OpenBMB/XAgent
Python
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source ↗OpenBMB/XAgent
Description: An Autonomous LLM Agent for Complex Task Solving
Language: Python
License: Apache-2.0
Stars: 8529
Forks: 904
Open issues: 61
Created: 2023-10-16T03:44:57Z
Pushed: 2024-08-12T06:41:38Z
Default branch: main
Fork: no
Archived: no
README:
XAgent
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Tutorial • Demo • Blog • Documentation • Citation
📖 Introduction
XAgent is an open-source experimental Large Language Model (LLM) driven autonomous agent that can automatically solve various tasks. It is designed to be a general-purpose agent that can be applied to a wide range of tasks. XAgent is still in its early stages, and we are working hard to improve it.
🏆 Our goal is to create a super-intelligent agent that can solve any given task!
We welcome diverse forms of collaborations, including full-time and part-time roles and more. If you are interested in the frontiers of agents and want to join us in realizing true autonomous agents, please contact us at xagentteam@gmail.com.
XAgent
XAgent is designed with the following features:
- Autonomy: XAgent can automatically solve various tasks without human participation.
- Safety: XAgent is designed to run safely. All actions are constrained inside a docker container. Run it anyway!
- Extensibility: XAgent is designed to be extensible. You can easily add new tools to enhance agent's abilities and even new agents!
- GUI: XAgent provides a friendly GUI for users to interact with the agent. You can also use the command line interface to interact with the agent.
- Cooperation with Human: XAgent can collaborate with you to tackle tasks. It not only has the capability to follow your guidance in solving complex tasks on the go but it can also seek your assistance when it encounters challenges.
XAgent is composed of three parts:
- 🤖 Dispatcher is responsible for dynamically instantiating and dispatching tasks to different agents. It allows us to add new agents and improve the agents' abilities.
- 🧐 Planner is responsible for generating and rectifying plans for tasks. It divides tasks into subtasks and generates milestones for them, allowing agents to solve tasks step by step.
- 🦾 Actor is responsible for conducting actions to achieve goals and finish subtasks. The actor utilizes various tools to solve subtasks, and it can also collaborate with humans to solve tasks.
🧰 ToolServer
ToolServer is the server that provides XAgent with powerful and safe tools to solve tasks. It is a docker container that provides a safe environment for XAgent to run. Currently, ToolServer provides the following tools:
- 📝 File Editor provides a text editing tool to write, read, and modify files.
- 📘 Python Notebook provides an interactive Python notebook that can run Python code to validate ideas, draw figures, etc.
- 🌏 Web Browser provides a web browser to search and visit webpages.
- 🖥️ Shell provides a bash shell tool that can execute any shell commands, even install programs and host services.
- 🧩 Rapid API provides a tool to retrieve APIs from Rapid API and call them, which offers a wide range of APIs for XAgent to use. See ToolBench to get more information about the Rapid API collections.
You can also easily add new tools to ToolServer to enhance XAgent's abilities.
✨ Quickstart
🛠️ Build and Setup ToolServer
ToolServer is where XAgent's action takes place. It is a docker container that provides a safe environment for XAgent to run. So you should install docker and docker-compose first. Then, you need to build the ToolServer image. Construct referring to any one of the following methods:
Pull the image from docker hub by running the following command:
docker compose up
Build an image from local sources by running the following command:
docker compose build docker compose up
This will build the image for the ToolServer and start the ToolServer's container. If you want to run the container in the background, please use docker compose up -d. Refer [here](ToolServer/README.md) for detailed information about our ToolServer.
If the ToolServer is updated, you have to repull/rebuild the images:
docker compose pull
Or
docker compose build
🎮 Setup and Run XAgent
After setting up ToolServer, you can start to run XAgent.
- Install requirements (Require Python >= 3.10)
pip install -r requirements.txt
- Configure XAgent
1. You should configure XAgent in assets/config.yml before running it. 2. At least one OpenAI key is provided in assets/config.yml, which is used to access OpenAI API. We highly recommend using gpt-4-32k to run XAgent; gpt-4 is also OK for most simple tasks. In any case, at least one gpt-3.5-turbo-16k API key should be provided as a backup model. We do not test or recommend using gpt-3.5-turbo to run XAgent due to minimal context length; you should not try to run XAgent on that. 3. If you want to change the config_file path for XAgentServer, you should modify the CONFIG_FILE value in .env file and restart the docker container.
- Run XAgent
python run.py --task "put your task here" --config-file "assets/config.yml"
1. You can use the argument --upload-files to select the initial files you want to submit to XAgent.
2. The local workspace for your XAgent is in local_workspace, where you can find all the files generated by XAgent throughout the running process.
3. After execution, the entire workspace in ToolServerNode will be copied to running_records for your convenience.
4. Besides, in running_records, you can find all the intermediate steps information, e.g., task statuses, LLM's input-output pairs, used tools, etc.
5. You can load from a record to reproduce a former run, just by setting record_dir in config(default to Null). The record is a system-level recording tied to the code version of XAgent. All running-config、query、code execution statuses (including errors)、server behavior will be documented.
6. We have removed all sensitive information (including API keys) from the record so you can safely share it with others. In the near future, we will introduce more granular sharing options highlighting the contributions of humans during execution.
- Run XAgent with GUI
The container XAgent-Server is started with nginx and a web server listening on port 5173. You could visit…
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