Files
ComfyAssets-ComfyUI_PromptM…/database/pair_ingestion.py
T
Vito Sansevero 144e6b1145 fix(ingestion): link an image only to a prompt that provably produced it
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
2026-10-25 12:58:16 -07:00

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)}