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
213 lines
7.6 KiB
Python
213 lines
7.6 KiB
Python
"""Atomic metadata enrichment for a single known generation context."""
|
|
|
|
import os
|
|
from typing import Any, Dict
|
|
|
|
from .models import normalize_image_path
|
|
from .operations import _coerce_file_info
|
|
from .workflow_documents import (
|
|
TEXT_COLUMNS,
|
|
DocumentReader,
|
|
release_documents,
|
|
resolve_image_row,
|
|
stored_values,
|
|
)
|
|
|
|
try:
|
|
from ..utils.hashing import generate_prompt_hash
|
|
from ..utils.json_strict import dumps_strict
|
|
from ..utils.prompt_pair_resolver import RESOLVER_VERSION
|
|
except ImportError:
|
|
from utils.hashing import generate_prompt_hash
|
|
from utils.json_strict import dumps_strict
|
|
from utils.prompt_pair_resolver import RESOLVER_VERSION
|
|
|
|
|
|
def blank_positive(resolution: Dict[str, Any]) -> bool:
|
|
"""A resolved pair whose stored positive text is empty (#342).
|
|
|
|
A PromptManager node whose editor is empty encodes only its prepend and
|
|
append text, which is never stored as a prompt: such a result names no
|
|
prompt to link.
|
|
"""
|
|
if resolution.get("state") != "resolved":
|
|
return False
|
|
positive = resolution.get("positive") or {}
|
|
text = positive.get("storage_text", positive.get("text"))
|
|
return not (isinstance(text, str) and text.strip())
|
|
|
|
|
|
def ingest_resolved_pair(
|
|
db: Any, image_path: str, metadata: Dict[str, Any], resolution: Dict[str, Any]
|
|
) -> Dict[str, Any]:
|
|
state = resolution.get("state", "unresolved")
|
|
if state == "resolved" and blank_positive(resolution):
|
|
state = "unresolved"
|
|
if state != "resolved":
|
|
return {"status": state, "pairs_added": 0, "links_added": 0}
|
|
with db._pair_transaction() as conn:
|
|
return _ingest_resolved_pair_in(conn, db, image_path, metadata, resolution)
|
|
|
|
|
|
def _conflict() -> Dict[str, Any]:
|
|
return {"status": "conflict", "pairs_added": 0, "links_added": 0}
|
|
|
|
|
|
def _ingest_resolved_pair_in(
|
|
conn: Any,
|
|
db: Any,
|
|
image_path: str,
|
|
metadata: Dict[str, Any],
|
|
resolution: Dict[str, Any],
|
|
*,
|
|
provenance: Dict[str, Any] | None = None,
|
|
) -> Dict[str, Any]:
|
|
"""``ingest_resolved_pair`` inside the caller's open ``_pair_transaction``.
|
|
|
|
The compatible-only rules are the public ingester's: an image with more
|
|
than one exact row, another positive, or a prior pair with another
|
|
negative is a ``conflict`` and nothing is written. The caller owns the
|
|
transaction, so its own later failure rolls the link back too.
|
|
``provenance`` replaces the link's default resolver provenance (Needs
|
|
review records the user's selection there).
|
|
"""
|
|
positive, negative = resolution["positive"], resolution["negative"]
|
|
positive_text = positive.get("storage_text", positive["text"])
|
|
negative_text = negative.get("storage_text", negative["text"])
|
|
normalized = normalize_image_path(image_path)
|
|
if provenance is None:
|
|
provenance = {
|
|
"resolver_version": RESOLVER_VERSION,
|
|
"positive": positive,
|
|
"negative": negative,
|
|
}
|
|
encoded = dumps_strict(provenance, sort_keys=True, separators=(",", ":"))
|
|
images = conn.execute(
|
|
"SELECT gi.*,p.hash AS positive_hash FROM generated_images gi "
|
|
"JOIN prompts p ON p.id=gi.prompt_id "
|
|
"WHERE gi.file_path=? OR gi.image_path=?",
|
|
(normalized, image_path),
|
|
).fetchall()
|
|
if len(images) > 1 or (
|
|
images and images[0]["positive_hash"] != generate_prompt_hash(positive_text)
|
|
):
|
|
return _conflict()
|
|
existing = images[0] if images else None
|
|
if existing:
|
|
prior = conn.execute(
|
|
"SELECT n.hash AS negative_hash FROM image_prompt_pairs ip "
|
|
"JOIN prompt_pairs pp ON pp.id=ip.pair_id "
|
|
"LEFT JOIN prompts n ON n.id=pp.negative_prompt_id WHERE ip.image_id=?",
|
|
(existing["id"],),
|
|
).fetchall()
|
|
expected = (
|
|
generate_prompt_hash(negative_text) if negative_text.strip() else None
|
|
)
|
|
if any(row["negative_hash"] != expected for row in prior):
|
|
return _conflict()
|
|
prior_pair = conn.execute(
|
|
"SELECT pp.id FROM prompt_pairs pp "
|
|
"JOIN prompts p ON p.id=pp.positive_prompt_id "
|
|
"LEFT JOIN prompts n ON n.id=pp.negative_prompt_id "
|
|
"WHERE p.hash=? AND n.hash IS ?",
|
|
(
|
|
generate_prompt_hash(positive_text),
|
|
generate_prompt_hash(negative_text) if negative_text.strip() else None,
|
|
),
|
|
).fetchone()
|
|
pair_id = db._save_pair(conn, positive_text, negative_text)
|
|
pair = conn.execute("SELECT * FROM prompt_pairs WHERE id=?", (pair_id,)).fetchone()
|
|
pairs_added = int(prior_pair is None)
|
|
file_size, width, height, image_format = _coerce_file_info(metadata)
|
|
# ComfyUI's NaN/Infinity are stored as null: the snapshot is strict JSON.
|
|
snapshots = {
|
|
column: dumps_strict(metadata[key], sort_keys=True)
|
|
for column, key in (
|
|
("workflow_data", "workflow"),
|
|
("prompt_metadata", "prompt"),
|
|
("parameters", "parameters"),
|
|
)
|
|
if key in metadata
|
|
}
|
|
info = {
|
|
"file_size": file_size,
|
|
"width": width,
|
|
"height": height,
|
|
"format": image_format,
|
|
}
|
|
snapshots.update({key: value for key, value in info.items() if value is not None})
|
|
changed = False
|
|
if existing:
|
|
image_id = existing["id"]
|
|
# Compared as stored text, whichever form the row is in.
|
|
current = resolve_image_row(DocumentReader(conn), existing)
|
|
updates = {
|
|
key: value for key, value in snapshots.items() if current[key] != value
|
|
}
|
|
if updates:
|
|
replaced = [
|
|
existing[reference]
|
|
for column, reference in TEXT_COLUMNS
|
|
if column in updates
|
|
]
|
|
updates = _document_form(conn, updates)
|
|
conn.execute(
|
|
"UPDATE generated_images SET "
|
|
+ ",".join(f"{key}=?" for key in updates)
|
|
+ " WHERE id=?",
|
|
[*updates.values(), image_id],
|
|
)
|
|
release_documents(conn, replaced)
|
|
changed = True
|
|
else:
|
|
stored = _document_form(conn, snapshots)
|
|
columns = ["prompt_id", "image_path", "filename", "file_path", *stored]
|
|
values = [
|
|
pair["positive_prompt_id"],
|
|
image_path,
|
|
os.path.basename(image_path),
|
|
normalized,
|
|
*stored.values(),
|
|
]
|
|
image_id = conn.execute(
|
|
"INSERT INTO generated_images("
|
|
+ ",".join(columns)
|
|
+ ") VALUES("
|
|
+ ",".join("?" for _ in columns)
|
|
+ ")",
|
|
values,
|
|
).lastrowid
|
|
linked = conn.execute(
|
|
"SELECT 1 FROM image_prompt_pairs WHERE pair_id=? "
|
|
"AND image_id=? AND provenance=?",
|
|
(pair_id, image_id, encoded),
|
|
).fetchone()
|
|
db._link_image_to_pair(conn, pair_id, image_id, provenance)
|
|
status = (
|
|
"added"
|
|
if existing is None
|
|
else "enriched" if changed or not linked else "unchanged"
|
|
)
|
|
return {
|
|
"status": status,
|
|
"pairs_added": pairs_added,
|
|
"links_added": int(not linked),
|
|
"pair_id": pair_id,
|
|
"image_id": image_id,
|
|
}
|
|
|
|
|
|
def _document_form(conn: Any, values: Dict[str, Any]) -> Dict[str, Any]:
|
|
"""``values`` with the workflow and prompt graph texts stored once.
|
|
|
|
Each of those columns becomes NULL beside its document id (new form);
|
|
every other column is unchanged.
|
|
"""
|
|
texts = {
|
|
column: values[column]
|
|
for column, _reference in TEXT_COLUMNS
|
|
if column in values
|
|
}
|
|
rest = {key: value for key, value in values.items() if key not in texts}
|
|
return {**rest, **stored_values(conn, texts)}
|