Fourteen modules import `json` without using it. Ruff flags every one with F401, and a word-boundary search for `json` in each file matches only the import line itself, including inside strings, comments and annotations.
Two exclusions, both deliberate. Migration files are left alone: the import is equally dead there, but those files are frozen history and not worth the churn. `models/chats.py` has the same dead import and is handled in its own change, so it is skipped here to avoid two changes touching the same line.
No behaviour change.
Tools.get_tools(defer_content=True) contained the literal dead statement "stmt = stmt": the deferral was a no-op, so every tools listing loaded the full Python source of every tool (five caller sites pass defer_content=True expecting the optimization: the tools list endpoints and the user and group permission overviews). The listing now selects every column except content, and ToolModel.content becomes optional to represent deferred rows; router projections are content-less response models, so nothing downstream reads the source on these paths.
On top of that, get_tools_by_user_id issued one grant query per non-owned tool and Knowledges.get_knowledge_bases_by_user_id did the same per knowledge base (the latter also sits inside per-file access checks). Both now resolve grants for all non-owned rows in a single get_accessible_resource_ids call, the same batch helper the model listing already uses.
Benchmark (real SQLite DB):
| metric | before | after |
| --- | --- | --- |
| tools listing, 33 tools x ~200 KB source | 5.13 ms | 3.18 ms |
| grant queries per accessible-tools call, N non-owned tools | N | 1 |
| grant queries per accessible-KBs call, N non-owned KBs | N | 1 |
The listing row scales with source size; on Postgres the deferral additionally avoids shipping every tool's source over the wire per listing, and each removed grant query was a real round trip.
Functionally verified: deferred listings match full listings field for field with content None, grants included and router projections working; access filtering returns exactly owned plus granted tools and knowledge bases and nothing for strangers; full (non-deferred) reads still carry the source.
Knowledges.get_file_metadatas_by_id fetched full File rows, whose data column carries the entire extracted text of each document, validated each into a FileModel and then threw everything except id, hash, meta and the timestamps away. The function backs every knowledge base detail view and runs again after every file add or remove (eight call sites in the knowledge router), so rendering a filename list for a 50-file knowledge base parsed tens of megabytes of JSON per request.
The listing now selects exactly the five columns the response needs, joined through KnowledgeFile, mirroring the column-only helper that already existed in the files model for id-based lookups.
Benchmark (real SQLite DB, 50 files with ~200 KB extracted text each):
| metric | before | after |
| --- | --- | --- |
| KB file metadata listing | 14.2 ms | 1.20 ms |
The gap widens linearly with file size and count since extracted contents no longer get read, parsed or validated at all.
Functionally verified: output matches the old implementation field for field on all 50 files and an unknown knowledge base still returns an empty list.
This fix restores and extends the username/email search functionality across workspace pages that was originally added in PR #14002. The issue was that:
1. The backend search functions for Models and Knowledge only searched `User.name` and `User.email`, but not `User.username`
2. The Functions admin page lacked user search entirely
Changes made:
Added User.username to backend search conditions for Models and Knowledge pages
Added complete user search (name, email, username) to the Functions admin page client-side filter
- Pre-fetch user group IDs in get_*_by_user_id methods across models layer
- Pass user_group_ids to has_access to avoid repeated group queries
- Reduce query count from 1+N to 1+1 pattern for access control validation
- Apply consistent optimization across knowledge, models, notes, prompts, and tools
Signed-off-by: Sihyeon Jang <sihyeon.jang@navercorp.com>
- Replace individual user queries with batch fetching
- Use single query to fetch all required users at once
- Implement O(1) user lookup with dictionary mapping
- Reduce query count from 1+N to 1+1 pattern
Signed-off-by: Sihyeon Jang <sihyeon.jang@navercorp.com>
Classic298