
|
try:
|
|
self.logger.debug("Starting gallery system...")
|
|
self.image_monitor.start_monitoring()
|
|
self.logger.debug("Gallery system started successfully")
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|
except Exception as e:
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|
self.logger.error(f"Failed to start gallery system: {e}")
|
|
self.logger.warning("Gallery features will be disabled")
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|
|
|
def get_gallery_status(self) -> Dict[str, Any]:
|
|
"""Get status of the gallery system."""
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|
return {
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|
"image_monitor": self.image_monitor.get_status(),
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|
"prompt_tracker": self.prompt_tracker.get_status(),
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|
}
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|
|
def cleanup_gallery_system(self):
|
|
"""Clean up gallery system resources.
|
|
|
|
Note: The image monitor is a singleton shared across all node instances,
|
|
so we intentionally do NOT stop it here. It should run for the entire
|
|
ComfyUI session. Stopping it would kill monitoring for all nodes.
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|
"""
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|
self.logger.debug("Gallery system cleaned up (monitor continues running)")
|