Grades fast-model activity-label headers against a fixed corpus so
instruction changes are measured rather than eyeballed on one
conversation. This existed untracked while the continuity work was
developed; committing it because it is the only reproducible record of
WHY `ACTIVITY_INSTRUCTION` is ordered and capped the way it is.
- captured.json: 9 real production payloads pulled verbatim from Langfuse
with the headers that shipped. Irreplaceable — traces age out.
- corpus.js: 17 cases / 28 steps. The captured run replays as one
sequence, plus synthetic cases for the modes it never exercised
(all-failed, partial, parallel batches, rapid near-duplicates, entry
overflow, truncated output, error-shaped success). Multi-step cases
chain each generated label into the next step's context, which is what
makes cross-batch redundancy measurable at all.
- prompt.js: faithful port of the SDK's buildActivityLabelPrompt so
synthetic cases render the bytes production sends, plus a
previousLabelCap knob for continuity-window experiments.
- variants.js: single-factor instruction variants. The baseline is read
from the BUILT package (workspace resolution, then dist, then
LABEL_EVAL_DIST) so a variant can never be graded against a stale copy
of the shipped instruction.
- checks.js: length/punctuation/markdown/tool-echo/count-echo, plus
overlap split into `restate` (adds nothing over an earlier header) vs
`template` (same frame, new payload — often fine).
- run.js / rescore.js: live runner on the production wire shape
(max_tokens 256) and an offline re-grader, so metric fixes never
require re-spending on the API.
Results are gitignored — regenerable, and 292K of the 364K. A full sweep
is ~$0.03 per variant and ~45s.
Findings are recorded in the README, two of them counter-intuitive:
enumerating acceptable opening verbs ANCHORED the model rather than
diversifying it (Confirmed 18→23, opener diversity halved), and diverse
examples alone changed nothing. Sentence order is load-bearing, so a
tidying reshuffle of ACTIVITY_INSTRUCTION regresses real output.
* 🔧 chore: Update ESLint config, add import sorting script, Test Sharding, Bump `@librechat/agents`
* Change 'no-nested-ternary' rule from 'warn' to 'error' in ESLint config
* Add new scripts for sorting imports in the project
* Update lint-staged configuration to include import sorting
* Modify GitHub Actions workflows to support sharding for unit tests
* chore: remove nested ternary expressions
* refactor: Extract scale multiplier logic into a separate function in CircleRender component
* refactor: Simplify auto-refill rendering logic in Balance component for better readability
* refactor: Improve width style handling in DataTable components for clarity and maintainability
* chore: remove CircleRender component
* delete: Remove CircleRender component as it is no longer needed in the project
* chore: Bump @librechat/agents to version 3.2.31 and update Node.js engine requirement
* Update @librechat/agents dependency from 3.2.2 to 3.2.31 in package-lock.json, api/package.json, and packages/api/package.json
* Change Node.js engine requirement from >=20.0.0 to >=24.0.0 in @librechat/agents
* chore: Add import sorting check to ESLint CI workflow
* Implement a new job in the GitHub Actions workflow to verify import ordering on changed files.
* The job checks for changes in specific file types and reports any import order drift, providing instructions for local fixes.
