Vito Sansevero
a6505a07af
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).
325 lines
12 KiB
Python
325 lines
12 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 (
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intrinsic_pair_nodes,
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run_prompt_components,
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save_setting,
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)
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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 (
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intrinsic_pair_nodes,
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run_prompt_components,
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save_setting,
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)
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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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save_to_library: bool = True,
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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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With ``save_to_library`` off nothing is saved, counted, tracked or
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recorded (#90); the four outputs are the same.
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"""
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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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result = positive_conditioning, negative_conditioning, positive, negative_text
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if not save_to_library:
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self._skip_not_saved(prompt, unique_id)
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return result
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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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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,
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(positive, negative_text),
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text,
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negative_text,
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fields=((text, prepend_text, append_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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if known and save_setting(prompt, node_id) is not True:
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# The hook skips a switch it cannot read (#90): the node counts
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resolved_positive = resolved_negative = None
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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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