Protea Self Evolving Life Agent

Self-evolving artificial life agent. Three-ring architecture: Ring 0 (Sentinel) supervises, Ring 1 (Intelligence) drives LLM-powered evolution, Ring 2 (Evolvable Code) is the living program that self-restructures, self-reproduces, and self-evolves. Supports Anthropic, OpenAI, DeepSeek, and Qwen as LLM providers. Includes fitness scoring, gene pool inheritance, tiered memory, skill crystallization, Telegram bot, and web dashboard.

Protea — Self-Evolving Artificial Life Agent

A living program that evolves itself. Three-ring architecture running on a single machine.

Architecture

• Ring 0 (Sentinel) — Immutable physics layer. Heartbeat monitoring, git snapshots, rollback, fitness tracking. Pure Python stdlib.
• Ring 1 (Intelligence) — LLM-driven evolution engine, task executor, Telegram bot, skill crystallizer, web dashboard. Multi-LLM support (Anthropic, OpenAI, DeepSeek, Qwen).
• Ring 2 (Evolvable Code) — The living code that evolves, managed in its own git repo by Ring 0.

Prerequisites

• Python 3.11+
• Git
• At least one LLM API key (Anthropic, OpenAI, DeepSeek, or Qwen)

Quick Start

curl -sSL https://raw.githubusercontent.com/EdisonChenAI/protea/main/setup.sh | bash
cd protea && .venv/bin/python run.py

Key Features

• Self-Evolution — LLM generates code mutations each generation; survivors kept, failures roll back
• Fitness Scoring — 6-component scoring (survival, output, diversity, novelty, structure, function)
• Gene Pool — Top 100 code patterns stored in SQLite, injected into evolution prompts
• Tiered Memory — Hot → Warm → Cold → Forgotten, with LLM-assisted curation
• Skill Crystallization — Surviving code patterns extracted as reusable skills
• Multi-LLM — Anthropic, OpenAI, DeepSeek, Qwen via unified interface
• Telegram Bot — Commands + free-text interaction
• Web Dashboard — Local UI at localhost:8899
• 1098 Tests — Comprehensive coverage

Source

GitHub: https://github.com/EdisonChenAI/protea