feat(optimizer): stage and goal selection controls

fix(bm25): strict n-gram remove guidance

feat(optimizer): add diff highlighting

optimizer: per-goal deficit-based iteration and candidate budget

refactor(optimizer): apply unified per-goal iteration budget across all stages

fix(optimizer): keep BERT stage from plateau auto-skip

fix(optimizer): require bert target for each phrase

fix(ui): apply optimized Title from analysis snapshot + resolved_title in metrics

fix(optimizer): reject title goal in _llm_edit_chunk; doc deploy check for title_rewrite

fix(optimizer): title stage rewrites Title field only, return optimized_title

fix(optimizer): define _emit before first call (avoid UnboundLocalError)

Optimizer: SSE log panel + static app.js (SES-safe nv), no global loader; HF_SES doc

Revert "Optimizer: SSE progress, cancel job with partial result, UI progress card"

Optimizer: SSE progress, cancel job with partial result, UI progress card

Revert to pre-progress-bar (ad42da6): remove SSE endpoint, optimizer callbacks, progress UI

Optimizer: SSE progress stream + UI progress bar during LLM run

N-gram: rank by Freq/Avg, extra loop budget, overlapping window chunking

Enforce per-term ngram loop and underrepresented-only targeting.

Align n-gram selection rules across summary and optimizer.

Implement n-gram tolerance stage rules and optimizer principles doc.

Add configurable BERT stage target and stage visibility in optimizer.

Implement staged multi-objective optimization flow after BERT.

Add ensemble phrase strategy mode for optimizer.

Add configurable phrase strategy mode for LLM optimizer.

Add multi-objective candidate utility for optimizer decisions.

Revert "Improve universal chunk selection with structural and diversity signals."

Improve universal chunk selection with structural and diversity signals.

Refine LLM prompt for semantic-vector chunk optimization.

Apply local-first accumulation for chunk-level optimizer progress.

Accept incremental BERT phrase gains during optimization.

Add semantic gap tolerance and detailed gap attribution.

Improve optimizer attribution and multi-edit batch search.

Add deep LLM-input diagnostics for chunk optimization debugging.

Implement two-stage optimizer acceptance with multi-chunk batching.

Improve optimizer span selection to avoid repeated chunk edits.

Improve optimizer candidate validation and BERT goal tracking.

Implement cascade state-machine for optimizer edit escalation

Add detailed optimizer debug trace for candidate-level visibility

Tune optimizer acceptance policy and add optimization modes

Add LLM optimizer tab with iterative constrained text improvements