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feat(recipes): add reconnect remediation paths for missing recipe LoRAs

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- Snapshot pre-rematch entry state (reconnectSnapshot) so rematched
  entries can be undone via the existing restore flow
- Bulk missing-LoRA downloads mark unresolvable failures hash-invalid,
  flipping those entries from download to reconnect candidacy
- Recipe modal always offers a reconnect action next to download for
  missing LoRA entries
- Rematch runs collect an opt-in relaxed-matching choice (also reconnect
  missing models by file name) via a pre-run options dialog on the
  global, bulk and single-recipe entries
- L4 (filename-level) matches are listed in a results dialog with
  per-entry undo
This commit is contained in:
Will Miao
2026-09-09 06:59:54 +08:00
parent e747946f7a
commit 1b5cbbbaa0
33 changed files with 2103 additions and 76 deletions
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py/services/recipe_scanner.py
+159 -31
View File
@@ -483,32 +483,43 @@ class RecipeScanner:
suggestions.sort(key=lambda s: (-s["score"], s["file_name"].lower()))
return suggestions[:limit]
def _is_rematch_candidate(self, entry: dict[str, Any]) -> bool:
def _is_rematch_candidate(
self, entry: dict[str, Any], relaxed: bool = False
) -> bool:
"""Return True when a recipe entry is eligible for local re-matching.
An entry counts as unresolved when its identity is known to be
broken (``isDeleted`` or ``hashInvalid``) or when it is missing
identity fields (``hash``/``file_name``). A healthy entry whose
hash is simply not present in the local library is NOT a candidate:
it may be a recipe imported without downloading the model yet, and
its CivitAI-valid hash must never be overwritten by the imprecise
filename fallback.
hash is simply not present in the local library is NOT a candidate
in the default strict mode: it may be a recipe imported without
downloading the model yet, and its CivitAI-valid hash must never be
overwritten by the imprecise filename fallback.
With ``relaxed=True`` any entry carrying an identifier is a
candidate, including healthy ones — the caller opted into trying to
reconnect "Not in Library" entries by file name. Entries without
any identifier are never candidates in either mode.
"""
if not isinstance(entry, dict):
return False
unresolved = (
entry.get("isDeleted")
or entry.get("hashInvalid")
or not entry.get("hash")
or not entry.get("file_name")
)
has_identifier = (
entry.get("hash")
or entry.get("modelVersionId")
or entry.get("id")
or entry.get("file_name")
)
return bool(unresolved and has_identifier)
if not has_identifier:
return False
if relaxed:
return True
unresolved = (
entry.get("isDeleted")
or entry.get("hashInvalid")
or not entry.get("hash")
or not entry.get("file_name")
)
return bool(unresolved)
async def _build_rematch_autov3_cache(self) -> dict[str, dict[str, Any]]:
"""Build a version-cached map of computed AutoV3 hashes to local items.
@@ -809,7 +820,9 @@ class RecipeScanner:
"""Check if cancellation has been requested."""
return self._cancel_requested
async def rematch_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
async def rematch_recipe_by_id(
self, recipe_id: str, *, relaxed: bool = False
) -> Dict[str, Any]:
"""Rematch a single recipe's deleted lora/checkpoint entries locally.
Logs one INFO summary line for this run and delegates the per-recipe
@@ -817,12 +830,14 @@ class RecipeScanner:
Args:
recipe_id: ID of the recipe to rematch
relaxed: When True, healthy entries are rematch candidates too
(see ``_rematch_single_recipe``).
Returns:
Dict summary of the rematch result (see ``_rematch_recipe_by_id``).
Raises RecipeNotFoundError when the recipe is missing.
"""
result = await self._rematch_recipe_by_id(recipe_id)
result = await self._rematch_recipe_by_id(recipe_id, relaxed=relaxed)
recipe_name = (result.get("recipe") or {}).get("name") or recipe_id
logger.info(
"Recipe rematch %s (%s): success=%s, %d entries matched, %d unresolved, %d errors",
@@ -835,7 +850,9 @@ class RecipeScanner:
)
return result
async def _rematch_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
async def _rematch_recipe_by_id(
self, recipe_id: str, *, relaxed: bool = False
) -> Dict[str, Any]:
"""Rematch a single recipe's deleted lora/checkpoint entries locally.
Match snapshots (local hash cache, computed autov3 cache, filename
@@ -846,12 +863,16 @@ class RecipeScanner:
Args:
recipe_id: ID of the recipe to rematch
relaxed: When True, healthy entries are rematch candidates too
(see ``_rematch_single_recipe``).
Returns:
Dict summary of the rematch result with unified counters
(matched_recipes, matched_entries, unresolved_recipes,
unresolved_entries plus the legacy rematched/skipped/errors
fields) and a per-entry ``details`` report. The legacy ``skipped``
fields) and a per-entry ``details`` report plus a flattened
``l4_matches`` list (filename-level matches for review/undo,
consistent with the bulk/global paths). The legacy ``skipped``
field means "recipe not updated" and overlaps
``unresolved_recipes`` (a recipe with unmatched candidates counts
as both). Raises RecipeNotFoundError when the recipe is missing.
@@ -872,7 +893,8 @@ class RecipeScanner:
try:
rematched, _errors, details = await self._rematch_single_recipe(
recipe, local_cache, autov3_cache, filename_cache
recipe, local_cache, autov3_cache, filename_cache,
relaxed=relaxed,
)
except RecipePersistenceError as exc:
logger.error(
@@ -891,12 +913,16 @@ class RecipeScanner:
"unresolved_recipes": 0,
"unresolved_entries": 0,
"details": {"matched": [], "unresolved": []},
"l4_matches": [],
"recipe": recipe,
"error": str(exc),
}
unresolved_entries = len(details["unresolved"])
unresolved_recipes = 1 if unresolved_entries > 0 else 0
# Flattened L4 matches for the results modal, consistent with
# the bulk/global paths.
l4_matches = self._collect_l4_matches(recipe_id, details)
if rematched == 0:
return {
@@ -908,6 +934,7 @@ class RecipeScanner:
"unresolved_recipes": unresolved_recipes,
"unresolved_entries": unresolved_entries,
"details": details,
"l4_matches": l4_matches,
"recipe": recipe,
}
@@ -921,6 +948,7 @@ class RecipeScanner:
"unresolved_recipes": unresolved_recipes,
"unresolved_entries": unresolved_entries,
"details": details,
"l4_matches": l4_matches,
"recipe": await self.get_recipe_by_id(recipe_id),
}
@@ -930,6 +958,8 @@ class RecipeScanner:
local_cache: dict[str, dict[str, Any]],
autov3_cache: dict[str, dict[str, Any]],
filename_cache: Optional[dict[str, list[dict[str, Any]]]] = None,
*,
relaxed: bool = False,
) -> Tuple[int, int, Dict[str, Any]]:
"""Rematch a single recipe's lora/checkpoint entries against local models.
@@ -945,16 +975,24 @@ class RecipeScanner:
autov3_cache: L3 computed-autov3 cache snapshot
filename_cache: L4 filename cache snapshot, or None to disable
the filename fallback
relaxed: When True, healthy entries ("Not in Library") are also
rematch candidates. Anti-churn rule: an entry that is a
candidate ONLY because of relaxed mode is skipped when its
hash already resolves in the L1 ``local_cache`` — it is
already correctly linked and rematching would only add noise
and a pointless snapshot.
Returns:
Tuple of (rematched_entries, errors, details). The errors element
is always 0 on a normal return — a persistence failure RAISES
``RecipePersistenceError`` so callers can count it. ``details``
carries the per-entry outcome:
``{"matched": [{type, entry, file_name, match_level}],
``{"matched": [{type, entry, file_name, match_level, lora_index?}],
"unresolved": [{type, entry}]}`` where an unresolved entry is a
rematch candidate that found no local match — an expected outcome
(the model may simply not exist locally), not an error.
``lora_index`` is only present for lora entries (the checkpoint
restore endpoint needs no index).
Raises:
RecipePersistenceError: when the recipe changed but
@@ -963,11 +1001,23 @@ class RecipeScanner:
rematched = 0
details: Dict[str, Any] = {"matched": [], "unresolved": []}
def is_actionable_candidate(entry: Dict[str, Any]) -> bool:
"""Apply candidacy plus the relaxed-mode anti-churn rule."""
if self._is_rematch_candidate(entry):
return True
if not relaxed or not self._is_rematch_candidate(entry, relaxed=True):
return False
# Relaxed-only candidate: skip when the stored hash already
# resolves in the L1 local cache — the entry is already correctly
# linked and rematching would just add noise and a snapshot.
entry_hash = (entry.get("hash") or "").lower()
return local_cache.get(entry_hash) is None
# Lora entries
loras = recipe.get("loras", [])
if isinstance(loras, list):
for entry in loras:
if not self._is_rematch_candidate(entry):
for lora_index, entry in enumerate(loras):
if not is_actionable_candidate(entry):
continue
item, level = await self._match_rematch_entry_with_level(
entry,
@@ -991,6 +1041,7 @@ class RecipeScanner:
"entry": self._entry_identifier(entry),
"file_name": item.get("file_name") or "",
"match_level": level,
"lora_index": lora_index,
}
)
self._write_rematch_lora_entry(entry, item)
@@ -1000,7 +1051,7 @@ class RecipeScanner:
# silently since ``entry.get`` on a str would raise AttributeError).
checkpoint = recipe.get("checkpoint")
if isinstance(checkpoint, dict):
if self._is_rematch_candidate(checkpoint):
if is_actionable_candidate(checkpoint):
item, level = await self._match_rematch_entry_with_level(
checkpoint,
local_cache,
@@ -1065,8 +1116,36 @@ class RecipeScanner:
self._update_fts_index_for_recipe(recipe, "update")
return (rematched, 0, details)
@staticmethod
def _collect_l4_matches(
recipe_id: Any, details: Dict[str, Any]
) -> List[Dict[str, Any]]:
"""Flatten a recipe's L4 (filename-level) matches for review.
Returns ``[{recipe_id, type, entry, file_name, lora_index?}]`` rows —
one per matched detail at level L4. ``lora_index`` is only present
for lora entries (checkpoint restore needs no index).
"""
rows: List[Dict[str, Any]] = []
for match in details.get("matched", []):
if match.get("match_level") != "L4":
continue
row: Dict[str, Any] = {
"recipe_id": recipe_id,
"type": match.get("type"),
"entry": match.get("entry"),
"file_name": match.get("file_name"),
}
if "lora_index" in match:
row["lora_index"] = match["lora_index"]
rows.append(row)
return rows
async def rematch_all_recipes(
self, progress_callback: Optional[Callable[[Dict[str, Any]], Any]] = None
self,
progress_callback: Optional[Callable[[Dict[str, Any]], Any]] = None,
*,
relaxed: bool = False,
) -> Dict[str, Any]:
"""Rematch every recipe's deleted lora/checkpoint entries locally.
@@ -1080,14 +1159,19 @@ class RecipeScanner:
Args:
progress_callback: Optional callback for progress updates
(started/processing/cancelled/completed events).
(started/processing/cancelled/completed events). The
completed/cancelled payloads carry ``l4_matches``, a
flattened list of filename-level matches for review/undo.
relaxed: When True, healthy entries are rematch candidates too
(see ``_rematch_single_recipe``).
Returns:
Dict summary of the rematch run with unified counters
(matched_recipes/matched_entries/unresolved_recipes/unresolved_
entries plus the legacy success/status/rematched/skipped/errors/
total fields). ``rematched`` (legacy) counts updated recipes —
use ``matched_entries`` for the entry-level total.
total fields) and ``l4_matches``. ``rematched`` (legacy) counts
updated recipes — use ``matched_entries`` for the entry-level
total.
"""
start_time = time.perf_counter()
@@ -1109,6 +1193,7 @@ class RecipeScanner:
unresolved_entries = 0
skipped_count = 0
errors_count = 0
l4_matches: List[Dict[str, Any]] = []
for i, recipe in enumerate(all_recipes):
if self.is_cancelled():
@@ -1137,6 +1222,7 @@ class RecipeScanner:
"matched_entries": matched_entries,
"unresolved_recipes": unresolved_recipes,
"unresolved_entries": unresolved_entries,
"l4_matches": l4_matches,
}
)
return {
@@ -1150,6 +1236,7 @@ class RecipeScanner:
"matched_entries": matched_entries,
"unresolved_recipes": unresolved_recipes,
"unresolved_entries": unresolved_entries,
"l4_matches": l4_matches,
}
try:
@@ -1165,11 +1252,15 @@ class RecipeScanner:
)
rematched, _errors, details = await self._rematch_single_recipe(
recipe, local_cache, autov3_cache, filename_cache
recipe, local_cache, autov3_cache, filename_cache,
relaxed=relaxed,
)
if rematched > 0:
matched_recipes += 1
matched_entries += rematched
l4_matches.extend(
self._collect_l4_matches(recipe.get("id"), details)
)
else:
skipped_count += 1
@@ -1215,6 +1306,7 @@ class RecipeScanner:
"matched_entries": matched_entries,
"unresolved_recipes": unresolved_recipes,
"unresolved_entries": unresolved_entries,
"l4_matches": l4_matches,
}
)
@@ -1228,9 +1320,12 @@ class RecipeScanner:
"matched_entries": matched_entries,
"unresolved_recipes": unresolved_recipes,
"unresolved_entries": unresolved_entries,
"l4_matches": l4_matches,
}
async def rematch_recipes_bulk(self, recipe_ids: List[str]) -> Dict[str, Any]:
async def rematch_recipes_bulk(
self, recipe_ids: List[str], *, relaxed: bool = False
) -> Dict[str, Any]:
"""Rematch a set of recipes by their IDs.
Iterates ``_rematch_recipe_by_id`` over each id: not-found ids are
@@ -1241,14 +1336,18 @@ class RecipeScanner:
Args:
recipe_ids: List of recipe ids to rematch.
relaxed: When True, healthy entries are rematch candidates too
(see ``_rematch_single_recipe``).
Returns:
Dict summary of the bulk run with unified counters
(matched_recipes, matched_entries, unresolved_recipes,
unresolved_entries plus the legacy total/rematched/skipped/errors
fields) and a per-recipe ``details`` list. The legacy ``rematched``
field is the total entry count (same as ``matched_entries``) —
unlike ``rematch_all_recipes`` where it counts updated recipes.
fields), a per-recipe ``details`` list, and ``l4_matches`` — a
flattened list of filename-level matches for review/undo. The
legacy ``rematched`` field is the total entry count (same as
``matched_entries``) — unlike ``rematch_all_recipes`` where it
counts updated recipes.
"""
total = len(recipe_ids)
matched_recipes = 0
@@ -1259,10 +1358,13 @@ class RecipeScanner:
errors = 0
recipes: List[Dict[str, Any]] = []
details_list: List[Dict[str, Any]] = []
l4_matches: List[Dict[str, Any]] = []
for recipe_id in recipe_ids:
try:
result = await self._rematch_recipe_by_id(recipe_id)
result = await self._rematch_recipe_by_id(
recipe_id, relaxed=relaxed
)
if result.get("success"):
matched_recipes += result.get("matched_recipes", 0)
matched_entries += result.get("matched_entries", 0)
@@ -1275,6 +1377,9 @@ class RecipeScanner:
details_list.append(
{"recipe_id": recipe_id, **result["details"]}
)
l4_matches.extend(
self._collect_l4_matches(recipe_id, result["details"])
)
else:
errors += result.get("errors", 0)
except RecipeNotFoundError:
@@ -1309,12 +1414,22 @@ class RecipeScanner:
"unresolved_entries": unresolved_entries,
"recipes": recipes,
"details": details_list,
"l4_matches": l4_matches,
}
def _write_rematch_lora_entry(
self, entry: Dict[str, Any], item: Dict[str, Any]
) -> None:
"""Write back a matched local model to a lora recipe entry."""
# Snapshot the pre-rematch state so the association can be restored
# later (undo), mirroring the manual reconnect flow in
# ``update_lora_entry``. Never nest snapshots.
snapshot = {
key: copy.deepcopy(value)
for key, value in entry.items()
if key != "reconnectSnapshot"
}
entry["isDeleted"] = False
entry["hashInvalid"] = False
@@ -1338,6 +1453,8 @@ class RecipeScanner:
if civitai.get("name"):
entry["modelVersionName"] = civitai["name"]
entry["reconnectSnapshot"] = snapshot
def _write_rematch_checkpoint_entry(
self, entry: Dict[str, Any], item: Dict[str, Any]
) -> None:
@@ -1349,6 +1466,15 @@ class RecipeScanner:
when they already exist on the entry (or written fresh for the
identifier key when neither identifier form exists).
"""
# Snapshot the pre-rematch state so the association can be restored
# later (undo), mirroring the manual reconnect flow. Never nest
# snapshots.
snapshot = {
key: copy.deepcopy(value)
for key, value in entry.items()
if key != "reconnectSnapshot"
}
entry["isDeleted"] = False
entry["hashInvalid"] = False
@@ -1389,6 +1515,8 @@ class RecipeScanner:
else:
entry["modelVersionId"] = civ_id
entry["reconnectSnapshot"] = snapshot
async def _save_recipe_persistently(self, recipe: Dict[str, Any]) -> bool:
"""Helper to save a recipe to both JSON and EXIF metadata."""
recipe_id = recipe.get("id")