Multi-stage /review on the full Phase 1+2+3+4 stack surfaced 9 findings (0 critical, 3 major, 5 minor, 1 nit, 1 uncertain). All applied. Major * perf-1 (session_routes.py:2402): make_history_handler ran sync storage.load_workstream_config inside async def history on the cold- workstream path, blocking the event loop on every dashboard /history request for non-resident workstreams. Every other storage call in the same handler correctly used asyncio.to_thread. Wrap the sync call in asyncio.to_thread (preserving the existing try/except so a DB failure still degrades to the conservative-default branch instead of bubbling out). * q-2 (test_reasoning_audit_log_discipline.py): the security-sensitive test (reasoning text never lands at INFO+ severity) only covered the 4 Phase 1 surfaces. Phase 2 added the strip predicate in AnthropicProvider._convert_messages and Phase 3 added 3 more code paths that touch reasoning text — none guarded. Added 4 parallel tests using the existing capture-and-walk infrastructure: OpenAIResponsesProvider.extract_reasoning_text, OpenAIChatCompletionsProvider.extract_reasoning_text, ChatSession._stream_response (drives the synth-block stamp via a fake reasoning-emitting stream), AnthropicProvider._convert_messages with replay_reasoning_to_model=False (drives the Phase 2 strip predicate). * q-1 (model_registry.py:42): the persist_reasoning flag name implied storage-control but actually gates UI rehydration only — operators flipping it could reasonably expect "stop persisting reasoning" but storage of reasoning bytes happens in provider_data regardless. Renamed everywhere to surface_persisted_reasoning: ModelConfig field, migration 052 column (renaming in-place since 052 is not yet on main), schema, MODEL_DEFINITION_MUTABLE allowlist, _postgresql.py + _sqlite.py CRUD impls, _protocol.py create_model_definition signature, 3 console_schemas Pydantic models, console/server.py admin POST + PUT, model_registry row mapper, history_decoration.py helper parameter, server.py _build_history local var, session_routes.py make_history_handler local var, sdk/events.py HistoryEvent docstring, admin.js form id + override pill label, index.html form input id + UI label + tooltip, coordinator.js (none needed), and every test that referenced the old field name. The admin tooltip now reads "Storage of reasoning bytes is unaffected by this flag — they ride in provider_data regardless" so the decoupling stays explicit at the operator surface. Minor * bug-1 (history_decoration.py:336): dispatcher discriminated on provider_content[0]["type"] only. Anthropic's redacted_thinking blocks (sealed by the safety system) can appear before, after, or interleaved with regular thinking blocks per the API docs. When a redacted block lands first, the dispatcher returned "" and the UI silently lost the surrounding thinking text. Registered "redacted_thinking" as a second key in _BLOCK_TYPE_PROVIDER_FACTORY pointing at the same AnthropicProvider factory — the existing extractor's type=="thinking" filter already correctly skips redacted blocks while walking the full list. Regression test added. * q-3 (_protocol.py:155): replay_reasoning_to_model defaults split across 9 sites — operator-side defaults to False (matches DB server_default), provider-API defaults to True (back-compat with direct callers). Original "pick False everywhere" fix would have silently flipped behaviour for any direct provider caller. Instead documented the intentional bifurcation in the Protocol's create_streaming docstring. * q-4+q-5 (_protocol.py:107 + 3 providers): MAX_REASONING_DISPLAY_BYTES was enforced via Python str slicing which counts code points, not UTF-8 bytes — 4-byte CJK/emoji glyphs would blow past the byte ceiling. Renamed to MAX_REASONING_DISPLAY_CHARS to match actual behaviour. Hoisted the 4-line truncation pattern into a shared _join_reasoning_with_cap helper in _protocol.py; each provider's extractor becomes a single line at the tail. * q-6 (tests/_session_helpers.py): _NullUI + _make_session were duplicated verbatim between test_session_replay_reasoning.py and test_session_synth_reasoning_block.py. Hoisted to a shared tests/_session_helpers.py module (importable, leading underscore so pytest doesn't try to collect it). test_model_registry.py's _make_session has a different signature (registry/model_alias args + _FakeUI) and is not a candidate for sharing. Nit * q-7 (history_decoration.py:286): _make_provider_factory used a dict-as-cell workaround for closure read-only scope. Replaced with the more idiomatic nonlocal pattern. Lint + test gate * ruff check + ruff format -- clean. * mypy -- no issues across all 191 source files. * pytest -m 'not live' -- 6115 passed (3 deselected). Net +5 tests (4 audit-log discipline + 1 redacted_thinking dispatcher). Refinements vs the dedupe output (caught during sanity rendering the report) * perf-1 fix preserved the try/except wrapper. The original "wrap in to_thread" one-liner would have let an OperationalError bubble out instead of degrading to the fallback branch. * q-3 fix explicitly documented the bifurcation rather than collapsing both sides to False. "Pick False everywhere" would silently flip back-compat behaviour for direct provider callers. * q-1 fix included the admin.js:5292 fallback site (m.persist_reasoning !== false) that the original threaded-change list missed. * q-6 fix verified the third _make_session in test_model_registry.py is structurally different (different signature + different UI helper) and intentionally NOT a dedupe target.
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), Anthropic Messages API, and Google Gemini
- 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
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.
