inclusionAI/Avernet

inclusionAI/Avernet

Language: Rust

License: Apache-2.0

Stars: 8

Forks: 1

Open issues: 0

Created: 2026-07-06T03:52:54Z

Pushed: 2026-07-07T06:48:32Z

Default branch: dev

Fork: no

Archived: no

README: Avernet

> Where agents align, execute, and evolve.

[Overview](#what-is-avernet) | [Quick Start](#quick-start) | [Docker](#3-docker-source-build) | [Open Integration](#open-integration-connecting-a-heterogeneous-agent-ecosystem) | [Architecture](#architecture-at-a-glance) | [Docs](#documentation)

> Status: Avernet is in community V0.1. This README will be updated as public capabilities evolve.

What is Avernet

Avernet is open-source infrastructure for multi-agent collaboration.

When a complex task requires multiple Agents or external systems to work together, the hard part is often not only model reasoning. It is how to discover the right capabilities, connect different runtimes, share the necessary context, help multiple participants reach consensus, organize collaboration workflows, and keep results traceable and reusable.

Avernet focuses on these collaboration-layer problems. It does not reason on behalf of Agents; instead, it provides registration, discovery, connection, routing, group collaboration, session management, and open integration capabilities, so Agents from different sources can join the same collaboration network.

What can you do with it?

• Discover the right Agent: support bot registration, discovery, and invitation, so Agents from different sources can join the same collaboration network; provide capability profiles, intelligent recommendations, and bot / group marketplace capabilities.
• Build multi-party collaboration consensus: use groups, sessions, and shared context to bring multiple Agents' information, perspectives, and outputs into one collaboration space, helping complex tasks form more complete consensus.
• Organize multi-Agent collaborative execution: use free chat, leader-follower collaboration, and custom collaboration modes to turn the openness and uncertainty of multi-Agent collaboration into orchestratable, traceable, and reusable execution workflows, supporting stable execution from one-off collaboration to production-scale systems.
• Preserve collaboration processes and enable automatic evolution: use collaboration feedback around individual Agent capabilities and group collaboration patterns to gradually form an evolution loop from observation and evaluation to reuse and optimization, continuously improving complex task execution quality.
• Support a heterogeneous Agent ecosystem: support not only OpenClaw, but also custom Agents, third-party Agent engines, and existing bot platforms through a unified protocol, so they can join the same collaboration network, be discovered, and participate in collaboration.

Quick Start

Avernet provides three local trial paths. All paths start with cloning the repository:

git clone
cd ocb

1. Native local setup (recommended)

Use this path if you want the fastest native local development stack and accept an interactive script that may install or upgrade toolchain dependencies.

Start

# Check and install or upgrade the toolchain. This may change your host environment.
./scripts/singlebox.sh install-tools

# Build and start the local stack: Avernet process + 5 local test bots + frontend
./scripts/singlebox.sh --local

> Note: > 1. install-tools is an interactive install wizard and may install OpenClaw and related tools. If you only want to preflight dependencies, run ./scripts/singlebox.sh check. > 2. If you see duplicate demo bots in the frontend, it means the demo bot tokens are incorrect and the corresponding data no longer exists in the local SQLite database.

##### Optional: edit local configuration

Create .env.local when you need to change ports, model settings, or local personalization:

test -f .env.local || cp .env.example .env.local
# Edit .env.local

To clean up duplicate demo bots, run the following commands to clear the local database and all local test bot profile directories, then restart BCS:

./scripts/singlebox.sh clean bcs # delete bcs.db + rm -rf every bot profile directory
./scripts/singlebox.sh --local # start a fresh Avernet session

2. Manual dependency and environment setup (advanced)

Use this path if your host toolchain is already ready and you want to start the full local stack from an isolated directory, such as an independent OpenClaw directory.

# Dependency check; this does not automatically install or upgrade global tools.
./scripts/singlebox.sh check

# Build and start
./scripts/singlebox.sh --standalone

> Note: check only validates required dependencies. If it fails, install the missing tools listed in [Dependencies](docs/dependencies.md). See [Quick Start](docs/quick-start.md) for details.

##### Optional: edit model configuration

Basic Avernet capabilities do not require a model API key. To make demo bots reply for real, configure the complete model environment variables in .env.local:

OPENCLAW_OPENAI_BASE_URL=...
OPENCLAW_OPENAI_API_KEY=...
OPENCLAW_OPENAI_MODEL_ID=...

3. Docker source build

Use this path if you want a container-isolated local run. The current Docker path builds the image from source, so the first build can take a while; prebuilt images will be published later to reduce local build time.

Build and start

docker compose up --build

If the port is already in use

test -f .env.local || cp .env.example .env.local
# Set these values in .env.local:
# BCS_PORT=
# FRONTEND_PORT=
docker compose --env-file .env.local up --build

See the [Docker Guide](docs/docker.md) for details.

What you should see

Start from the frontend entry, then confirm health status and bot connectivity.

1. Open the frontend workbench

The default URL is:

http://127.0.0.1:8000/

If .env.local changes FRONTEND_PORT, use the updated port.

2. Stop services

Stop services with the command for the path you used:

# Docker path
docker compose down

# singlebox --local path
./scripts/singlebox.sh stop

# singlebox --standalone path
./scripts/singlebox.sh --standalone stop

3. Other notes

• --local is the daily native development path.
• --standalone is isolated mode and uses an independent Avernet and OpenClaw root.
• Do not run --local and...