Janis Eccarius ac51ad09a4 feat(spark-analytics): per-row AI analysis with queue and rate-limit handling ...

- Add ⚡ button on each row (first 200) — clicking analyses that specific
  row with a chess-expert prompt tailored to the entry type (opening,
  player, etc.)
- Cache results per row so already-analysed rows skip re-requests
- Serialise all NIM requests through a promise queue to avoid bursting
- Pass 429 + Retry-After through from NIM to the browser; JS surfaces
  "Rate limited — retry in Ns" error and re-enables the button for retry
- Dataset-level "Analyse top 10 rows" now sends a per-row numbered prompt
  asking for chess-specific analysis of each entry rather than a vague
  dataset summary
- Store first 200 rows in window.DATASET.rows for client-side row access

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-06-21 17:48:10 +02:00

..

base

feat(spark-analytics): per-row AI analysis with queue and rate-limit handling

2026-06-21 17:48:10 +02:00

eu-central-1-prod

fix(spark): use file:/// so driver serves analytics.jar to executors over HTTP

2026-06-17 01:33:13 +02:00

eu-central-1-staging

chore(staging): bump analytics image to 0.7.0

2026-06-21 16:55:52 +02:00