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