Patrick Buckley c0be383f99 refactor(doctor): replace turnstone-bootstrap with turnstone-doctor (#718)
* refactor(doctor): replace turnstone-bootstrap with turnstone-doctor

turnstone-bootstrap was an LLM setup wizard for Day-0; run.sh now owns install.
Repurpose its LLM/conversation plumbing into turnstone-doctor — a diagnose-only
tool for a running cluster.

- Preflight detects the install kind (docker-compose/systemd/pip/source) from
  config.toml + TURNSTONE_* env, with secret redaction.
- Self-configuring brain resolves the cluster's own model from config/env/storage
  read-only (no migrations, no create_all), falling back to interactive
  selection; the attempt itself is the LLM-backend health check.
- Deterministic version check: installed version, cluster drift via the console's
  authoritative /health, and latest upstream stable/experimental (offline-safe).
- Read-only diagnostic tools (read_file, compose/systemd/journal, http_health,
  check_llm_backend, node_health, finish) behind one secret-scrubbing chokepoint;
  no generic shell, so read-only is structural.
- node_health reaches a node the right way for the detected install kind
  (exec-into-container for compose, direct HTTP otherwise), overridable per node
  for mixed clusters.
- mTLS-aware: forwards [database] SSL params and reports node-mesh mTLS instead of
  mislabelling healthy nodes "unreachable".

init_storage gains a backward-compatible create_tables override for read-only
opens. Entry point turnstone-bootstrap -> turnstone-doctor; README/QUICKSTART/
architecture/docker docs, the bundled compose header, run.sh, and the CI smoke
updated. CHANGELOG deferred.

* fix(doctor): address Copilot + CodeQL review findings on #718

Validated all seven review findings (none false positives) and fixed:

- check_llm_backend now applies the same scheme / metadata-host guard as
  http_health (extracted to _assert_safe_http_url), so a model-supplied
  base_url can't be steered at the cloud metadata endpoint or a file:// URL.
- node_health no longer double-appends the default port when the operator
  passes host:port (regression: 10.0.0.5:8081 -> http://10.0.0.5:8081:8080).
- node_health install_type enum uses "git-source" to match the label the
  rest of the module and the prompt/report show the model (a schema-strict
  provider would otherwise reject the value the model is told to use).
- _read_api_creds takes base_url + api_key as a unit from the first config
  source that defines either field, then env-fills, instead of splicing the
  two across different config files into a pair that exists in no real config.
- _mask_secrets masks assignment-shaped content inside comment lines, so a
  commented-out real secret can't leak through read_file / the report; prose
  comments (no KEY=value shape) still pass through untouched.
- drop the mixed import styles CodeQL flagged in doctor.py and test_doctor.py.

Adds 5 tests; ruff + mypy clean; full doctor suite passes (129).
2026-06-26 04:57:20 -07:00
2026-06-25 19:17:12 -07:00

Turnstone

CI PyPI Python License Discord

Self-hosted, local-first orchestration for tool-using AI agents. Give LLMs real tools — shell, files, search, web — and run them across your own cluster with direct HTTP routing and interactive interfaces. Your code, your models, your data stay on hardware you control: no telemetry, no phone-home.

Turnstone coordinator — parallel tool batches with judge-graded approval and child workstream tracking

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

What is a harness?

 :  s_{n+1} ~ T(s_n)   for n < τ*,    T = ρ ∘ (M_W ∘ π, E)

the hypothesis →

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.

  • Local-first & private — runs entirely on hardware you control, with no telemetry and no phone-home. Point it at local models (vLLM, llama.cpp) or commercial APIs you hold the keys to — your prompts and data never transit a third party you didn't choose.
  • Bring your own models — OpenAI-compatible APIs (vLLM, llama.cpp, NIM), the Anthropic Messages API, and Google Gemini, mixed freely per role
  • Interactive sessions — terminal CLI or browser UI with parallel workstreams
  • Cluster dashboard — real-time view of every node and workstream, with a rendezvous routing proxy
  • Intent validation — an LLM judge (your model) grades every tool call with a risk assessment and evidence before it runs
  • MCP support — external tool servers with native deferred loading (Anthropic/OpenAI) or BM25 fallback
  • Team controls when you need them — optional RBAC, SSO, tool policies, and audit logs, all stored in your own database

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
turnstone-console --port 8090

For PostgreSQL (recommended for production):

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

One-line install — autodetects Ubuntu/Debian, Fedora/RHEL, Arch, and WSL, installs git + Docker if missing, generates secrets, and starts the stack:

curl -fsSL https://raw.githubusercontent.com/turnstonelabs/turnstone/main/run.sh | bash

Or, if you already have Docker, clone the repo and run it yourself:

docker compose up

That builds one image and brings up a full local cluster — PostgreSQL, console, Caddy, channel gateway, and 10 server nodes — with no .env required (it ships with insecure dev defaults). Open the dashboard at https://localhost:8443 (Caddy serves it over TLS with its own local CA — trust it once). Nodes boot without an LLM; add model backends from the console UI.

For production (released images from ghcr.io, real secrets required), use the bundled stack: docker compose -f turnstone/deploy/compose.yaml up.

See QUICKSTART.md for the install + troubleshooting walkthrough and docs/docker.md for Docker configuration.

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-doctor LLM-backed cluster diagnostics

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: Discord / Slack channel integrations (pip install turnstone[discord,slack])
  • Git LFS for cloning (diagram PNGs)

Community

Questions, ideas, or want to show what you're building? Join us on Discord: discord.gg/Nh3bWMacaq.

License

Apache License 2.0, as of version 1.6.0. Versions 1.5.x and earlier remain under the Business Source License 1.1 they shipped with.

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