Vito
55fa2c4870
* fix(usage): count cached re-runs of runtime-linked prompt text (#347) A PromptManager-family node whose text comes from a runtime link (PreviewAny, an LLM, a list node) counted only the job that executed it; later jobs served from ComfyUI's output cache counted nothing. Each execution now records a receipt (digests of its STRING outputs and hashes of the text it stores) per run key and queue item. On execution_cached the receipt whose digests equal the cache entry's text is replayed once for the job, with the node's role and what the queue hook already saw recomputed from the job's own graph. The executing node and the replay count through one shared own_counts. Unmatched cache entries count nothing, as before; a node that executes after its replay in the same job skips its own count. No schema change, no backfill. * fix(usage): never replay a node twice in one job; dedupe receipts once complete (#347) A repeated execution_cached id or message for the same job now counts the node once. Receipts replace equal older ones only when their job finishes (or the next job starts), so a list still recording [A] of [A, B] no longer drops an older [A] receipt. Node-level tests check the receipt each execution records. * test(comfyui): count #347's cached-run cases in the execution suite pin (#347) The pin listed 19 execution-text-link cases per project; #347 adds five node kinds and eight one-renderer cases, so the suite lists 32 per project and 118 in total with #332's image-attribution case from main.
302 lines
11 KiB
Python
302 lines
11 KiB
Python
"""Paired positive and negative conditioning with reusable recipe storage."""
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import hashlib
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import json
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import time
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from typing import Any, Dict, Optional, Tuple
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if __package__:
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from .utils.execution_context_capture import record_runtime_context
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else:
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from utils.execution_context_capture import record_runtime_context
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try:
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from .prompt_manager import IO, InputTypeDict, PromptManagerFocused
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from .utils.cached_runs import (
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PAIR,
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Role,
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Seen,
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own_counts,
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pair_components,
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stored_facts,
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)
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from .utils.hashing import generate_prompt_hash
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from .utils.pair_execution import record_pair_execution
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from .utils.prompt_graph import intrinsic_pair_nodes, run_prompt_components
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from .utils.prompt_pair_resolver import resolve_text_input
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from .utils.usage_tracking import (
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PENDING_FIRST_USE,
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PENDING_PAIR_FIRST_USE,
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pair_run_key,
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)
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except ImportError:
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from prompt_manager import IO, InputTypeDict, PromptManagerFocused
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from utils.cached_runs import (
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PAIR,
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Role,
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Seen,
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own_counts,
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pair_components,
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stored_facts,
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)
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from utils.hashing import generate_prompt_hash
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from utils.pair_execution import record_pair_execution
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from utils.prompt_graph import intrinsic_pair_nodes, run_prompt_components
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from utils.prompt_pair_resolver import resolve_text_input
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from utils.usage_tracking import (
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PENDING_FIRST_USE,
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PENDING_PAIR_FIRST_USE,
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pair_run_key,
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)
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class PromptManagerPair(PromptManagerFocused):
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"""Keep raw editors as one recipe while encoding their effective texts."""
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@classmethod
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def INPUT_TYPES(cls) -> InputTypeDict:
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inputs = super().INPUT_TYPES()
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inputs["required"] = {
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"text": inputs["required"]["text"],
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"negative_text": (
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IO.STRING,
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{"default": "", "multiline": True, "dynamicPrompts": True},
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),
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"clip": inputs["required"]["clip"],
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}
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inputs["hidden"]["extra_pnginfo"] = "EXTRA_PNGINFO"
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return inputs
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RETURN_TYPES = (IO.CONDITIONING, IO.CONDITIONING, IO.STRING, IO.STRING)
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RETURN_NAMES = ("positive", "negative", "positive_text", "negative_text")
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OUTPUT_TOOLTIPS = (
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"Positive conditioning with composition and optional LoRA trigger words.",
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"Negative conditioning from the negative editor, including empty text.",
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"The effective positive text that was encoded.",
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"The unchanged negative text that was encoded.",
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)
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DESCRIPTION = "Encode and save a reusable positive/negative prompt pair."
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def encode_prompt(
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self,
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clip: Any,
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text: str,
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negative_text: str = "",
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category: str = "",
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tags: str = "",
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search_text: str = "",
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prepend_text: str = "",
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append_text: str = "",
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prompt: Optional[Dict[str, Any]] = None,
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unique_id: Optional[str] = None,
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extra_pnginfo: Optional[Dict[str, Any]] = None,
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) -> Tuple[Any, Any, str, str]:
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"""Encode both sides once; database and tracking failures never block CLIP."""
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if clip is None:
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raise RuntimeError("ERROR: clip input is invalid: None")
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if not isinstance(text, str) or not isinstance(negative_text, str):
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raise ValueError("Positive and negative prompt text must be strings")
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positive = self._inject_lora_trigger_words(
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" ".join(
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part
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for part in (prepend_text.strip(), text, append_text.strip())
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if part
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)
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)
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positive_conditioning = clip.encode_from_tokens_scheduled(
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clip.tokenize(positive)
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)
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negative_conditioning = clip.encode_from_tokens_scheduled(
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clip.tokenize(negative_text)
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)
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record_pair_execution(
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extra_pnginfo,
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unique_id,
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text=text,
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negative_text=negative_text,
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positive_text=positive,
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negative_effective_text=negative_text,
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prepend_text=prepend_text.strip(),
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append_text=append_text.strip(),
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)
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pair_id = prompt_id = None
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known = isinstance(prompt, dict) and unique_id is not None
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node_id = str(unique_id)
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used_fields = (
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{
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field
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for source, field in run_prompt_components(prompt)
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if source == node_id
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}
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if known
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else {"text"}
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)
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is_positive = "text" in used_fields
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pair_used = node_id in intrinsic_pair_nodes(prompt) if known else True
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if not text.strip():
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# Nothing to store: prepend/append are never the stored prompt (#342)
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self._skip_empty_prompt(prompt, unique_id)
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else:
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try:
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pair_id, prompt_id = self._save_and_track_pair(
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text,
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negative_text,
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positive,
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category=category,
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tags=tags,
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prepend_text=prepend_text,
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append_text=append_text,
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prompt=prompt,
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unique_id=unique_id,
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used_fields=used_fields,
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is_positive=is_positive,
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pair_used=pair_used,
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)
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except Exception as error:
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self.logger.warning(f"Could not save or track paired prompt: {error}")
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if is_positive:
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self._mark_untracked(prompt, unique_id)
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try:
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self.comfyui_integration.register_prompt(
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f"promptmanager_pair_{time.time_ns()}",
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positive,
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{
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"prompt_id": prompt_id,
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"pair_id": pair_id if pair_used else None,
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"negative_text": negative_text,
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"category": category.strip() or None,
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},
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)
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except Exception as error:
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self.logger.warning(f"Could not register paired metadata: {error}")
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result = positive_conditioning, negative_conditioning, positive, negative_text
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record_runtime_context(
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type(self).__name__,
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text,
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prepend_text,
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append_text,
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positive,
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role="positive",
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)
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record_runtime_context(
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type(self).__name__, negative_text, "", "", negative_text, role="negative"
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)
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self._record_cached_item(
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unique_id, (positive, negative_text), text, negative_text
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)
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return result
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def _save_and_track_pair(
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self,
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text: str,
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negative_text: str,
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positive: str,
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*,
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category: str,
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tags: str,
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prepend_text: str,
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append_text: str,
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prompt: Optional[Dict[str, Any]],
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unique_id: Optional[str],
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used_fields: set,
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is_positive: bool,
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pair_used: bool,
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) -> Tuple[Optional[int], Optional[int]]:
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"""Save the recipe, count its runs and register the positive for linking."""
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known = isinstance(prompt, dict) and unique_id is not None
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node_id = str(unique_id)
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pair_id = self.db.save_prompt_pair(
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text,
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negative_text,
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category=category.strip() or None,
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tags=self._parse_tags(tags),
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)
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pair = self.db.get_prompt_pair(pair_id)
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prompt_id = pair["positive_prompt_id"]
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resolved_positive = (
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resolve_text_input(prompt, node_id, "text") if known else None
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)
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resolved_negative = (
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resolve_text_input(prompt, node_id, "negative_text") if known else None
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)
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positive_seen = resolved_positive is not None and generate_prompt_hash(
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resolved_positive
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) == generate_prompt_hash(text)
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pair_seen = (
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positive_seen
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and resolved_negative is not None
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and generate_prompt_hash(resolved_negative)
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== generate_prompt_hash(negative_text)
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)
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negative_seen = resolved_negative is not None and generate_prompt_hash(
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resolved_negative
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) == generate_prompt_hash(negative_text)
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positive_pending = getattr(self, "pending_first_use", PENDING_FIRST_USE)
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pair_pending = getattr(self, "pending_pair_first_use", PENDING_PAIR_FIRST_USE)
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facts = stored_facts(text, negative_text)
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role = Role(frozenset(used_fields), pair_used)
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# Own counts are skipped when this job already counted the node from
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# ComfyUI's cache (#347); the pending first-use catch-up never is.
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counts = (
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[]
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if self._replayed(unique_id)
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else own_counts(
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PAIR, facts, role, Seen(positive_seen, negative_seen, pair_seen)
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)
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)
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component_ids = {"text": prompt_id, "negative_text": pair["negative_prompt_id"]}
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for field, component_hash in pair_components(facts, role):
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component_id = component_ids[field]
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if not component_id:
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continue
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runs = positive_pending.consume(component_hash) + int(
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("prompt", component_hash) in counts
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)
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if runs:
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self.db.record_prompt_use(component_id, times=runs)
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if pair_used:
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runs = pair_pending.consume(pair_run_key(text, negative_text)) + int(
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("pair", facts.positive_hash, facts.negative_hash) in counts
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)
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if runs:
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self.db.record_prompt_pair_use(pair_id, times=runs)
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if is_positive:
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self.prompt_tracker.set_current_prompt(
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prompt_text=positive,
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additional_data={
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"prompt_id": prompt_id,
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"pair_id": pair_id if pair_used else None,
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"positive_text": positive,
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"negative_text": negative_text,
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"positive_storage_text": text.strip(),
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"negative_storage_text": negative_text.strip(),
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"prepend_text": prepend_text.strip(),
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"append_text": append_text.strip(),
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"final_text": positive,
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"category": category.strip() or None,
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"tags": self._parse_tags(tags) or [],
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},
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push_to_queue=not positive_seen or (pair_used and not pair_seen),
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**self._run_identity(prompt, unique_id),
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)
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return pair_id, prompt_id
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@classmethod
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def IS_CHANGED(
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cls,
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clip: Any,
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text: str = "",
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negative_text: str = "",
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category: str = "",
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tags: str = "",
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search_text: str = "",
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prepend_text: str = "",
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append_text: str = "",
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**kwargs: Any,
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) -> str:
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"""Either editor, composition or pair metadata invalidates the node cache."""
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serialized = json.dumps(
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[text, negative_text, prepend_text, append_text, category, tags]
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)
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return hashlib.sha256(serialized.encode("utf-8")).hexdigest()
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