XAgent

It is an open-source experimental Large Language Model (LLM) driven autonomous agent designed to automatically solve a wide range of complex tasks.

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XAgent AI Agent Competitors

It is an open-source experimental Large Language Model (LLM) driven autonomous agent designed to automatically solve a wide range of complex tasks. XAgent is a general-purpose tool that can handle tasks such as data analysis, coding, model training, and more. It operates using a three-part system, with the ToolServer being a key component that provides a safe and powerful environment for task execution. The ToolServer is a docker container that ensures secure and efficient operation of XAgent.

To use XAgent, users must first install docker and docker-compose, then build the ToolServer image. Once set up, XAgent can be run, and users can upload initial files for processing. The local workspace, located in `local_workspace`, stores all files generated during the task execution. After completion, the workspace is copied to `running_records`, where users can review intermediate steps, task statuses, and LLM input-output pairs. XAgent also allows users to reproduce previous runs by loading records tied to specific code versions.

XAgent is capable of breaking down complex tasks into sub-tasks, such as data inspection, environment verification, code generation, and report compilation. It can also actively seek human assistance when necessary, enhancing its problem-solving capabilities. For example, in a restaurant recommendation scenario, XAgent used the AskForHumanHelp tool to gather additional details from the user, enabling it to provide personalized suggestions.

The system has been evaluated on over 50 real-world tasks across categories like Search and Report, Coding, Data Analysis, Math, and Life Assistant. XAgent has shown significant improvements over AutoGPT in terms of human preference and performance on benchmarks. The project is open to collaborations and contributions, with the goal of creating a super-intelligent agent capable of solving any task. For more information, users can visit the XAgent Official Website, check the live demo, or refer to the documentation and blog. Contributions and feedback are highly valued, and users are encouraged to cite the project if they find it useful.

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