Commit Graph

10 Commits

Author SHA1 Message Date
c1f5fcb561 fix(admin): ops page — add section description, remove redundant footer (#107)
Adds a one-line purpose description under the Ops heading so it is clear
what the section is for (shadow policy toggles, signal replay, per-user
actions). Removes the duplicate "User-level actions" subsection whose
content is now covered by the header description.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-27 13:53:35 +00:00
bad1bb2cba feat(simulate): MLflow tracking, Airflow DAG integration, health checks for mlflow/airflow
- sim_runs schema: add judge_mode, n_policies, airflow_dag_run_id, mlflow_run_id columns
- admin health endpoint: add mlflow + airflow checks (Basic auth for Airflow API)
- admin nav: add Simulations page link; rename section label
- runner.py: optional MLflow experiment tracking; multi-policy support
- sim_dag.py: Airflow DAG for offline sim pipeline
- admin simulate page + API client methods for sim runs
- shared-types tsconfig: exclude test files from build

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-26 12:08:36 +00:00
e96ceb7ee1 feat(auth): token-based admin authentication for Playwright/CI (#105)
Add POST /api/auth/token — validates ADMIN_TOKEN env var, creates a 24h
session and sets the sid cookie so automated tools can access the admin
panel without Google OAuth. Admin login page gains a token input form.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-26 12:07:43 +00:00
4a42a6aabf feat(admin): profile freshness panel in data-quality (#81 phase B.4)
Adds a per-feature freshness summary to /admin/data-quality so the admin
can spot features that are systematically stale or never computed:

  totalEligible — distinct users with tip_views in the last 30 days
  missing       — eligible users with no row stored for the feature
  stale         — eligible users whose stored row is past its TTL

Backend exposes summarizeProfileFreshness() in profile/builder.ts; one
query per feature joins eligible users LEFT JOIN profile rows.
Coverage = (eligible − missing − stale) / eligible, colored
green/yellow/red via the new PctGood helper (high-is-good, opposite of
the existing Pct used for missing-feature/stale-token rates).

Refs #81.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-25 00:34:46 +00:00
9e96540bcc feat(admin): per-user profile view + rebuild action (#81 phase B.1)
Surfaces phase A's profile features in /admin/users/:id so we can verify
they're actually computing useful values before investing in bandit
consumption. The detail GET now includes profile rows joined with registry
metadata (name, value, age, fresh badge, ttlSec, description). Read does
NOT trigger compute — staleness must be visible. A new POST
.../profile/rebuild button force-recomputes and is audit-logged like
reset-bandit.

Refs #81.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-25 00:27:08 +00:00
aa4bdd8f09 feat(admin): LLM tip quality dashboard — per-model/prompt/kind breakdowns
/admin/reward-analytics now surfaces served count, reaction rate, and avg
reward grouped by llm_model, prompt_version, and tip_kind — closing the
loop so model/prompt iterations in M2 are legible next to the bandit
policy view. Data comes from the tip_scores columns added in ffdf707 and
tip_feedback.reward_milli; bandit-only tips show as "(bandit-only)".

Closes #92.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-24 15:24:52 +00:00
bb879c5f0f refactor(admin): drop simulations/experiments/models pages; group nav into sections
Removes the in-shell MLOps pages (experiments, models, simulations) and their
client API helpers in favour of external MLflow/Airflow links. Nav is regrouped
into Signals / Recommender status / Ops sections for clarity.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-18 14:41:17 +00:00
85367aeaa0 feat: MLOps external services, AI stack planning, admin MLOps hub
Infrastructure:
- Add `mlops` compose profile: MLflow (basic-auth, /mlflow path) + Airflow (LocalExecutor, /airflow path) + airflow-db
- infra/mlflow/basic_auth.ini for MLflow auth config
- Caddy routes /mlflow* and /airflow* inside existing o.alogins.net block (see agap_git)
- Dockerfile.admin: NEXT_PUBLIC_MLFLOW_URL / NEXT_PUBLIC_AIRFLOW_URL build args (default /mlflow, /airflow)

Admin panel:
- /admin/models: replace MLflow iframe with external link cards
- /admin/experiments: replace LinUCB stats with MLOps hub (links to MLflow experiments/models + Airflow DAGs/datasets)
- AdminShell: external nav links for MLflow ↗ and Airflow ↗ under MLOps section

Docs & planning:
- README: new AI stack section (Ollama/LiteLLM/OpenWebUI three-tier, tip generation pipeline, model aliases)
- README: Phase 2 expanded with AI infra issues (#86-#93) and granular pipeline breakdown
- README: Phase 4 expanded with LLM MLOps items (#94-#97)
- CLAUDE.md: AI stack section, updated current phase (M1 shipped / M2 in progress), compose profiles, updated What NOT to do
- docs/architecture/overview.md: AI stack section, updated decision flow diagram for Phase 2 LLM pipeline
- ADR-0006: updated to reflect external services (path-based, not embedded)
- Gitea issues #86-#97 created (M2: AI infra + pipeline; M4: LLM MLOps)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-17 08:20:44 +00:00
faf44c18fc feat: ε-greedy v1 as active policy; dwell-time reward inference; offline sim framework
- Promote egreedy-v1 to active serving policy (ADR-0007): /score/egreedy + /reward/egreedy
  replaces linucb-v1 endpoints after offline sim shows +10.7% mean reward (−0.548 vs −0.606)
- Replace explicit helpful/not_helpful feedback with dwell-time inferred reward (inferReward):
  dismiss=−1.0, snooze=+0.1, done<15s=−0.3, done 15s–2min=+1.0, done 2–10min=+0.6, done>10min=+0.3
- Add ml/serving ε-greedy endpoints: /score/egreedy, /reward/egreedy, /stats/egreedy/{user_id}
  with d=7 feature vector (base 5 + sin/cos day-of-week encoding)
- Add offline simulation framework (ml/experiments/sim): rule/LLM/claude-code judges,
  two-phase score+reward, synthetic personas, task generator; results stored in sim_runs/sim_events
- Add /admin/simulations page: start runs, live-poll status, reward curve SVG, action/persona tables
- Fix egreedy day_of_week training skew: reward endpoint now uses actual dow instead of hardcoded 0
- Fix runner.py proxy bypass: httpx.Client(trust_env=False) for localhost ML calls
- Add dwellMs to TipFeedbackEvent contract and bus.test.ts fixture
- Schema: sim_runs, sim_events tables; tip_feedback gains dwell_ms, reward_milli columns
- ADR-0006: admin console framework; ADR-0007: egreedy-v1 policy selection rationale

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 07:44:37 +00:00
e62c726ea4 feat: M1 admin console — all 10 remaining pages + signal/quality/ops infrastructure
Admin console (issues #63–72):
- Event stream viewer: live-tail ring buffer (500 events) with subject/user filters
- Feature store browser: per-user feature vector history from ml/serving
- Model registry panel: MLflow embed at /admin/models
- Experiment dashboard: LinUCB per-user stats (pulls, reward, θ) + bandit reset
- Recommendation log: per-tip explainability (policy, score, features, latency)
- Reward analytics: daily reaction breakdown + per-policy compare
- Data quality widget: missing-feature rate, stale-token rate, daily completeness
- Ops actions: replay-signal, policy enable/disable; user actions link to Users page
- SQL runner: read-only SELECT runner with saved queries
- Health rollup: fan-out to api/ml/sqlite/event-bus with auto-refresh

Backend:
- tip_scores table: logs features+policy+score+latency at every scoring call (#67)
- saved_queries table: per-admin saved SQL (#71)
- Event bus: 500-event ring buffer + tail() API (#63)
- Admin routes: /events, /tips, /reward-analytics, /data-quality, /health,
  /policies, /replay-signal, /sql, /saved-queries endpoints
- /api/ml/* admin-gated proxy to ml/serving (#64, #66)
- Shadow-policy registry in recommender (#56)

ML serving:
- /reset/{user_id}: clear bandit state + feature history (#66)
- /stats/{user_id}: pulls, cumulative reward, estimated mean, θ (#66)
- /features/{user_id}: last 100 feature vectors logged at scoring time (#64)
- Meta (pulls, rewards) persisted alongside A/b matrices

Web:
- Tip action sheet adds Helpful / Not helpful buttons (#62)
- TipFeedback type extended with helpful/not_helpful actions
- Rewards mapped: helpful=+0.5, not_helpful=−0.5

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-16 03:56:48 +00:00