Welcome to the Getting Started Tutorial! This tutorial is designed to walk you through the process of setting up and running your own AutoGPT agent in the Forge environment. Whether you are a seasoned AI developer or just starting out, this guide will equip you with the necessary steps to jumpstart your journey in the world of AI development with AutoGPT.
This is part 1 of a series of tutorials on how to use build your own AI Agents using the AutoGPT Forge.
Section 1: Understanding the Forge
The Forge serves as a comprehensive template for building your own AutoGPT agent. It not only provides the setting for setting up, creating, and running your agent, but also includes the benchmarking system and the frontend. These integrated components facilitate the development and performance evaluation of your agent.
It plays a pivotal role in the AutoGPT ecosystem, functioning as the stem from which an agent is created. It is designed to be integrated with the agent protocol, the benchmark system, and the AutoGPT frontend, thereby forming a cohesive and robust environment for agent development.
This harmonization ensures that developers adhere to a standardized framework, which significantly streamlines the development process. Consequently, it eliminates the need to construct boilerplate code, allowing developers to channel their efforts and creativity directly into crafting the “brains” of the agent. By focusing on enhancing the agent’s intelligence and functionalities, developers can truly leverage the potential of AutoGPT, creating agents that are not only efficient but also innovative and advanced. The Forge, therefore, stands as a beacon of innovation and efficiency, propelling the development of AutoGPT agents to new heights.
This project supports Linux (Debian based), Mac, and Windows Subsystem for Linux (WSL). If you are using a Windows system, you will need to install WSL. You can find the installation instructions for WSL here.
Section 2: Setting up the Forge Environment
To begin, you need to fork the repository by navigating to the main page of the repository and clicking “Fork” in the top-right corner. Remember to hit star, if you have not already!
Follow the on-screen instructions to complete the process.
Cloning the Repository
Next, clone the repository to your local system. Ensure you have Git installed to proceed with this step. You can download Git from here. Then clone the repo using the following command and the url for your repo. You can find the corect url by clicking on the green Code button on your repos main page.
# replace the url with the one for your forked repo
git clone https://github.com/Significant-Gravitas/Auto-GPT.git
Setting up the Project
Once you have clone the project change your directory to the newly cloned project:
# The name of the directory will match the name you gave your fork. The defualt is Auto-GPT
To set up the project, utilize the ./run setup command in the terminal. Follow the instructions to install necessary dependencies and set up your GitHub access token.
Note: for advanced users. The github access token is only needed for the ./run arena enter command so the system can automatically create a PR
Section 3: Creating Your Agent
Choose a suitable name for your agent. It should be unique and descriptive. Examples of valid names include swiftyosgpt, SwiftyosAgent, or swiftyos_agent.
Create your agent template using the command:
./run agent create YOUR_AGENT_NAME
Replacing YOUR_AGENT_NAME with the name you chose in the previous step.
Section 4: Running Your Agent
Begin by starting your agent using the command:
./run agent start YOUR_AGENT_NAME`
This will initiate the agent on http://localhost:8000/
Logging in and Sending Tasks to Your Agent
Access the frontend at http://localhost:8000/ and log in using a Google or GitHub account. You can then send tasks to your agent through the interface.
Stopping and Restarting Your Agent
When needed, use Ctrl+C to end the session or use the stop command:
./run agent stop
This command forcefully stops the agent. You can also restart itby using the start command.
In our exploration today, we’ve covered the essentials of working with AutoGPT projects. We began by laying out the groundwork, ensuring you have all the right tools in place. From there, we delved into the specifics of building an effective AutoGPT agent. Trust me, with the right steps, it becomes a straightforward process.
Next Steps: Building and Enhancing Your Agent
With the foundation set, you are now ready to build and enhance your agent, exploring various functionalities and improving its performance. The next tutorial will look into the anatomy of an agent and how to add some basic functionality.