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Basic Information

XAgent is an open-source experimental autonomous agent driven by large language models, designed to automatically solve a wide range of tasks without human intervention while also supporting human collaboration. The system bundles an agent runtime, a ToolServer for safe tool execution inside Docker, and both GUI and command-line interfaces so users can interact with the agent. XAgent decomposes tasks into subtasks via a Planner, dispatches work to different agents via a Dispatcher, and executes actions with an Actor that uses tools such as a file editor, Python notebook, web browser, shell, and Rapid API connectors. The project includes setup instructions, configuration via assets/config.yml, instructions for supplying OpenAI API keys and recommended models, examples and demos, and facilities to record and reproduce runs including intermediate steps and LLM inputs and outputs.

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App Details

Features
XAgent emphasizes autonomy, safety, extensibility and observability. Autonomy: it plans and executes multi-step tasks by splitting goals into milestones. Safety: all action tools run inside a ToolServer Docker container to limit side effects. Extensibility: developers can add new tools and agents and change configuration via assets/config.yml. Toolset: built-in tools include a text file editor, interactive Python notebook, web browser, shell, and Rapid API access. Interfaces: a web GUI (default guest account) and CLI are provided. Architecture: a Dispatcher for task routing, a Planner for plan generation and correction, and an Actor that runs tools and can ask for human help. Reproducibility: run records, local_workspace, and running_records capture execution traces and intermediate artifacts.
Use Cases
XAgent helps users and researchers automate complex, multi-step workflows end-to-end by combining LLM planning with executable tools. It can assist with data analysis, coding and development tasks, recommendations, model training, and general life-assistant queries by breaking tasks into subtasks, validating code in a Python notebook, running shell commands, browsing the web, and editing files. Its dockerized ToolServer provides a safer environment for executing actions and its recording features let users reproduce and inspect runs. The agent can solicit human help when inputs are insufficient, supports both GUI and CLI interactions, and includes examples, demos, and evaluation material comparing performance to other autonomous agents.

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