Verlihub Python API

A FastAPI-based REST API and web dashboard for managing Verlihub DC hubs.

Fork notice: verlihub-py is a modified fork of Verlihub, maintained at github.com/transfix/verlihub. It is not the original project. Licensed GPL-3.0-or-later; all upstream copyrights are preserved.

Features

• REST API - Full hub management via HTTP endpoints
• Web Dashboard - Browser-based administration UI
• WebSocket - Real-time hub events and log streaming
• CLI Tools - Command-line management utilities
• Performance Benchmarks - Load testing and performance analysis
• Remote Client - Python client library for hub administration
• NMDCpb Protocol Extension - Protobuf structured messaging with hub-relayed transfers, E2E encrypted PM, media sharing, channels, and voice/video signaling
• LLM & MCP Integration - AI chat assistant with hub tool-calling, an NMDC Hub-Security bot, and a Model Context Protocol server for AI editors

Quick Start

Installation

# From PyPI (recommended)
pip install verlihub-py

# With LLM / MCP integration extras (OpenAI-compatible client + MCP server)
pip install "verlihub-py[ai]"

# From source (development)
git clone https://github.com/transfix/verlihub
cd verlihub/python
pip install -e ".[dev]"

Note: the published wheels bundle the native Verlihub C++ core (built via scikit-build-core + SWIG). A source build additionally needs CMake, SWIG, a C++17 compiler, and the hub's build dependencies.

Running the API Server

# Start the API server
verlihub-api

# Or with custom settings
verlihub-api --host 0.0.0.0 --port 8000

Using the CLI

# Check hub status
verlihub-cli status

# List online users
verlihub-cli users

# Execute a hub command
verlihub-cli command "!help"

# Login and save token
verlihub-cli login admin password123

API Endpoints

Public Endpoints

Authenticated Endpoints

WebSocket Endpoints

Web Dashboard

Access the dashboard at http://localhost:8000/dashboard/

Pages

• Dashboard - Hub overview with stats and quick actions
• Users - Online and registered user management
• Bans - Ban list and management
• Logs - Real-time log viewer
• Console - Command execution interface
• Config - Hub configuration (Master only)
• Plugins - Plugin management (Admin only)

NMDCpb Protocol Extension

verlihub-py ships the server side of NMDCpb — a protobuf-based structured messaging layer that extends classic NMDC with six integrated features. The hub negotiates NMDCpb in $Supports, dispatches $PB/$PBR envelopes to a Python plugin, and transparently translates to legacy NMDC ($<nick>, $To:, $Search) for non-NMDCpb clients.

Admin surface

• Chat commands (operator, class ≥ 5): +nmdcpb stats, +nmdcpb users, +nmdcpb relay, +nmdcpb channel list|create|delete|info
• REST API under /dashboard/nmdcpb/api (admin JWT, user_class ≥ 5): GET /api/stats, GET /api/users, GET /api/relays, GET /api/relay/{id}, POST /api/relay/{id}/close, POST /api/relay/close-all, POST /api/relay/close-user/{nick}
• Media API mounted at /api/media/ (per-user HMAC bearer tokens): POST /upload, GET /quota, GET /{id}, GET /{id}/thumb, GET /{id}/meta, DELETE /{id}
• WebSocket /ws/relay streams relay_created / relay_closed events
• Dashboard at /dashboard/nmdcpb/ with live stats, relay/user tables, and admin actions

Client library

A high-level Python client for these extensions (E2E-encrypted PM, hub-relayed transfers, media sharing, channels) ships in verlihub.client.nmdcpb — see NMDCpb Client Library below.

Detailed documentation

LLM & MCP Integration

verlihub-py includes optional LLM integration that connects to any OpenAI-compatible backend (Ollama, vLLM, llama.cpp, LiteLLM, OpenRouter, or a hosted API):

• AI Chat Assistant — a dashboard chat tab (POST /api/v1/llm/chat, streaming over /ws/llm-chat) where admins ask natural-language questions and the LLM executes hub tool-calls (list users, kick, ban, read stats) and feeds results back for a final answer.
• NMDC Hub-Security Bot — hub users chat with an LLM-backed bot via PM or main chat, with session memory, a mood engine, web access (search/fetch/RSS), and persistent notes.
• MCP Server — a Model Context Protocol server exposing the hub as tools/resources/prompts to AI editors (VS Code, Claude Desktop) over stdio or HTTP; ships the verlihub-mcp CLI.

Enable it in config and point base_url at your backend. See LLM_INTEGRATION.md for the full architecture, configuration reference, setup guides (Ollama/vLLM/llama.cpp), the tool-calling flow, bot features, and MCP server/client usage.

Performance Benchmarks

The benchmark suite measures API performance including latency percentiles and throughput.

Running Benchmarks

# Quick health check
verlihub-bench quick

# Full API benchmark suite
verlihub-bench api --requests 1000 --concurrency 20

# Stress test
verlihub-bench stress --requests 5000 --concurrency 50

# Detailed latency profile
verlihub-bench latency --endpoint /api/v1/hub/stats --samples 1000

# Full benchmark with all tests
verlihub-bench full --stress --websocket --output results.json

Benchmark Options

--url, -u           API base URL (default: http://localhost:8000)
--requests, -n      Requests per benchmark (default: 100)
--concurrency, -c   Concurrent connections (default: 10)
--output, -o        Output file for results (JSON)
--token, -t         Authentication token
--username          Username for auth
--password          Password for auth

Sample Output

======================================================================
Benchmark: GET /api/v1/hub/stats
======================================================================

Summary:
  Total Requests:    1,000
  Successful:        1,000 (100.0%)
  Failed:            0
  Total Time:        2.34s
  Throughput:        427.35 req/s

Latency (ms):
  Min:               1.234
  Max:               45.678
  Avg:               2.341
  Std Dev:           1.567
  p50 (median):      2.123
  p95:               4.567
  p99:               8.901
======================================================================

Programmatic Usage

import asyncio
from verlihub.benchmarks import BenchmarkRunner, BenchmarkSuite

async def run_benchmarks():
    # Create a custom benchmark suite
    suite = BenchmarkSuite("My Benchmarks")
    suite.add_endpoint("Health", "GET", "/health", num_requests=500)
    suite.add_endpoint("Stats", "GET", "/api/v1/hub/stats", num_requests=500)
    
    # Run benchmarks
    results = await suite.run(base_url="http://localhost:8000")
    
    # Print summary
    print(suite.summary())
    
    # Export to JSON
    with open("results.json", "w") as f:
        f.write(suite.to_json())

asyncio.run(run_benchmarks())

Client Library

Synchronous Client

from verlihub.client import HubClient

client = HubClient("http://localhost:8000")
client.login("admin", "password")

# Get hub stats
stats = client.get_stats()
print(f"Users online: {stats['user_count']}")

# List online users
users = client.get_online_users()
for user in users:
    print(f"  {user['nick']} - {user['share']}")

# Kick a user
client.kick_user("baduser", reason="Spamming")

Asynchronous Client

import asyncio
from verlihub.client import AsyncHubClient

async def main():
    async with AsyncHubClient("http://localhost:8000") as client:
        await client.login("admin", "password")
        stats = await client.get_stats()
        print(stats)

asyncio.run(main())

NMDC Protocol Client

from verlihub.client import NMDCClient

# Connect directly to hub via NMDC protocol
client = NMDCClient("192.168.1.100", 4111)
client.connect("BotNick", "password")

# Send a message
client.send_chat("Hello from Python!")

# Get user list
users = client.get_users()

client.disconnect()

NMDCpb Client Library (E2EPM · HubRelay · MediaShare · Channels)

Beyond the raw protocol, verlihub-py ships a high-level NMDCpb client (verlihub.client.nmdcpb) that speaks the protobuf overlay and exposes ergonomic, strongly-typed APIs for the extension features. It doubles as the reference client that validates the hub-side implementation. Requires the protobuf + cryptography extras.

from verlihub.client import NMDCpbClient  # also: WireCodec, E2EPMSession, E2EPMManager

client = NMDCpbClient("mybot", "password")
await client.connect("nmdc://hub.example.com:411")

# Structured chat / PM (protobuf)
await client.send_pb_chat("Hello from protobuf!")
await client.send_pb_pm("Alice", "Hi Alice")

End-to-end encrypted PM (E2EPM)

X25519 key exchange + ChaCha20-Poly1305, with 4-emoji verification fingerprints and Trust-On-First-Use key continuity — negotiated automatically on first use:

client.on_e2epm_established = lambda peer, fp: print(f"Secure with {peer}: {fp}")
client.on_encrypted_pm      = lambda frm, text, enc: print(f"[E2E] {frm}: {text}")

await client.send_encrypted_pm("Alice", "Secret message")

Lower-level session control is available via E2EPMManager / E2EPMSession (initiate_session, handle_key_exchange, encrypt_message, decrypt_message).

Hub-relayed transfers (HubRelay)

Hub-brokered, NAT-friendly, resumable file relay with SHA-256 verification:

from verlihub.client.nmdcpb.relay import RelayFileTransfer

relay = RelayFileTransfer(client, download_dir="/downloads")
info  = await relay.send_file("Alice", "/path/to/file.bin")   # -> TransferInfo (progress, speed, state)

# …or drive the protocol directly:
client.on_relay_request = lambda frm, token, purpose, size: None
await client.accept_relay(token)
await client.send_relay_data(relay_id, chunk, offset)
await client.close_relay(relay_id)

client.relay_only_mode = True    # privacy: force all transfers through the hub relay

Admin REST surface (dashboard, user_class ≥ 5) at /dashboard/nmdcpb/api: GET /relays, GET /relay/{id}, POST /relay/{id}/close, POST /relay/close-all, POST /relay/close-user/{nick}; live events over the /ws/relay WebSocket (relay_created / relay_closed).

Media sharing (MediaShare)

Server-side storage with per-user quota, TTL, thumbnails, and a REST surface:

from verlihub.client.nmdcpb.media_storage import MediaStorage, MediaConfig

store = MediaStorage(MediaConfig())
meta  = store.store(data, "clip.mp4", "video/mp4", uploader="mybot")   # -> MediaMeta
quota = store.get_quota("mybot")

REST API (per-user HMAC bearer tokens), mounted at /api/media:

Channels

Server-managed public/private channels with member roles (MEMBER/ADMIN/OWNER/READONLY), message history, and group sender-key encryption. Managed by verlihub.client.nmdcpb.channel_manager.ChannelManager (auto-creates and auto-joins #general); driven over the protobuf protocol with actions: list / create / delete / join / leave / set-topic / kick / set-role.

Protobuf message types

All wire types are importable for advanced/manual use:

from verlihub.client.nmdcpb.nmdcpb_pb2 import (
    PbEnvelope,
    PbPMKeyExchange, PbEncryptedPM, PbPMPlaintext,        # E2EPM
    PbMediaUpload, PbMediaMeta, PbMediaRef,               # MediaShare
    PbRelayRequest, PbRelayAck, PbRelayData, PbRelayClosed,  # HubRelay
    PbChannel, PbChannelList, PbChannelMemberUpdate,      # Channels
)

Configuration

Environment Variables

Database

The API supports both MySQL and SQLite:

# MySQL (production)
from verlihub.models.database import DatabaseConfig

config = DatabaseConfig(
    driver="mysql",
    host="localhost",
    port=3306,
    database="verlihub",
    username="verlihub",
    password="secret",
)

# SQLite (testing)
config = DatabaseConfig(
    driver="sqlite",
    database=":memory:",  # or path to file
)

Testing

# Run all tests
pytest

# Run with coverage
pytest --cov=verlihub --cov-report=html

# Run specific test file
pytest tests/test_api_endpoints.py -v

# Run benchmark tests
pytest tests/test_benchmarks.py -v

Test Results

Current test status: 188 passed, 21 skipped

Skipped tests require C++ SWIG bindings to be built.

Development

Project Structure

python/
├── verlihub/
│   ├── api/           # FastAPI routes and app
│   ├── dashboard/     # Web dashboard templates
│   ├── client/        # Remote client library
│   ├── models/        # SQLModel database models
│   ├── benchmarks/    # Performance testing
│   └── cli.py         # Command-line interface
├── tests/             # Test suite
└── pyproject.toml     # Project configuration

Adding New Endpoints

1. Create route in verlihub/api/routes/
2. Add to router in verlihub/api/__init__.py
3. Add tests in tests/test_api_endpoints.py
4. Update API documentation

Adding Dashboard Pages

1. Create template in verlihub/dashboard/templates/
2. Add route in verlihub/dashboard/routes.py
3. Add navigation link in base.html
4. Add tests in tests/test_dashboard.py

License

GPL-3.0-or-later - See LICENSE for details.