ARGO is an open-source AI Agent platform designed for local, private AI assistant deployment. It targets users seeking autonomous task planning, RAG capabilities, and seamless integration of both open-source and closed-source LLMs, with a strong emphasis on data privacy and offline operation.

How It Works

ARGO utilizes a multi-agent task engine for autonomous planning, tool calling, and execution of complex, multi-stage tasks. Its Agentic RAG engine intelligently decomposes issues and leverages local knowledge bases, supporting various data sources and dynamic synchronization. The platform integrates with Ollama and major LLM providers, allowing flexible model switching and offering a built-in toolset with MCP protocol support for custom extensions.

Quick Start & Requirements

• Installation: Native installers for Windows, macOS, and Linux are available. Docker Compose options are provided for CPU and GPU configurations.
• Prerequisites: Docker >= 24.0.0 and Docker Compose >= v2.26.1 are required for Docker installations. GPU support via Docker requires the Nvidia CUDA container toolkit.
• Access: ARGO is accessible at http://localhost:38888 after setup.
• Documentation: Quick Start Guide

Highlighted Details

• Supports one-click Ollama integration and HuggingFace GGUF model downloads.
• Features an "Agent Factory" for customizing agents via visual scenario creation, role setting, and tool integration.
• Provides "Agentic RAG" for intelligent decomposition of complex issues and traceable answers.
• Offers native clients for Windows, macOS, and Linux with plug-and-play, zero-dependency installation.

Maintenance & Community

The project is actively being developed and welcomes contributions. Community channels include Discord, Twitter, and WeChat groups.

Licensing & Compatibility

The project is released under the LICENSE file, which is typically MIT for open-source projects, allowing for commercial use and closed-source linking.

Limitations & Caveats

The project is in its early stages of development, and users may encounter usability issues or instability. Features like "Self-Evolving Agent" are noted as being in testing.