Patrick Buckley 7e33fc68bb fix(approve): apply /review feedback on inline child approvals
Critical:
- coordinator.js RISK_SEVERITY accepted 'crit' only; production
  emits 'critical' (per turnstone/core/judge.py:1556 + heuristic
  seeds). A risk_level=='critical' verdict ranked as 0 and
  rendered with .risk.low (green) styling, never triggering
  the crit-risk auto-expand. Now accepts both aliases. Unknown
  risk_level falls back to rank 2 ('high') so future schema
  drift fails *safe* (over-alert) instead of silently
  downgrading. Pill ternary handles both 'crit' and 'critical'
  alias to the existing .risk.crit class.

Major:
- Urgent live-badge flush now coalesces N urgent calls in the
  same JS tick into one bulk request via queueMicrotask, instead
  of firing N single-id fetches. The motivating 10-children-
  pending-bash scenario in the design doc now lands on one bulk
  /v1/api/cluster/ws/live request.
- Test coverage gap: added test_session_ui_base.py cases for
  POLICY-BLOCKED (item.error + needs_approval=False) and
  judge-unavailable (no verdict + no judge_pending) matrix rows.
  Added literal-string assertions to the smoke list in
  test_coordinator_page.py so a refactor dropping either branch
  surfaces at test-time.

Minor batch (4 coord.js + 1 CSS + 1 fake-divergence):
- 409 stale-call_id path re-enables both buttons before return
  (urgent fetch is best-effort; could also fail).
- judgePending pill no longer conflicts with a present heuristic
  verdict — guard changed from !judge to !verdict.
- Empty <div class="approval-reasoning"> no longer appended when
  reasoning is absent but evidence is present (evidence still
  renders inside the disclosure).
- Dead .ch-row .approval-pill.rec-* CSS rules removed (JS never
  combines those classes). Recommendation chip in the disclosure
  footer now has its own scoped rules so the chip is actually
  styled.
- _FakeUI.serialize_pending_approval_detail call_id selection
  aligned to the real impl's "first non-empty" semantics.
- liveBadgeCache reconnect cleanup now preserves permanent
  (403/404) entries — denied users no longer pay one wasted
  bulk fetch per denied id per reconnect.

All 4465 non-live tests pass. Ruff + mypy clean. node --check OK.
2026-04-27 11:41:14 -07:00
2026-04-23 18:46:15 -07:00
2026-04-27 07:50:27 -07:00

Turnstone

CI PyPI Python License

Multi-node AI orchestration platform. Deploy tool-using AI agents across a cluster of servers with direct HTTP routing, interactive interfaces, and enterprise governance.

Turnstone console — multi-workstream AI orchestration with mermaid diagrams

Named after the Ruddy Turnstone (Arenaria interpres) — a shorebird that flips stones to discover what's hiding underneath.

Release Tracks

Track Install Docker Description
Stable pip install turnstone ghcr.io/turnstonelabs/turnstone:stable Production-grade. Bugfixes only.
Experimental pip install turnstone --pre ghcr.io/turnstonelabs/turnstone:experimental New features. May have rough edges.

See docs/releasing.md for the full release process.

What it does

Turnstone gives LLMs tools — shell, files, search, web, planning — and orchestrates multi-turn conversations where the model investigates, acts, and reports.

  • Interactive sessions — terminal CLI or browser UI with parallel workstreams
  • Cluster dashboard — real-time view of all nodes and workstreams with console routing proxy
  • Intent validation — LLM judge evaluates every tool call with risk assessments and evidence
  • Governance — RBAC, OIDC SSO, tool policies, skills, usage tracking, audit logs
  • Multi-provider — OpenAI-compatible APIs (vLLM, llama.cpp, NIM), Anthropic Messages API, and Google Gemini
  • MCP support — external tool servers with native deferred loading (Anthropic/OpenAI) or BM25 fallback

Turnstone system architecture

Quickstart

pip install turnstone

# Terminal REPL
turnstone --base-url http://localhost:8000/v1

# Browser UI
turnstone-server --port 8080 --base-url http://localhost:8000/v1

# Cluster dashboard
pip install turnstone[console]
turnstone-console --port 8090

For PostgreSQL (recommended for production):

pip install turnstone[postgres]
export TURNSTONE_DB_BACKEND=postgresql
export TURNSTONE_DB_URL="postgresql+psycopg://user:pass@localhost:5432/turnstone"
turnstone-server --port 8080 --base-url http://localhost:8000/v1

Docker

cp .env.example .env  # edit LLM_BASE_URL, OPENAI_API_KEY, etc.
docker compose --profile production up

See QUICKSTART.md for the bootstrap wizard and docs/docker.md for Docker configuration and profiles.

Programmatic (SDK)

from turnstone.sdk import TurnstoneServer

with TurnstoneServer("http://localhost:8080", token="tok_xxx") as client:
    ws = client.create_workstream(name="demo")
    result = client.send_and_wait("Analyze the error logs", ws.ws_id, auto_approve=True)
    print(result.content)

Tools

Built-in tools for shell, files, search, web, memory, notifications, and autonomous sub-agents — plus external tools via MCP with native deferred loading. See docs/tools.md for the full reference and docs/mcp-registry.md for MCP configuration.

Architecture

Single-node: Client → Server (direct HTTP + SSE). No external dependencies beyond the database.

Multi-node: Client → Console (rendezvous routing proxy) → Server nodes. The console picks the target node for each workstream via rendezvous (HRW) hashing over the live service registry — pure function of (ws_id, live_nodes), no stored bucket state, deterministic across readers. A node join or drop only re-routes the keys that score highest on the affected node.

Component Purpose
turnstone Terminal CLI (REPL)
turnstone-server Web UI + REST API + SSE events
turnstone-console Cluster dashboard + routing proxy + admin panel
turnstone-channel Channel gateway (Discord and Slack adapters)
turnstone-admin User/token management CLI
turnstone-eval Eval harness for prompt/tool optimization
turnstone-bootstrap LLM-guided setup wizard

Diagrams

UML diagrams in docs/diagrams/:

Diagram Description
System Context Components and external dependencies
Package Structure Python modules and dependency graph
Core Engine SessionUI, ChatSession, LLMProvider
Conversation Turn Message lifecycle through the engine
Tool Pipeline Prepare / approve / execute
Workstream States State machine transitions
Console Data Flow Dashboard data collection
Deployment Docker Compose topology
Auth JWT, scopes, login flows
Channels Discord / Slack adapters + routing
Judge Intent validation pipeline
OIDC SSO authorization code flow

Documentation

Topic Link
Configuration reference docs/settings.md
API reference docs/api-reference.md
Docker deployment docs/docker.md
Intent validation (judge) docs/judge.md
Governance & RBAC docs/governance.md
OIDC SSO docs/oidc.md
TLS / mTLS docs/tls.md
Channel integrations docs/channels.md
Console dashboard docs/console.md
Eval harness docs/eval.md
Tools reference docs/tools.md
MCP integration docs/mcp-registry.md

Requirements

  • Python 3.11+
  • An OpenAI-compatible API endpoint, Anthropic API key, or Google Gemini API key
  • Optional: PostgreSQL (pip install turnstone[postgres]), Anthropic (pip install turnstone[anthropic])
  • Git LFS for cloning (diagram PNGs)

License

Business Source License 1.1 — free for all use except hosting as a managed service. Converts to Apache 2.0 on 2030-03-01.

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