PR #498 round-robin review surfaced 5 findings. 4 applied; 1 rejected with rationale. Applied * **Copilot finding 5** (history_decoration.py:341): dispatcher inspected only ``provider_content[0]['type']``. OpenAI Responses captures EVERY ``output_item.done`` event into ``provider_blocks`` (not just reasoning) — in practice the order is ``[reasoning, message, ...]`` but the API doesn't guarantee that; a hypothetical ``[message, reasoning]`` ordering would silently drop the reasoning under an index-only check. Now walks the list for the first block whose type is in ``_BLOCK_TYPE_PROVIDER_FACTORY``, then dispatches the WHOLE list to that provider's extractor. Each provider's extractor already filters internally by its own block type, so passing the full list is correct. Regression test added (``test_dispatcher_scans_past_unrecognized_first_blocks``). * **Copilot finding 3** (migration 052 docstring): the previous review-fix wave used sed to rename ``persist_reasoning`` → ``surface_persisted_reasoning`` everywhere, which mangled a historical reference in the migration docstring ("The earlier name ``surface_persisted_reasoning`` was renamed..."). Restored to point at the actual pre-rename name (``persist_reasoning``). * **Copilot finding 4** (sdk/typescript/src/events.ts:26): ``HistoryEvent`` JSDoc still referenced ``persist_reasoning`` — the sed rename only walked ``turnstone/`` and ``tests/``, missing the TypeScript SDK. Updated to ``surface_persisted_reasoning``. Also widened the comment to cover all three reasoning-bearing block types (Anthropic ``thinking``, OpenAI Responses ``reasoning``, synthetic ``reasoning_text``) instead of mentioning only Anthropic. * **github-code-quality finding** (session.py:1120): ``_resolve_server_type`` had a bare ``except Exception: pass``. Replaced with a ``log.debug(..., exc_info=True)`` + explanatory comment. Behaviour unchanged (still returns ``""`` on any lookup failure); failures are now observable under DEBUG triage. Rejected (with rationale) * **github-code-quality finding** (_protocol.py:265): ``extract_reasoning_text``'s body is ``...`` per ``LLMProvider`` Protocol convention. Every method in the file uses ``...`` (PEP 544 idiomatic Protocol style). Changing only this one to ``raise NotImplementedError`` would be inconsistent with the rest of the file. CodeQL's "statement has no effect" warning is technically correct for ``...`` as a standalone expression but ignores the documented Python Protocol convention. No fix. Docs sync * docs/api-reference.md: ``history`` SSE event message-shape table gains the optional ``reasoning`` field. * docs/architecture.md: ``ModelCapabilities`` row in the type table gains ``supports_reasoning_replay``; ``StreamChunk`` and ``CompletionResult`` rows gain the existing ``provider_blocks`` field (was missing pre-PR). New "Per-model reasoning persistence" subsection under the Models config section, documenting the two flags + capability gate + three reasoning paths + cross-provider shape filter. * docs/settings.md: new "Reasoning persistence (per-model)" subsection with the two-flag table and capability-gate note. * docs/diagrams/03-core-engine-classes.puml: ``LLMProvider`` interface adds ``extract_reasoning_text`` + the new ``replay_reasoning_to_model`` kwarg; ``ModelCapabilities`` class adds ``supports_reasoning_replay``. PNG regenerated. Lint + test gate * ruff check + ruff format clean. * mypy clean (191 source files). * pytest -m 'not live' — 6116 passed (3 deselected), +1 net new test (``test_dispatcher_scans_past_unrecognized_first_blocks``).
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.
