Free Open Source Tool Archon Makes AI Agents as Easy as Operating a Dashboard

Archon is a project for building, optimizing, and managing AI agents, and is billed as the world's first "Agenteer", i.e., an AI agent that can autonomously build, improve, and optimize other AI agents. Below is a detailed description of the repository:

Project Overview

• core functionality: Archon aims to demonstrate three key principles in modern AI development, namely agent reasoning, domain knowledge integration, and scalable architecture. It can be used as a practical tool for developers or as an educational framework to demonstrate the development of agent systems.
• Version Iteration: The project takes an iterative approach to development, starting with a simple Pydantic AI agent and progressing to a full agent workflow using LangGraph, capable of building other AI agents using any framework.

Current version (V4)

• specificities: The V4 release has undergone a massive Streamlit UI revamp, providing a comprehensive dashboard interface for managing Archon.
• Important Updates: The environment variable system has been radically improved and made more intuitive, divided into separate sections for LLM and embedded providers, making it easy to switch between providers and manage configuration files.

Project structure

• home directory (computing): Contains the main runtime scripts (e.g. run_docker.py), dependency files (e.g. requirements.txt) and UI scripts (such as streamlit_ui.py).
• archon/ catalogs: Includes core functionality code such as crawl_pydantic_ai_docs.py for crawling and processing Pydantic AI documents.pydantic_ai_coder.py Coding logic that may be used to implement Pydantic AI agents.
• streamlit_pages/ catalogs: Contains the various pages of the Streamlit UI, such as the agent_service.py,chat.py,database.py etc., which correspond to different functional modules.
• iterations/ catalogs: Contains code from various iterations of the project, such as the v1-single-agent,v2-agentic-workflow,v3-mcp-support respond in singing v4-streamlit-ui-overhaulThe
• mcp/ catalogs: May contain MCP (Multi - Container Platform) related code and configuration.

Database settings

• SQL files::utils/site_pages.sql respond in singing iterations/v2-agentic-workflow/ollama_site_pages.sql For creating and configuring a PostgreSQL database, including enabling the pgvector Expansion, Creation site_pages tables, adding indexes and defining search functions, etc.

Docker Support

• scripts::run_docker.py respond in singing iterations/v4-streamlit-ui-overhaul/run_docker.py Docker containers for building and running Archon, including building MCP containers and master Archon containers, handling environment variables, and stopping and deleting existing containers when they are already running.

data structure

• ChatMessage resemble: in Archon/iterations/v1-single-agent/streamlit_ui.py Defined in the role,timestamp respond in singing content Fields.
• ProcessedChunk resemble: Defined in multiple documents, such as Archon/archon/crawl_pydantic_ai_docs.py,Archon/iterations/v1-single-agent/crawl_pydantic_ai_docs.py etc., which are used to represent the processed document chunks containing the url,chunk_number,title,summary,content,metadata respond in singing embedding Fields.

Quick Start

pre-conditions

• Docker (optional but recommended)
• Python 3.11+
• Supabase account (for vector databases)
• OpenAI/Anthropic/OpenRouter API key or Ollama for native large language modeling

Installation steps

• Docker approach (recommended)::
  1. Cloning Warehouse:git clone https://github.com/coleam00/archon.git && cd archon
  2. Run the Docker script:python run_docker.py
  3. Access the Streamlit UI:http://localhost:8501
• Local Python Installation::
  1. Cloning Warehouse:git clone https://github.com/coleam00/archon.git && cd archon
  2. Create a virtual environment and install dependencies:python -m venv venv && source venv/bin/activate && pip install -r requirements.txt
  3. Start the Streamlit UI:streamlit run streamlit_ui.py
  4. Access the Streamlit UI:http://localhost:8501

Important Links

• V4 Documentation::V4 Documentation
• Community Forum::Archon community
• GitHub Kanban::GitHub Kanban board