Vito Sansevero
144e6b1145
An LLM fed a PromptManagerPair's prepend_text while its text editor was empty. The node refused to save (an empty positive raised and logged a warning), and the image monitor then linked the image to a stale tracker entry or to the newest prompt in the database. - Nodes: an empty text editor saves and tracks nothing (prepend and append text are never the stored prompt), logs at info, and marks the node's run key empty so no earlier entry can be used for its images. - Tracker entries carry a run key: a digest of the prompt node and its whole upstream graph, the identity ComfyUI's cache uses. The monitor computes the same key from the image's embedded graph and uses a queued or snapshot entry only when the keys match (a snapshot also needs a known run with one entry, so a batch's last item is never applied to every image). - The recency fallback is gone; anything uncertain stays unlinked and is logged at info. - Recorded execution history attributes a file when exactly one run reported it, the file was written during that run, and the run's positive contexts name one stored prompt. The monitor and the output scan use it as their last certain source. - The scan and pair ingestion treat a resolved pair with an empty stored positive as unresolved instead of raising. - tools/review_image_links.py reviews selected links by these rules; dry run by default, --apply changes only named ids after a backup. Closes #342
282 lines
10 KiB
Python
282 lines
10 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 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.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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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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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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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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