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Evonic

Design. Deploy. Orchestrate.
Your Models. Your Rules. Your Swarm.

Evonic is an agentic AI framework for designing, building, and orchestrating intelligent agents from concept to production. It empowers you to define every aspect of an agent — its model, tools, knowledge base, channels, and skills — and compose them into multi-agent systems that operate autonomously across distributed environments.

Full documentation: evonic.dev

Evonic Logo

Evonic Web UI Screenshot


Three Core Differentiators

Evonic is not just another agent framework. Three architectural decisions set it apart:

1. Workplace — Anywhere Execution

Agents are not tied to a single machine. A Workplace is a first-class execution environment that can be:

  • Local — sandboxed workspace on the host machine
  • Remote — SSH servers, edge devices, or any machine with network access
  • Tunnel — lightweight Evonet connector that requires no public IP, no SSH, and no firewall rules

This means your agents can operate across your entire infrastructure — development laptops, production servers, and cloud instances — with a single abstraction layer.

2. Agent-to-Agent Communication

Communication between agents is a first-class protocol, not an afterthought. Agents can message, delegate, and coordinate with each other natively. This enables:

  • Multi-agent swarms where each agent has a distinct role and toolset
  • Hierarchical orchestration with supervisor agents managing worker agents
  • Peer-to-peer collaboration for complex multi-step workflows

Each agent maintains its own identity, state, and capabilities, making swarm intelligence a natural pattern rather than a bolt-on feature.

3. Heuristic Mal-activity Detection System

Safety is not optional. Every action an agent takes is inspected through a real-time, multi-layer heuristic detection system that identifies and blocks dangerous patterns before execution. The system monitors for:

  • Mass file deletion and privilege escalation attempts
  • Unauthorized remote code execution
  • Behavioral drift beyond expected action boundaries

When suspicious activity is detected, the system escalates to a human operator rather than blindly executing — giving you a safety net that enables genuine agent autonomy without compromising security.


Key Features

Feature Description
Agents Independent, LLM-powered assistants with custom tools, knowledge bases, and isolated workspaces
Models Pluggable LLM backends — any OpenAI-compatible API, local or cloud
Skills Installable packages that bundle tool definitions with Python backends
Plugins Event-driven extensions for custom integrations and background workers
Workplaces Execution environments: local directories, SSH servers, or tunnel devices via Evonet
Evonet Lightweight Go connector for remote execution without SSH or firewall rules
Scheduler Cron-based triggers, recurring tasks, and reminders for agents
Channels Connect agents to Telegram, WhatsApp, Discord, Slack, and custom interfaces
Evaluation Engine Automated LLM evaluation with customizable regex and heuristic evaluators
Token Compressor RTK-based token compression that cuts LLM costs by reducing context without losing meaning
Agent Artifacts Persistent files and outputs agents produce, stored and retrievable across sessions
Injection Guard Multi-layer prompt injection detection that blocks manipulation and unauthorized override attempts
Supervisor Daemon Background supervisor that monitors agent health, restarts on failure, and tracks uptime
Backup & Restore Full backup and restore of all agent configurations, knowledge bases, and data

Getting Started

Prerequisites

  • Python 3.10+
  • LLM endpoint — any OpenAI-compatible API (local or cloud)

Installation

One-liner install:

curl -fsSL https://evonic.dev/install.sh | bash

This clones the repository, sets up a virtual environment, installs dependencies, generates configuration, and guides you through adding evonic to your PATH.

Manual installation:

git clone https://github.com/anvie/evonic
cd evonic
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
chmod +x ./evonic

Start

./evonic start

Open http://localhost:8080 in your browser.

Docker Sandbox (optional)

Agent tools like bash and runpy execute inside an isolated Docker container by default:

docker build -t evonic-sandbox:latest docker/tools/

Configure resource limits in .env (memory, CPU, network). If Docker is unavailable, set sandbox_enabled=0 to fall back to local execution.


Agents

Each agent is designed from the ground up with six configurable dimensions:

Dimension Description
Concept System prompt and identity — who the agent is and how it behaves
Model LLM backend — which model powers the agent's reasoning
Tools Capabilities — what actions the agent can take
Knowledge Base Reference documents — what information the agent can access
Channels Interfaces — where users interact with the agent
Skills Modular extensions — additional capabilities installed on demand

Create and manage agents via the web UI (/agents) or CLI:

./evonic agent list
./evonic agent get my_bot
./evonic agent add my_bot --name "My Bot"
./evonic agent add dev_bot --name "Dev Bot" --skillset coder
./evonic agent enable my_bot
./evonic agent disable my_bot
./evonic agent remove my_bot

Channels

Connect your agents to the platforms your users already use:

Channel Status Library
Telegram ✅ Implemented python-telegram-bot
WhatsApp ✅ Implemented @whiskeysockets/baileys (Node.js sidecar)
Discord 🔄 Planned discord.py
Slack 🔄 Planned slack-sdk

Skills

Skills extend agents with new capabilities. Install via CLI:

./evonic skill add path/to/skill.zip
./evonic skill list
./evonic skill get math
./evonic skill rm math

Skills follow a load → context → execute lifecycle, keeping the agent's system prompt lean and modular.


Plugins

Plugins are event-driven extensions that hook into Evonic's event stream. Manage them via CLI:

./evonic plugin install path/to/plugin.zip
./evonic plugin list
./evonic plugin uninstall my_plugin

Models

Manage LLM configurations:

./evonic model add gpt4o --name "GPT-4o" --provider openai --api-key "sk-..." --base-url "https://api.openai.com/v1"
./evonic model list
./evonic model rm gpt4o

CLI Quick Reference

Command Description
start Start the Flask server
stop Stop the running server
restart Restart the server in daemon mode
status Check if the server is running
setup Interactive first-time setup wizard
reconfigure Reconfigure an existing Evonic setup
pass Set or change the admin dashboard password
doctor Run system diagnostics and health checks
update Check for and apply self-updates
backup Create a full Evonic backup archive
restore Restore Evonic from a backup archive
clear-sandbox Destroy all running sandbox containers
agent list/get/add/enable/disable/remove Manage agents
model list/get/add/rm Manage LLM models
skill list/add/get/rm Manage skills
skillset list/get/apply Manage skillset templates
plugin install/uninstall/list/enable/disable Manage plugins
channel approve Approve pending channel pairings
kanban add/rm/update Manage kanban tasks

Use Cases

Evonic's architecture unlocks a broad spectrum of real-world applications. Here are fifteen concrete scenarios:

Customer Service

Deploy agents that handle support tickets, answer FAQs, process refunds, and escalate complex issues — all within your existing Telegram or WhatsApp channels.

Personal Companion

Build personal assistants that manage daily tasks, set reminders, conduct research, and maintain long-term context across conversations.

Agentic Swarm / Multi-Agent Orchestration

Orchestrate multiple agents with distinct roles — a researcher, a writer, a reviewer, and a publisher — collaborating autonomously on complex deliverables.

Automation & DevOps

Deploy agents that monitor server health, trigger deployments, roll back faulty releases, and respond to incidents with automated runbooks.

Research Assistant

Create agents that perform literature reviews, extract structured data from documents, summarize findings, and generate citations.

Customer Onboarding

Guide new users through product setup with interactive agents that adapt to each user's pace and knowledge level.

Quality Assurance & Evaluation

Automate LLM evaluation pipelines — define test cases, run evaluations across models, and generate benchmark reports automatically.

Internal Helpdesk

Provide IT support, HR policy lookups, and facility requests through a single agent interface connected to your internal knowledge base.

E-commerce Assistant

Power product recommendations, order tracking, cancellation requests, and inventory inquiries — connected to your commerce backend.

Healthcare Triage

Deploy agents that conduct initial symptom assessment, schedule appointments, and route critical cases to the appropriate specialist.

Education Tutor

Build adaptive tutoring agents that personalize learning paths, grade assignments, and provide real-time feedback to students.

Content Moderation

Scan user-generated content for harmful patterns, flag violations, and take appropriate action — all within configurable safety boundaries.

Financial Advisory

Create agents that analyze portfolios, generate market summaries, assess risk profiles, and provide data-driven financial insights.

Agentic ERP

Orchestrate enterprise resource planning workflows — supply chain monitoring, inventory optimization, procurement automation, and financial reconciliation — through specialized agents that coordinate across departments.

AI Workflow Orchestration

Design end-to-end AI pipelines where agents manage the entire lifecycle: data ingestion, preprocessing, model training, evaluation, and deployment — with each stage handled by a specialized agent.


Architecture Overview

User Message
    ↓
Channel (Telegram, Web, WhatsApp, etc.)
    ↓
┌──────────────────────────────────────────┐
│           Injection Guard                │
│  (prompt injection & manipulation check) │
└──────────────────────────────────────────┘
    ↓
┌──────────────────────────────────────────┐
│           Agent Runtime                  │
│  ├─ Load agent config (system prompt,    │
│  │   model, tools, knowledge base)       │
│  ├─ Load/create session (per-user)       │
│  ├─ Build messages + apply token         │
│  │   compression (RTK)                   │
│  ├─ Call LLM                             │
│  ├─ Execute tool calls (sandboxed)       │
│  ├─ Heuristic safety check on actions    │
│  ├─ Store artifacts from tool output     │
│  └─ Loop until final response            │
└──────────────────────────────────────────┘
    ↓
┌──────────────────────────────────────────┐
│         Evaluation Engine                │
│  (optional: regex / heuristic / LLM eval)│
└──────────────────────────────────────────┘
    ↓
┌──────────────────────────────────────────┐
│         Supervisor Daemon                │
│  (health checks, auto-restart, uptime)   │
└──────────────────────────────────────────┘
    ↓
Response → Channel → User

License

Evonic is open source. See the LICENSE file for details.


Built with ❤️ by Robin Syihab

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