Patrick Buckley db0baefeb2 feat: render rich media embeds for MCP tool results (#292)
* feat: render rich media embeds for MCP tool results

Detect structured media JSON (stream_url, results, sessions) in MCP
tool output and render interactive cards instead of plain text.

Web UI: media cards with thumbnail, title, metadata, and click-to-play
video/audio. HLS via lazy-loaded hls.js with direct-stream preference.
Collapsed raw JSON (API keys redacted) for inspection.

Discord: rich embeds with proxied thumbnail images (fetched by the bot
since Discord CDN cannot reach private media servers). Search results
as numbered lists, session state as "Now Playing" cards. Stream URLs
never exposed in embeds — web_url used for safe clickable links.

CI: vendor hls.js 1.6.15 with renovate tracking and update script.

* fix: address PR #292 review — SSRF guards, streaming fetch, tests

- URL validation: reject non-http(s) schemes and userinfo in thumbnail
  URLs. Private IPs intentionally allowed (media servers are on LAN).
- Streaming fetch: use http.stream() with aiter_bytes() and a running
  byte count to enforce the 2MB cap without buffering the full response.
  Validate content-type is image/* before downloading.
- Resilience: wrap try_build_media_embed in try/except in bot.py so a
  media embed failure falls through to the code-block path.
- LICENSE: download hls.js LICENSE from npm on update instead of only
  copying from old dir.
- Tests: add 19 new tests — try_parse_media (8 cases), _is_safe_image_url
  (7 cases), embed builders (4 cases including stream_url exclusion and
  string season/episode safety).

* chore: add LICENSE file for vendored hls.js

* fix: remove ANSI escape codes from tool preview fields

Preview text (tool args, URLs, queries) was wrapped in DIM/RESET ANSI
codes at the source in session.py, which leaked into SSE events and
rendered as raw escape sequences in Discord and the web UI.

Move ANSI styling to the CLI consumer (cli.py) where it belongs. Also
escape markdown in Discord tool name titles to prevent __ from being
interpreted as underline formatting.

* fix: drop [MCP: server] prefix from tool descriptions

The prefix made MCP tools look second-class compared to builtins,
causing models to hesitate using them. The server name is already
encoded in the tool name (mcp__server__tool).

* feat: pretty-print JSON tool output, player error state, broader key redaction

- JSON tool results are detected and pretty-printed with 2-space indent
  instead of rendering as a wall of text
- API key redaction extended to cover api_key, apiKey, api-key, and
  token query params across all tool output (not just media embeds)
- Video/audio player shows styled error message when stream fails to
  load instead of leaving a broken player element
- Both appendToolOutput and replayHistory use shared renderToolOutput()

* fix: designer review — player error retry, contrast, tool-cmd cap

- Player error: role="alert" for screen readers, retry button that
  reuses existing play handler, includes media title in error message
- Light theme: darken --red from #dc2626 to #b91c1c (5.7:1 contrast
  on --code-bg, was 4.3:1 failing WCAG AA at 12px)
- Pretty-print collapsed raw JSON in media embeds (was missed earlier)
- Cap .tool-cmd at 120px to prevent tools with many args from making
  approval blocks disproportionately tall in history replay
- Dedicated .media-player-error class instead of reusing .tool-output

* fix: Discord tool info name matching regression, suppress deprecation warning

The escape_markdown call on tool names was stored for matching against
ToolResultEvent.name, but event.name is raw/unescaped. The escaped name
never matched, so the "Running → Done" transition silently failed and
previews disappeared from the status embed.

Fix: store raw name for matching, use escaped name only for display.

Also suppress discord.py's re.sub count deprecation warning (Python
3.13+ issue, fixed upstream).

* fix: update MCP tool description tests to match prefix removal

* fix: address PR #292 review round 2

- Retry button: handle missing span children in click handler so retry
  buttons from player error state don't throw
- Footer count: use len(lines) instead of min(len(results), 10) to
  reflect actual rendered count after char budget truncation
- Null display: use "null" instead of "None" in JS tool arg preview
- Broader redaction: also redact JSON "api_key": "..." patterns
- SSRF hardening: block loopback and link-local IPs plus cloud metadata
  hostnames in thumbnail fetch (private LAN IPs still allowed)
2026-04-04 14:47:25 -07:00
2026-04-03 15:41:15 -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 console — multi-workstream AI orchestration with mermaid diagrams

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) and Anthropic Messages API
  • 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

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.md for MCP configuration.

Architecture

Single-node: Client → Server (direct HTTP + SSE). No external dependencies beyond the database.

Multi-node: Client → Console (hash ring routing proxy) → Server nodes. The console maintains a 65536-entry bucket cache for O(1) workstream routing. A rebalancer daemon redistributes buckets when nodes join or leave.

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, with adapters for Slack/Teams planned)
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 adapter + 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.md

Requirements

  • Python 3.11+
  • An OpenAI-compatible API endpoint or Anthropic 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.

S
Description
No description provided
Readme Apache-2.0 114 MiB
Languages
Python 87.6%
JavaScript 8.7%
CSS 1.8%
HTML 1%
TypeScript 0.5%
Other 0.3%