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Any authenticated user could fetch the profile image of a model they have no access to, and could tell an existing model id from an unknown one by whether the response carried the image or the default logo.
The endpoint now serves an image only to callers who can see the model itself: the owner, an admin under the admin bypass, or the holder of a read grant, with the same rule applied to arena models defined in config. Everyone else gets the default logo, byte for byte the response an unknown id already returned, so ids can no longer be probed. BYPASS_MODEL_ACCESS_CONTROL is honoured here because it is what decides which models reach a user's model list to begin with.
Avatars now fall back to the default logo wherever a viewer meets a model id without holding a grant on it: a model reply in a channel shown to the other members, and the admin analytics and evaluation pages when the admin bypass is switched off.
Moving a folder under one of its own subfolders was accepted. A folder in a parent loop is never a root, so it and everything under it silently disappeared from the sidebar, and there was no way to get it back from the UI.
The move is now rejected with a 400, folders whose parent chain loops are put back at the root on the next folder list, and the folder tree traversals skip ids they have already visited so existing data in that state stays workable.
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The timer scheduler polls once a second and cancels on every message send and chat open, the sidebar lists chats ordered by `updated_at`, and the folder badges count unread chats per folder. None of those could be served by an index, so each call read most of the `chat` table, and because `meta` sits after the chat payload column SQLite had to walk every row's overflow pages to get there. On a large history that stalls the sidebar, every chat switch and every send, and the idle poll alone burns about a quarter of a CPU core.
Timers now keep their due time in a dedicated `chat.timer_at` column behind a partial index, and the chat list, unread and unfinished-reply queries each get an index matching their filter and ordering. Existing pending timers are backfilled from their meta by the migration. Dropping the `internal` and `type` checks also makes a forked timer chat inert, where a fork used to copy `meta` verbatim and become a second claim target that could fire a duplicate timer.
Measured on SQLite, same rows returned:
| query | before | after |
|---|---|---|
| idle timer poll (2000 chats, 0.43 GB) | 170 ms | 0.04 ms |
| cancel on send and chat open (4000 chats, 377 MB) | 200 ms | 0.04 ms |
| sidebar chat list (15000 chats, 1.26 GB) | 157 ms | 1.8 ms |
| folder unread badges (15000 chats, 1.4 GB) | 54 ms | 0.2 ms |
PostgreSQL 17 serves all of them as index-only scans with no sort node. Exercised through fresh install, upgrade with seeded data, downgrade and re-upgrade on SQLite and PostgreSQL 17.
Fixes#27622
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Exporting workspace models loaded every model row, built a full response object with its owner for each, and only then dropped the ones the caller may not see. On a large model table that made the export endpoint slow in proportion to models the user cannot even access.
The owner-or-grant check now happens in the query itself, reusing the permission filter this file already applies to the paginated list endpoint, so only visible rows are ever hydrated. The by-user wrapper had one caller left and is gone with it.
Measured with 500 workspace models of which 3 are visible to the caller: 5 queries and ~12.7 ms before, 4 queries and ~2.8 ms after. The resulting set is unchanged for owner, public, direct-user, group and multi-grant entries, and base model entries stay excluded as before.
Every streamed event that persists to a chat (status updates, citations,
file attachments, message content) serialized the entire conversation JSON
three times: a null-byte check of the stored row, a second sanitize of the
whole blob after merging in the event payload and the flush of the UPDATE
itself. The middle pass rescans megabytes of already-clean history for null
bytes that can only come from the small incoming payload, so long chats pay
for their full history on every single event.
The write paths now sanitize just the incoming message, message id and
status dict and keep the row-level sanitize, so legacy rows with null bytes
still self-heal as before. Median per-event write time (sqlite, orjson):
1 MB chat 15.0 ms to 11.1 ms, 4 MB 65.2 ms to 52.4 ms, 10 MB 159.9 ms to
124.5 ms, roughly 20 percent less per event. As a side effect the
chat_message dual write now receives the sanitized message; previously null
bytes in non-content fields were cleaned in the blob but written raw to
chat_message, which failed that insert on PostgreSQL. Verified byte-identical
rows against the previous implementation across nine scenarios covering null
bytes in every input, legacy dirty rows, a missing title and a NULL chat
column.
Listing a user's folders re-checks which entries they may still see, and it resolved their group membership again for every folder, then again inside the collection and note branches for every entry. A comment in that helper claims one membership fetch for the whole listing, but the caller invokes it once per folder, so the claim never held.
The listing now resolves membership once, and only when some folder actually carries entries, then threads it through the file, collection and note checks. Callers that do not supply it are unchanged and still resolve for themselves.
Measured with twenty folders holding six files, two knowledge bases and two notes each: 245 queries and ~145 ms before, 186 and ~117 ms after. The folders returned, and the entries the integrity pass writes back, are unchanged. That was checked against entries the caller owns, entries shared through a group, entries shared with nobody, another user's files, and an unrecognised entry type.
A calendar event's `meta` is a free-form dict, so `meta.alert_minutes` can hold any JSON type, while the upcoming-events lookup assumed it was a number and compared it directly. It now ignores a value that is not numeric and falls back to the default alert window for that event.
Handled on the read side rather than on the write path so events already stored with a non-numeric value are covered too. Numeric values are untouched, including the negative "no alert" sentinel.
Checking whether a user may reach a file loaded and validated every workspace model that user can access, then scanned each model's knowledge list in Python for one file id. Folder listings run that check once per file, so opening a folder of twenty files rebuilt the whole accessible-model set twenty times, and the same check sits on every retrieval and download path.
The lookup now runs the other way round: the database returns the models that attach the file, and only those are access-checked. The text match on the metadata column is a prefilter and the knowledge entries still decide, so a file id that merely appears in a description grants nothing; file ids are server-generated uuids, so the match can only be too wide, never too narrow.
Measured with 500 accessible workspace models: a single check drops from 9 queries and ~20 ms to 6 and ~2.6 ms, and a twenty-file folder listing from 180 queries and ~680 ms to 120 and ~56 ms. A 72-case matrix over owner, public, direct-user and group grants, for both read and write, returns exactly what it returned before, and write still requires the model owner to own the file. The check also no longer writes to the database while answering a read-only question.
Listing skills ran one database query per skill in the instance. A non-admin opening the list on a workspace with 500 skills issued over 500 queries, the paginated list re-resolved the caller's group membership once per row, and every chat message carrying a skill loaded every skill the user can read, full body and owner included, to use the two or three it actually referenced.
Skills now arrive already filtered: the owner-or-grant check runs in the query as an EXISTS subquery, the same way prompts and the search endpoints already do it, the per-item write flag uses the existing batch grant lookup, and the chat path asks only for the skill ids the request names.
Measured with 500 skills of which 3 are visible to the caller: 504 queries and ~300 ms before, 4 queries and ~2.6 ms after. The resulting set is unchanged for owner, public, direct-user, group and multi-grant entries, for both read and write.
Three methods on KnowledgeTable have no callers anywhere in the repository. get_knowledge_bases_by_user_id loaded every knowledge base and filtered them in Python, which search_knowledge_bases already does in SQL with pagination. get_knowledge_by_id_and_user_id duplicates check_access_by_user_id with the permission hardcoded to write. update_knowledge_data_by_id writes a data column that a migration dropped, so it could only ever raise and return None through its own except block.
What remains is one per-entry access helper and one SQL-filtered list path, so nobody reaches for the slower or the broken variant by accident.
No behaviour change.
Opening the shared folder list fetched every shared folder in its own query, fetched a chunk of them a second time to walk their children, and looked up each distinct owner separately. With forty folders shared with a user that is over a hundred queries before any subtree work starts.
The folders and their owners now come back in one query each, and the inheritance pass reuses the rows already in hand. Both folder listings also gained an explicit order: the sidebar merges shared subfolders in response order without sorting them, and neither query had an ORDER BY, so on Postgres a folder rename could reshuffle its siblings.
Measured with forty shared folders and no subtrees: 181 queries and ~105 ms before, 92 and ~66 ms after. With subtrees attached, 203 folders in total, it is 341 queries before against 252 after; the remainder is the recursive child walk, which this change deliberately leaves alone. The returned set, permissions and owner names are unchanged, including for a grant pointing at a deleted folder row, a folder the caller owns that is also shared with them, a folder whose owner record is gone, and a child folder that is itself directly shared.
Saving a chat rewrote its message rows one at a time. Each message took its own session out of the pool and committed on its own, and the save endpoint hands over the entire merged history rather than only what changed, so a two hundred message chat cost two hundred sessions and two hundred commits on every save.
The messages now go through a single select and a single commit. The field mapping for the insert and the update branch moved into two small helpers, so the batch and the single-message path cannot drift apart.
Measured on a two hundred message chat with one message edited: 201 queries and 200 transactions before, 2 queries and 1 transaction after, ~149 ms against ~6 ms. Re-saving an unchanged history now costs one select and no writes at all.
One behaviour change worth stating: a message the database cannot store used to be skipped on its own, and now costs the rest of that same save. This table is a rebuildable fast path, so the reader falls back to the history on the chat row and re-triggers the backfill, and the next save reconciles everything still present. A per-message retry was tried and dropped, because a commit that lands but still raises would re-apply the usage merge and double the recorded token counts.
Three searches LIKE against cast(json_col AS text), which means they have to match
bytes a JSON encoder wrote. Encoders disagree on non-ASCII: stdlib escapes it to
\uXXXX, orjson writes it raw. Which one produced a row depends on the codec in force
when it was written, so any single pattern finds only half the table.
models.py hard-codes the stdlib spelling, with a comment asserting SQLite stores
JSON via json.dumps(ensure_ascii=True). Model.meta is a JSONField, which has
serialised through JSONCodec since ENABLE_ORJSON was introduced, so on that setting
it stores raw UTF-8 and the escaped pattern matches nothing: non-ASCII workspace
model tag search is broken today. prompts.py and automations.py hard-code the
opposite spelling and miss rows written the other way.
json_text_variants returns both spellings a string can take inside serialised JSON,
collapsing to one for ASCII, and the three call sites OR over them. Rows written
under either setting are now found under either setting, which also covers a
database holding a mix of the two.
Case handling is unchanged. models.py keeps matching non-ASCII tags case-sensitively
on SQLite, whose LOWER() is ASCII-only and would not fold the stored text the way
str.lower() folds the tag. ASCII tags collapse to a single variant and take exactly
the query they took before.
Verified on SQLite across every combination of codec-that-wrote-the-row and
codec-the-app-is-running, for an ASCII and a CJK tag, over all three call sites: 24
of 24 match, against 12 of 24 before. Quoting still bounds whole-tag matches, so
searching "weather" does not match a row tagged "weathervane".
Co-authored-by: Claude <noreply@anthropic.com>
POST /api/v1/models/sync only worked when every model in the payload was new. As soon as one id already existed, the whole call blew up and the endpoint still answered HTTP 200 with an empty list, so nothing was updated and well-behaved clients saw a success. Only a first-ever sync into an empty catalogue went through.
The update branch splatted the model dump (which already carries user_id and updated_at) and then passed both again as explicit keyword arguments, which is a duplicate-keyword TypeError before SQLAlchemy ever sees it. The insert branch right below merged the same values into a dict first, so it never collided.
Fixed by building that dict once and using it for both branches, matching how sync_functions already does it. Left the broad exception handler alone: it is the reason the failure was silent, but changing the error contract of sync_models is a separate call.
Fixes#28033
Both the OAuth and SCIM user lookups now compare the nested JSON value with SQLAlchemy's subscript operator, which emits the correct SQL for each supported database on its own. This replaces the hand-written sqlite and postgresql branches and the column-level contains() call they used.
