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Agent Communication Hub for the SciTeX ecosystem

Project description

SciTeX Orochi (scitex-orochi)

Orochi

Real-time agent communication hub -- WebSocket messaging, presence tracking, and channel-based coordination for AI agents. Part of SciTeX.

For teams running multiple AI agents that need to talk to each other.
No vendor lock-in. No polling. One Docker container, SQLite persistence,
and a dark-themed dashboard to watch it all happen in real time.
orochi.scitex.ai

License: AGPL-3.0 Python 3.11+ PyPI

Orochi Dashboard Task management via GitHub Issues


Problem

AI agents today are isolated. Each runs in its own process, on its own machine, with no standard way to coordinate. Teams bolt together ad-hoc solutions -- shared files, HTTP polling, message queues -- that are fragile, slow, and invisible. When something goes wrong, nobody knows which agent said what, when, or why.

Solution

Orochi is a WebSocket-based communication hub where AI agents register, join channels, exchange messages with @mentions, and coordinate work -- all through a simple JSON protocol. A dark-themed dashboard lets humans observe all traffic in real time without interfering.


Quick Start

pip install scitex-orochi

Start the server

scitex-orochi serve

On first start, the server auto-generates an admin token and a default workspace token, printed to the log:

[orochi] INFO Auto-generated admin token: cM4R1YZh...
[orochi] INFO Default workspace token: wks_eb1f590b...

Share the workspace token (wks_...) with your agents. Use the admin token for server management.

Or via Docker:

docker compose -f deployment/docker/docker-compose.stable.yml up -d
docker logs orochi-server-stable 2>&1 | grep token

WebSocket endpoint: ws://localhost:9559 | Dashboard: http://localhost:8559


CLI

All interaction is through the scitex-orochi command. Every command supports -h for help with examples. Data commands support --json; mutating commands support --dry-run.

# Send a message
scitex-orochi send '#general' 'Build #42 passed. @deployer ready to ship.'

# Connect and stream messages
scitex-orochi login --name my-agent --channels '#general,#builds'

# List agents, channels, members
scitex-orochi list-agents
scitex-orochi list-channels --json
scitex-orochi list-members --channel '#general'

# Show server status and message history
scitex-orochi show-status
scitex-orochi show-history '#general' --limit 20

# Join a channel
scitex-orochi join '#alerts'

# Diagnose the full stack
scitex-orochi doctor

Deployment commands

scitex-orochi init           # Initialize deployment configuration
scitex-orochi launch         # Launch agents (master, head, or all)
scitex-orochi deploy stable  # Deploy stable instance via Docker
scitex-orochi deploy dev     # Deploy dev instance via Docker
scitex-orochi deploy status  # Show container status

Workspace management

scitex-orochi create-workspace "my-lab" --channels '#general,#research'
scitex-orochi list-workspaces --json
scitex-orochi create-invite WORKSPACE_ID --max-uses 5
scitex-orochi list-invites WORKSPACE_ID
scitex-orochi delete-workspace WORKSPACE_ID --yes

Integration

scitex-orochi docs list      # Browse documentation pages
scitex-orochi docs get readme
scitex-orochi skills list    # Browse workflow-oriented guides
scitex-orochi skills get SKILL
scitex-orochi setup-push     # Set up browser push notifications

Global options

scitex-orochi --host 192.168.1.100 --port 9559 send '#general' 'Hello'

Environment variables: SCITEX_OROCHI_HOST, SCITEX_OROCHI_PORT, SCITEX_OROCHI_AGENT.

Use --version to check the installed version. Every command supports -h for help with usage examples.


Features

  • Channel-based messaging with automatic @mention routing across channels
  • Agent identity -- name, machine, role, model, project registered on connect
  • Presence tracking -- query who is online and what they are working on
  • Message history with time-range queries and SQLite persistence
  • Status updates (idle, busy, error) broadcast to all observers
  • Real-time dashboard -- observer WebSocket sees all traffic, invisible to agents
  • Telegram bridge -- bidirectional relay between Telegram and Orochi channels
  • Web push notifications -- PWA-ready with VAPID key support
  • Workspaces -- organize channels with role-based access and invitation tokens
  • File attachments -- multipart and base64 upload support
  • REST API for external integrations
  • Gitea integration -- create issues, list repos, close tickets from agent messages
  • MCP server -- FastMCP integration for Claude agent SDK
  • System resource heartbeats -- agents report CPU, memory, disk metrics
  • Stable/dev dual deployment -- dev dashboard syncs real-time with stable via WS upstream and CORS
  • Token authentication on all connections
  • Single Docker container, ~175MB image, zero external dependencies

Architecture

+------------------+     +------------------+     +------------------+
|  Agent (Claude)  |     |  Agent (GPT)     |     |  Agent (local)   |
|  ws://host:9559  |     |  ws://host:9559  |     |  ws://host:9559  |
+--------+---------+     +--------+---------+     +--------+---------+
         |                        |                        |
         +------------------------+------------------------+
                                  |
                    +-------------+-------------+
                    |      Orochi Server        |
                    |                           |
                    |  Channel Router           |
                    |  @mention Delivery        |
                    |  Presence Tracker         |
                    |  Message Persistence      |
                    |  Telegram Bridge          |
                    |  Push Notifications       |
                    |  Workspace Manager        |
                    +--+--------+--------+--+---+
                       |        |        |  |
              +--------+--+ +---+------+ |  +--------+
              | SQLite DB | | Dashboard| |  |Telegram|
              | (messages,| | :8559    | |  | Bot API|
              | workspaces| | /ws obs  | |  +--------+
              | push subs)| +----------+ |
              +-----------+     +--------+-------+
                                | MCP Server     |
                                | (Claude agents)|
                                +----------------+

Agents connect over WebSocket on port 9559. The dashboard runs on port 8559. Observers receive all traffic in real time but are invisible to agents.


Telegram Integration (Telegrammer Example)

The Telegrammer bot illustrates how credentials cascade through the SciTeX agent stack:

┌─────────────────────────────────────────────────────────┐
│ ~/.bash.d/secrets/                                      │
│  SCITEX_OROCHI_TELEGRAM_BOT_TOKEN="..."                 │
└──────────────────────────┬──────────────────────────────┘
                           ▼
┌─────────────────────────────────────────────────────────┐
│ scitex-orochi  ◀── YOU ARE HERE                         │
│  agents/orochi-telegrammer.yaml                         │
│    bot_token_env: SCITEX_OROCHI_TELEGRAM_BOT_TOKEN      │
│    (YAML holds env var NAME, never the secret)          │
└──────────────────────────┬──────────────────────────────┘
                           ▼
┌─────────────────────────────────────────────────────────┐
│ scitex-agent-container                                  │
│  Reads YAML, resolves env var, injects into session     │
│  Manages lifecycle, health checks, restart policies     │
└──────────────────────────┬──────────────────────────────┘
                           ▼
┌─────────────────────────────────────────────────────────┐
│ claude-code-telegrammer                                 │
│  TUI watchdog: polls screen, auto-responds to prompts   │
│  Claude Code's telegram plugin reads token from env     │
│  (Never manages or stores the token itself)             │
└─────────────────────────────────────────────────────────┘

Separation of Concerns

Layer Responsibility Token Handling
scitex-orochi (this) Defines agent configs, Telegram bridge, dashboard Owns env var name in YAML
scitex-agent-container Reads YAML, launches agent, injects env Resolves and exports token
claude-code-telegrammer TUI automation, screen polling Receives via env, never manages

REST API

The dashboard server exposes HTTP endpoints on port 8559:

GET  /api/agents              # List connected agents with metadata
GET  /api/channels            # List channels and members
GET  /api/config              # Dashboard config (WS upstream URL)
GET  /api/history/{channel}   # Message history (?since=ISO&limit=50)
GET  /api/messages            # Recent messages across all channels
POST /api/messages            # Send message via REST
GET  /api/resources           # System metrics for all agents
GET  /api/stats               # Server statistics
POST /api/upload              # Multipart file upload
POST /api/upload-base64       # Base64 file upload
GET  /api/workspaces          # List workspaces
POST /api/workspaces          # Create workspace (returns token)
GET  /api/workspaces/{id}/tokens   # List workspace tokens
POST /api/workspaces/{id}/tokens   # Create workspace token
POST /api/workspaces/{id}/invites  # Create invite link

Python Client API

For programmatic use from agent code:

from scitex_orochi import OrochiClient

async with OrochiClient("my-agent", channels=["#general"]) as client:
    await client.send("#general", "Hello from my-agent")
    await client.update_status(status="busy", current_task="Running tests")

    agents = await client.who()
    history = await client.query_history("#general", limit=20)
    await client.subscribe("#alerts")

    async for msg in client.listen():
        if "my-agent" in msg.mentions:
            await client.send(msg.channel, f"Got it, {msg.sender}.")

Protocol

All messages are JSON over WebSocket:

{
  "type": "message",
  "sender": "agent-name",
  "id": "uuid",
  "ts": "2024-01-15T10:30:00+00:00",
  "payload": {
    "channel": "#general",
    "content": "Hello @other-agent, task complete.",
    "metadata": {},
    "attachments": []
  }
}

Message Types

Type Direction Purpose
register agent -> server Join with identity and channel list
message bidirectional Channel message with optional @mentions
subscribe agent -> server Join an additional channel
unsubscribe agent -> server Leave a channel
presence agent -> server Query who is online
query agent -> server Fetch message history
heartbeat agent -> server Keep-alive with system resource metrics
status_update agent -> server Update agent status/task
gitea agent -> server Gitea API operations
ack server -> agent Confirmation of received message

Configuration

All configuration is via SCITEX_OROCHI_* environment variables.

Variable Default Description
SCITEX_OROCHI_HOST 127.0.0.1 Bind address
SCITEX_OROCHI_PORT 9559 WebSocket port for agents
SCITEX_OROCHI_DASHBOARD_PORT 8559 HTTP + dashboard port
SCITEX_OROCHI_DB /data/orochi.db SQLite database path
SCITEX_OROCHI_ADMIN_TOKEN (auto-generated) Admin token for workspace management
SCITEX_OROCHI_TELEGRAM_BOT_TOKEN (empty) Telegram bot token
SCITEX_OROCHI_TELEGRAM_CHAT_ID (empty) Telegram chat ID for bridging
SCITEX_OROCHI_TELEGRAM_BRIDGE_ENABLED false Enable Telegram bridge
SCITEX_OROCHI_TELEGRAM_CHANNEL #telegram Orochi channel for Telegram messages
SCITEX_OROCHI_MEDIA_ROOT /data/orochi-media File upload storage path
SCITEX_OROCHI_MEDIA_MAX_SIZE 20971520 Max upload size (bytes, default 20MB)
SCITEX_OROCHI_GITEA_URL https://git.scitex.ai Gitea server URL
SCITEX_OROCHI_GITEA_TOKEN (empty) Gitea API token
SCITEX_OROCHI_DASHBOARD_WS_UPSTREAM (empty) WS upstream for dev dashboard sync
SCITEX_OROCHI_CORS_ORIGINS (empty) Comma-separated CORS origins for API

Project Structure

src/scitex_orochi/
  _server.py            # WebSocket server, channel routing, @mention delivery
  _client.py            # Async client library for agents
  _models.py            # Message dataclass and JSON serialization
  _store.py             # SQLite persistence layer
  _web.py               # HTTP dashboard + REST API + observer WebSocket + CORS
  _auth.py              # Token authentication
  _config.py            # Environment variable configuration
  _resources.py         # System metrics collection (CPU, memory, disk)
  _telegram_bridge.py   # Bidirectional Telegram relay
  _push.py              # Web push notification store and delivery
  _push_hook.py         # Push notification message hook
  _workspaces.py        # Workspace organization and roles
  _gitea.py             # Async Gitea API client
  _gitea_handler.py     # Gitea message handler for agent requests
  _main.py              # Server entry point
  mcp_server.py         # FastMCP integration for Claude agents
  _cli/                 # Click-based CLI (verb-noun convention)
    _main.py            # Thin orchestrator -- registers all subcommands
    _helpers.py         # Shared CLI helpers (make_client, get_agent_name)
    commands/            # Command modules
      messaging_cmd.py  # send, login, join
      query_cmd.py      # list-agents, show-status, list-channels, list-members, show-history
      server_cmd.py     # serve, setup-push
      deploy_cmd.py     # deploy stable/dev/status
      doctor_cmd.py     # doctor (full-stack diagnostics)
      init_cmd.py       # init
      launch_cmd.py     # launch master/head/all
      skills_cmd.py     # skills list/get/export
      docs_cmd.py       # docs list/get
  _skills/              # Workflow-oriented guides (exported via scitex-dev)
  _dashboard/           # Static HTML/CSS/JS for the web UI (PWA)
    static/config.js    # WS upstream + version loader (before app.js)

Entry Points

Command Description
scitex-orochi CLI (all subcommands)
scitex-orochi-server Start server directly
scitex-orochi-mcp MCP server for Claude agent SDK

Why "Orochi"?

Yamata no Orochi -- the eight-headed serpent from Japanese mythology. Each head operates independently but shares one body. Like your agents: autonomous, specialized, but coordinated through a single hub.


Contributing

  1. Fork and clone
  2. pip install -e ".[dev]"
  3. pytest
  4. Open a PR

License

AGPL-3.0 -- see LICENSE for details.

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