# XAgent — Autonomous AI Agent for Complex Task Solving

> XAgent is an open-source autonomous agent framework that decomposes complex tasks into subtasks, plans execution strategies, and uses tool calling to complete multi-step workflows with minimal human intervention.

## Install

Save in your project root:

# XAgent — Autonomous AI Agent for Complex Task Solving

## Quick Use
```bash
git clone https://github.com/OpenBMB/XAgent.git
cd XAgent
pip install -r requirements.txt
python run.py --task "Analyze the top 10 Python packages by downloads"
```

## Introduction
XAgent is an autonomous AI agent framework developed by OpenBMB that breaks down complex tasks into manageable subtasks, creates execution plans, and carries them out using a combination of LLM reasoning and tool use. It supports human-in-the-loop interaction and provides a web interface for monitoring agent progress.

## What XAgent Does
- Decomposes user goals into structured subtask trees
- Plans and executes multi-step workflows autonomously
- Uses tool calling (web search, code execution, file operations)
- Supports human-in-the-loop mode for guidance at decision points
- Provides a web-based UI for real-time task monitoring

## Architecture Overview
XAgent uses a dual-loop architecture. The outer loop manages high-level planning and task decomposition, while the inner loop handles individual subtask execution with tool dispatch. A ToolServer component runs tools in sandboxed Docker containers for safety. The dispatcher routes between planning and execution phases, maintaining a persistent task state that enables recovery from failures.

## Self-Hosting & Configuration
- Clone the repository and install Python dependencies
- Configure API keys for the LLM backend (supports OpenAI and compatible APIs)
- Start the ToolServer via Docker for sandboxed tool execution
- Launch the web UI for interactive monitoring
- Adjust planning depth and tool permissions in the config file

## Key Features
- Hierarchical task decomposition with plan-then-execute strategy
- Sandboxed tool execution via Docker-based ToolServer
- Human-in-the-loop mode for supervised autonomous operation
- Web UI with real-time task tree visualization
- Supports multiple LLM backends through OpenAI-compatible API

## Comparison with Similar Tools
- **AutoGPT** — loop-based autonomous agent; XAgent uses structured planning with subtask trees
- **CrewAI** — multi-agent role-based framework; XAgent is a single-agent planner-executor
- **LangChain Agents** — tool-calling agents within a chain; XAgent provides deeper task decomposition
- **MetaGPT** — multi-agent software engineering; XAgent targets general-purpose task solving

## FAQ
**Q: What LLMs does XAgent support?**
A: It works with GPT-4, GPT-3.5, and any model accessible through an OpenAI-compatible API.

**Q: Is XAgent safe to run?**
A: Tool execution happens in sandboxed Docker containers. Human-in-the-loop mode adds an additional safety layer.

**Q: Can it handle coding tasks?**
A: Yes, it can write, execute, and debug code as part of its task-solving workflow.

**Q: How does it differ from simple ReAct agents?**
A: XAgent creates a full task tree before execution, enabling more structured and recoverable workflows than single-loop ReAct patterns.

## Sources
- https://github.com/OpenBMB/XAgent
- https://blog.openbmb.org/xagent/

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Source: https://tokrepo.com/en/workflows/asset-51e958c5
Author: AI Open Source