The process cwd was nowhere in the model's context: shells start in the inherited process cwd (spawn_group_leader passes no cwd), relative file paths resolve against it, but nothing told the model where it was standing — in stock Docker every shell ran in /data while user files sat in the /workspace mount, and the model's only recourse was to probe with pwd (#857, #833). Lower both facts into the tool schemas, where they gate intrinsically on tool availability (a persona without fs tools carries no note, and coordinator envelopes are untouched): - tools/*.json: cwd_note/workspace_note metadata templates on bash, read_file, write_file, edit_file, search, diff_file; bash also states the fresh-shell-per-call semantics (cd does not persist) and drops a stale reference to the removed man tool. - tools.apply_cwd_context(): renders the notes into descriptions; deep-copies noted tools (the fs dicts are shared across TOOLS/INTERACTIVE_TOOLS/TASK_AGENT_TOOLS and aliased through merge_mcp_tools), passes note-less tools through by reference. - ChatSession._apply_cwd_notes(): wraps every fresh interactive build of _tools AND _task_tools (construction, MCP catalog change, MCP disconnect) — assignment-time, so the wire tools block stays byte-stable for provider prompt caches. os.getcwd() is OSError-guarded (MCP rebuilds run on a background thread; eval tears down its workdir); the workspace hint drops when the dir is missing or equals the cwd. Task-agent sub-agents carry their own notes via _task_tools, independent of parent persona visibility. - config.get_workspace_dir(): [tools] workspace_dir with TURNSTONE_WORKSPACE env fallback (searxng pattern), informational only — no chdir, no path confinement (per-workstream working-dir grants are a separate planned feature). - Dockerfile: ENV TURNSTONE_WORKSPACE=/workspace so stock deployments surface the mount with zero operator config. - docs/docker.md: document the /data working directory, the working_dir: /workspace compose override as the operator-level fix, and the SQLite-fallback-DB-in-cwd caveat. Closes #857
Turnstone
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.
Named after the Ruddy Turnstone (Arenaria interpres) — a shorebird that flips stones to discover what's hiding underneath.
What is a harness?
ℋ : s_{n+1} ~ T(s_n) for n < τ*, T = ρ ∘ (M_W ∘ π, E)
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
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 |
Headless measurement — scores tool-use against expected actions |
turnstone-optimizer |
Prompt/tool optimizer (UCB self-modify loop over the eval substrate) |
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)
Support
Turnstone is free, Apache-2.0, and self-hosted — no paid tier, no telemetry, no upsell. If it saves you time or you'd like to help keep development moving, you can sponsor the project:
❤ Sponsor Turnstone → · one-off via PayPal
Sponsorship is entirely optional and funds maintenance, new features, and infrastructure. Prefer to contribute in other ways? Filing issues, improving docs, and pull requests help just as much.
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.
