turnstone 1.2.0a3

Multi-node AI orchestration platform with tool use, agent routing, and cluster simulation.

Turnstone

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

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) and Anthropic Messages API
• MCP support — external tool servers with native deferred loading (Anthropic/OpenAI) or BM25 fallback

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

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.md for MCP configuration.

Architecture

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

Multi-node: Client → Console (hash ring routing proxy) → Server nodes. The console maintains a 65536-entry bucket cache for O(1) workstream routing. A rebalancer daemon redistributes buckets when nodes join or leave.

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, with adapters for Slack/Teams planned)
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 adapter + 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.md

Requirements

• Python 3.11+
• An OpenAI-compatible API endpoint or Anthropic 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.