Patrick Buckley b7b4dcc0df fix(judge): UPSERT intent_verdicts so llm_fallback upgrades land
Async LLM-tier "llm_fallback" verdicts (judge.py:1073, judge.py:1131
via _deliver_fallbacks) deliberately reuse the heuristic verdict's
``verdict_id`` so the row gets "upgraded in place" from heuristic →
llm_fallback when the LLM judge times out, is cancelled, or returns
no content.  The consumer ``_persist_intent_verdict`` was doing a
plain INSERT via ``create_intent_verdict``, hitting the
``intent_verdicts_pkey`` constraint on every llm_fallback delivery.
Postgres logged the duplicate-key error; the application try/except
swallowed it at log.debug — so the row never actually got upgraded
and the LLM judge's annotation ("(LLM judge did not return a
verdict)") was lost.

The collision rate exploded on stable/1.5 smoke tests because
PR #527 (just merged) added two new heuristic-INSERT paths in the
auto-approve early-return branches of ``approve_tools`` — previously
those branches dropped heuristic verdicts on the floor, leaving no
row for the fallback to collide with.

Fix:
- New ``upsert_intent_verdict`` method on the storage protocol +
  sqlite + postgres impls, using dialect-specific
  ``insert(...).on_conflict_do_update(index_elements=["verdict_id"],
  set_={...})``.  Set_ clause updates ONLY the three fields that
  genuinely change between heuristic and llm_fallback: ``tier``,
  ``reasoning``, ``judge_model``.
- Every other column is excluded from set_: identity columns
  (verdict_id, ws_id, call_id, func_name, func_args), carried-
  verbatim columns (intent_summary, risk_level, confidence,
  recommendation, evidence, latency_ms), and ``user_decision``.
- ``user_decision`` exclusion is load-bearing: ``IntentVerdict
  .to_dict()`` doesn't project it, so a fallback verdict reaching
  ``_persist_intent_verdict`` carries the kwarg's ``"pending"``
  default.  If the operator already resolved the approval between
  heuristic INSERT and fallback delivery, the row's user_decision
  has been stamped to ``"approved"``/``"denied"``/``"timeout"`` (or
  an auto-approve reason at heuristic-INSERT time per PR #527).
  Including ``user_decision`` in set_ would silently clobber that
  back to ``"pending"``.
- ``_persist_intent_verdict`` switched from ``create_*`` to
  ``upsert_*``.  Bulk path ``create_intent_verdicts_bulk`` stays as
  plain INSERT — every heuristic ``verdict_id`` is freshly minted
  in ``judge.evaluate`` so in-turn dups can't happen.  The inverse
  race (daemon-judge verdict lands BEFORE the bulk write) IS
  reachable today but its observable behavior is unchanged by the
  per-row UPSERT switch; documented at the bulk site for a future
  hardening pass.

Test coverage:
- TestIntentVerdictUpsert × 4 — fresh-id insert, conflict-upgrade,
  user_decision preservation across heuristic→approved→fallback,
  identity + carried-field preservation.
- Existing tests in test_session_ui_base.py updated to mock the
  new upsert method instead of create_intent_verdict.
2026-05-18 20:32:02 -07:00
2026-05-18 19:39:30 -07:00

Turnstone

CI PyPI Python License

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

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.

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

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
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.

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