BabyAGI

BabyAGI

BabyAGI is the original minimal autonomous AI agent framework. It demonstrated that a small loop — execute task → create new tasks → prioritize tasks → repeat — with vector-based memory could autonomously work toward an objective without per-step human guidance.

Key Features

• Task creation loop — after each execution the agent generates follow-up tasks and adds them to the queue
• Priority queue — tasks are re-ranked by relevance to the overall objective after each cycle
• Vector memory — task results are stored in Chroma/Pinecone and retrieved to give future tasks context
• Minimal implementation — the core agent is ~100 lines of Python; easy to understand and extend
• Foundation paper — cited in hundreds of agent papers; the starting point for CrewAI, AutoGPT, and many others
• Modular — swap the LLM backend, vector store, or execution engine without touching the loop

Quick Start

git clone https://github.com/yoheinakajima/babyagi.git
cd babyagi
pip install -r requirements.txt
OPENAI_API_KEY=sk-... OBJECTIVE="Research the latest advances in fusion energy" python babyagi.py

Install via ai-supply

npx ai-supply add babyagi-autonomous-task-agent

Curated mirror of the open-source BabyAGI (MIT). Get it from the source.