Vito Sansevero
49a6a5a2a8
- A switch wired from a node the graph cannot read and off at run time
marks the node's run key, so an earlier run's tracker entry never
links this run's images.
- The scan reports such files as not_saved_wired ("only the run itself
can link it") instead of not_saved.
- Workflow-only metadata ignores muted and bypassed PromptManager nodes
and reads nodes inside subgraph definitions.
- The Focused, Split and Pair footer says when the switch comes from a
link.
303 lines
11 KiB
Python
303 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.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.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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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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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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counted = set()
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for field, component_text, resolved_text, component_id in (
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("text", text, resolved_positive, prompt_id),
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(
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"negative_text",
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negative_text,
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resolved_negative,
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pair["negative_prompt_id"],
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),
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):
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component_hash = generate_prompt_hash(component_text)
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if (
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field not in used_fields
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or not component_id
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or component_hash in counted
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):
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continue
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counted.add(component_hash)
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seen_at_queue = (
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resolved_text is not None
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and generate_prompt_hash(resolved_text) == component_hash
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)
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runs = positive_pending.consume(component_hash) + int(not seen_at_queue)
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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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not pair_seen
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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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