v0.1.1

Added

• Ask Genie chat overlay (behind FEATURE_GENIE_ENABLED, defaults off; requires GENIE_SPACE_ID). Floating bottom-right FAB on every page; ⌘/Ctrl+K to toggle. Sends questions to the Databricks Genie REST API on behalf of the signed-in user, polls until completion, and renders Genie's prose answer alongside a chart or table derived from the SQL it ran. The bootstrap script setup_genie_space.py provisions an ACP Analytics space with 11 Delta tables and 30 sample questions.
• Auto-detected result charts in the overlay: line (date × numeric), bar with top-15 + "Other" bucket (string × numeric), multi-series line (date × category × numeric), stacked bar with top-8 series + "Other" bucket (string × category × numeric), and donut for ≤6 categories. Y-axis uses compact formatting (1.38B, $12K); hover shows full precision; column-name hints route currency/percent formatting automatically. Date cells render as "May 16" with full ISO on hover.
• Per-route starter chips in the empty state. Routes covered: governance, agents, agent detail, ai-gateway, observability, workspaces, tools, knowledge bases, admin.
• In-chat retry on errors (re-asks the previous question), cancel button while Genie is thinking (AbortController-aware poll loop), and conversation persistence across hard refresh via sessionStorage.
• Per-user / per-group token budgets (behind FEATURE_BUDGETS_ENABLED, defaults off). Admins set a token cap per principal scoped optionally to an endpoint and a period (day / month / quarter / year). The new "Budgets" sub-tab on AI Gateway shows real-time spent vs cap with ok / warning / breached status pills, a breached-count header banner, and a token-amount input that accepts K / M / B suffixes. Spend is computed on read from gateway_usage_daily (input + output tokens) — no separate cache, no dollar conversion. For authoritative billed dollars, the Governance tab remains the source of truth.
• New Lakebase table gateway_budgets (created by setup_lakebase_tables.py); new REST surface GET/POST/PATCH/DELETE /api/v1/gateway/budgets plus GET /api/v1/gateway/budgets/alerts; admin gating via the existing require_admin dependency.

Changed

• Billing data refresh moved from app startup to the discovery workflow. New task workflows/09_discover_billing.py pulls system.billing.usage, system.billing.list_prices, and system.serving.endpoint_usage every 30 min into four Delta tables (billing_serving_daily, billing_token_daily, billing_product_daily, billing_user_endpoint_daily). 02_sync_to_lakebase.py (Phase 7) mirrors them to Lakebase and stamps billing_cache_meta.last_refreshed. The app's billing_service.py is now a read-only layer over the Lakebase cache — maybe_refresh_async()/force_refresh_async() are kept as no-op stubs for backward compatibility. Brings the billing pipeline in line with the project's discovery → Delta → Lakebase pattern and exposes per-endpoint cost data to Genie/analytics consumers via Delta.

v0.1.0

Added

• Knowledge Bases page: unified Vector Search + Lakebase monitoring with cost attribution
• Vector Search: endpoint/index discovery, sync status, health history, workload cost breakdown
• Lakebase: instance inventory, compute vs storage cost, per-workspace breakdown
• Gateway usage caching: all system.serving queries cached via workflow (zero live queries)
• User analytics caching: activity data cached via workflow
• 6 parallel discovery workflow tasks (agents, observability, knowledge bases, user analytics, gateway usage)
• All billing data cached in kb_billing_daily Lakebase table
• Recharts line charts for cost trends on Knowledge Bases page
• Trace discovery: Tier 2a (AI Gateway / Model Serving inference logs from *_payload UC tables) and Tier 2b (UC-stored MLflow traces from both *_otel_spans and trace_logs_* table formats), both account-wide via Unity Catalog SQL
• Gateway Requests panel in Observability with payload deep-dive
• Trace deep-dive view now serves UC-stored traces from the Lakebase cache (no MLflow REST round-trip)
• Trace and gateway-log time-window selectors extended to 180d / 365d

Changed

• Knowledge Bases billing reads from Lakebase cache (was live system table queries)
• Gateway usage reads from Lakebase cache (was live system table queries)
• User analytics reads from Lakebase cache (was live system table queries)
• Sidebar nav reordered: Agents → AI Gateway → Knowledge Bases → Tools → ...
• Trace discovery's visibility model and run-as principal recommendation documented in README and installation guide
• observability_trace_details lookup falls back to request_id-only when workspace_id is empty (UC traces have no owning workspace)

Fixed

• grant_sp_lakebase.py now registers the app SP correctly on Provisioned Lakebase via POST /api/2.0/database/instances/{name}/roles with identity_type=SERVICE_PRINCIPAL. The previous Provisioned-mode branch only printed a TODO message and skipped role registration, leaving operators to do it by hand — and raw psql CREATE ROLE produced a PG_ONLY role that couldn't validate Databricks-OAuth-minted passwords (every app Lakebase read failed with password authentication failed)
• 02_sync_to_lakebase.py wraps all DDL (ALTER, CREATE INDEX) in PostgreSQL savepoints so the workflow tolerates non-owner-runs without poisoning the surrounding transaction (caught failures roll back to the savepoint and the run continues)
• Installation guide documents the workflow-before-app deploy order to avoid the SP-ownership trap on fresh Lakebase instances

Notes

• Tier 3 (cross-workspace MLflow REST fan-out for default-backend traces) is on the roadmap. Until then, default-backend traces are visible only from within their owning workspace; UC-stored traces and AI Gateway logs are covered account-wide.