Files
ComfyAssets-ComfyUI_PromptM…/database/pair_ingestion.py
T
Vito caa9649f32 feat: reuse positive and negative prompt combinations (#195)
* feat(db): add pair schema and stage restore migrations for #193

* feat(database): persist reusable ordered prompt pairs (#193)

* feat(api): expose reusable pairs and atomic metadata enrichment (#193)

* feat(metadata): resolve canonical prompt pairs with bounded provenance (#193)

* feat(scan): enrich image pairs without guessing or duplicate links (#193)

* fix(database): preserve pair tags during global maintenance (#193)

* feat(tracking): enrich live image pairs and cancel scans safely (#193)

* feat(nodes): encode paired prompts and count cached recipe runs (#193)

* fix(database): validate restored pair ownership and provenance (#193)

* feat(admin): report pair scan outcomes and cancellation (#193)

* feat(ui): add paired prompt editor and explicit recipe library for #193

* fix(autocomplete): include reusable pair metadata vocabulary (#193)

* fix(pairs): honor recent sorting and conservative scan outcomes (#193)

* fix(ui): protect paired draft saves and clarify negative variants (#193)

* fix(metadata): preserve bounded paired execution evidence (#193)

* fix(tracking): follow actual pair output roles and prefer execution evidence (#193)

* docs(pairs): document live validation and retain renderer screenshots (#193)

* test(api): inject disposable databases before API startup (#194)

* test(api): canonicalize portable temporary gallery roots (#194)

* docs(ui): prototype branching negative variant history (#193)

* docs(ui): show selected negative beneath positive in timeline concept (#193)

* docs: retain approved timeline for later gallery redesign (#193)

* test(db): close restore fixture connections before cleanup (#194)

* test(db): reuse existing handle guards in all pair fixtures (#194)

* chore: clarify rollback test and intentional exception handling (#193)
2026-10-17 08:00:42 -07:00

137 lines
5.2 KiB
Python

"""Atomic metadata enrichment for a single known generation context."""
import json
import os
from typing import Any, Dict
from .models import normalize_image_path
from .operations import _coerce_file_info
try:
from ..utils.hashing import generate_prompt_hash
except ImportError:
from utils.hashing import generate_prompt_hash
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":
return {"status": state, "pairs_added": 0, "links_added": 0}
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)
provenance = {"resolver_version": 1, "positive": positive, "negative": negative}
encoded = json.dumps(
provenance, sort_keys=True, separators=(",", ":"), allow_nan=False
)
with db._pair_transaction() as conn:
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 {"status": "conflict", "pairs_added": 0, "links_added": 0}
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 {"status": "conflict", "pairs_added": 0, "links_added": 0}
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)
snapshots = {
column: json.dumps(metadata[key], sort_keys=True, allow_nan=False)
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"]
updates = {
key: value for key, value in snapshots.items() if existing[key] != value
}
if updates:
conn.execute(
"UPDATE generated_images SET "
+ ",".join(f"{key}=?" for key in updates)
+ " WHERE id=?",
[*updates.values(), image_id],
)
changed = True
else:
columns = ["prompt_id", "image_path", "filename", "file_path", *snapshots]
values = [
pair["positive_prompt_id"],
image_path,
os.path.basename(image_path),
normalized,
*snapshots.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,
}