Build AI agent workforce - Multi agent framework with MetaGPT & chatDev

The video discusses the burgeoning field of autonomous AI agents, highlighting their increasing integration into the workforce. It outlines the four key components of AI agents: profile, memory, planning, and tool/API usage. The framework for multi-agent collaboration is explored through projects like MetaGPT and chatDev, which enable the creation of specialized agent teams to tackle complex tasks. chatDev, in particular, is praised for its customization options, allowing users to simulate various team structures and workflows. A step-by-step guide is provided for setting up chatDev, from cloning the GitHub repository to defining agent roles and tasks. The video also touches on the ethical considerations of AI content generation, referencing research by HubSpot and Jasper, and concludes with a demonstration of how chatDev can be used to create a simple snake game, showcasing the potential of AI agents in software development.

Takeaways

• 🤖 The emergence of autonomous AI agents has been a hot topic since the introduction of Auto GPT and PB AGI, with AI agents capable of performing complex tasks autonomously.
• 📚 AI agents consist of four main components: profile, memory, the ability to use large language models for planning, and the ability to use various tools and APIs to complete tasks.
• 📈 The paper 'A Survey on Large Language Model Based Autonomous Agents' provides a deep dive into the world of AI agents, and there's also a video on building research-performing autonomous agents.
• 🔮 Predictions suggest that within the next 6 to 12 months, AI agents will be integrated into the workforce for specialized tasks across various fields like design, development, and product management.
• 🤝 Multi-agent frameworks like MetaGPT and chatDev are gaining popularity, allowing for the creation of teams of agents with different specialties to work together on complex tasks.
• 💬 Projects like CAMEL and Adrian verse are exploring multi-agent simulations, providing insights into how different agents can collaborate and interact in various scenarios.
• 🛠️ chatDev offers customization and flexibility with three key components: roles, faces (specific tasks and stages), and chat chain (defining the sequence of tasks in a project).
• 📝 chatDev can be used to create customized teams for different tasks, such as a content operation team for idea generation, research, and content writing.
• 🔗 HubSpot and Jasper's research explores the limitations and pitfalls of using AI in content creation, providing insights for content creators on how to scale their content generation with AI.
• 💻 Setting up chatDev involves cloning the GitHub repo, setting up the Python environment, installing dependencies, and configuring the OpenAI API key.
• 🐍 chatDev can automate the creation of simple software applications, such as a snake game, with a fully functional and visually appealing result.
• 📋 The chatDev framework includes a web app for visualizing the team's work process, allowing users to replay and analyze the conversation history between different agents.

Q & A

What are the four big components of an AI agent?

The four big components of an AI agent are the profile, memory, the ability to use large language models for planning, and the ability to use different tools and APIs to complete tasks.

What is the role of the 'profile' in an AI agent?

The profile in an AI agent defines who the agent is and what its role is within a system or framework.

How does an AI agent's 'memory' function?

An AI agent's memory allows it to have both domain knowledge and short-term memory, enabling it to remember what happened before and apply that knowledge to future tasks.

What is the significance of using large language models in AI agents?

Large language models enable AI agents to plan by breaking down big goals into subtasks, which helps in the autonomous completion of complex tasks.

Can you explain the concept of multi-agent frameworks like MetaGPT and chatDev?

Multi-agent frameworks like MetaGPT and chatDev allow the creation of teams of agents with different specialties. These frameworks orchestrate these agents to work together to complete very complex tasks.

What is the 'rows' component in chatDev?

In chatDev, 'rows' refers to defining different types of agents, such as a boss, product managers, CTO, and QA, each with specific roles within a team.

What does 'faces' represent in the context of chatDev?

'Faces' in chatDev means defining specific tasks and stages for the agents to perform, starting from demand analysis to coding, code review, testing, and documentation writing.

How does the chatDev framework allow customization for different teams?

ChatDev allows customization by setting up different types of agents in 'rows', defining tasks in 'faces', and orchestrating the phases of work in 'chat chain'. Users can modify these components to fit the requirements of any team or task.

What kind of software can the default team in chatDev deliver?

The default team in chatDev can deliver compact software solutions like a classic ping pong game, Flappy Bird, a calculator, a 2048 game, and even an image editor.

How does the chatDev framework handle the generation of tasks for AI agents?

ChatDev handles task generation by allowing users to input a task through a command line interface, which then initiates a series of conversations between different agents to complete the task.

What are the steps to set up chatDev on a computer?

To set up chatDev, you first clone the GitHub repo, open the project in Visual Studio Code, set up the Python environment, install the required dependencies, and then set up your OpenAI API key specific to your operating system.

How can users customize their own AI agent teams in chatDev?

Users can customize their own AI agent teams in chatDev by modifying the 'company config' folder, which includes defining agents in 'raw config', setting up tasks in 'face config', and establishing the standard procedure in 'chat chain config'.

Outlines

00:00

🤖 Introduction to Autonomous AI Agents

The first paragraph introduces the concept of autonomous AI agents, which have become a hot topic following the release of Auto GPT and PB AGI. It discusses the four main components of AI agents: profile, memory, planning using large language models, and the ability to use various tools and APIs. The paragraph also references a research paper for further reading and a video on building research-performing autonomous agents. It ends by expressing optimism about the integration of AI agents into the workforce and the potential for specialized AI agents for different tasks.

05:02

🚀 Multi-Agent Collaboration and Projects

The second paragraph delves into how multiple AI agents can collaborate on complex tasks. It mentions the 'camel' project, which simulates conversations between different agents, and 'Adrian verse' for multi-agent simulations. The paragraph highlights two multi-agent frameworks, 'meta GPT' and 'chat Dev', which have gained popularity on GitHub. It provides an overview of how to create a team of agents with chat Dev, emphasizing its customization and flexibility. The paragraph also describes setting up chat Dev, including cloning the GitHub repo, setting up the Python environment, and using the open AI API key.

10:04

📚 Customizing AI Agent Teams with chat Dev

The third paragraph focuses on customizing AI agent teams using chat Dev. It explains the process of setting up a new team configuration, defining roles, and creating a standard procedure for software development. The paragraph provides a step-by-step guide on how to create an AI marketing agency team, detailing the creation of roles such as marketing director and marketing specialist. It also covers the process of defining faces for different tasks, updating the chat chain configuration, and running tasks with the new team. The paragraph concludes by inviting viewers to share their interesting agent use cases in the comments.

Keywords

AI agents

AI agents in the context of the video refer to autonomous artificial intelligence entities capable of performing complex tasks independently. They are likened to a professional team, each with a specific role and function, which can collaborate to achieve a common goal. The video discusses how these agents can be integrated into a workforce, highlighting their potential to revolutionize various industries.

Multi-agent framework

A multi-agent framework is a system that allows multiple AI agents to operate and interact with each other. It is the foundation for creating a collaborative environment where different AI agents can work together to accomplish complex tasks. In the video, frameworks like MetaGPT and chatDev are mentioned as examples of such systems, which are gaining popularity for their ability to orchestrate teams of AI agents with different specialties.

Large language model

A large language model is an AI system designed to process and understand human language at scale. These models are integral to AI agents as they enable them to plan and break down large goals into subtasks, as well as interact with humans in a natural language. The video emphasizes the importance of large language models in the planning ability of AI agents.

APIs

API stands for Application Programming Interface, which are sets of protocols and tools that allow different software applications to communicate with each other. In the context of the video, AI agents utilize APIs to access and use various digital tools and services to complete tasks, showcasing their versatility and capability to integrate with existing technologies.

chatDev

chatDev is a multi-agent framework highlighted in the video that allows users to create and customize teams of AI agents for different tasks. It provides components like rows, faces, and chat chains, which enable the definition of agent types, tasks, and the workflow for completing those tasks. The video demonstrates how chatDev can be used to create specialized AI teams for software development and content creation.

Customization

Customization in the video refers to the ability to tailor the AI agents' roles, tasks, and the overall workflow to suit specific needs or scenarios. It is a key feature of platforms like chatDev, which enables users to create unique AI teams for various applications, from software development to content operations, as demonstrated in the step-by-step guide provided.

Content generation

Content generation is the process of creating new content, often in the context of digital media and online publishing. The video discusses the use of AI agents for content generation, where they can autonomously create content such as blog posts, social media updates, and newsletters. This is particularly relevant in the context of scaling content operations and exploring the creative potential of AI.

AI in content creation

The use of AI in content creation is a topic of discussion in the video, where it explores the capabilities and limitations of AI-generated content. It mentions a research paper by HubSpot and Jasper that delves into the implications of using AI for content creation, including potential penalties from search engines like Google for AI-generated content.

Technical details

Technical details in the context of the video pertain to the specific instructions and steps required to set up and use the chatDev framework. This includes cloning the GitHub repository, setting up the Python environment, installing dependencies, and configuring the OpenAI API key. The video provides a walkthrough of these technical details to help users get started with creating their own AI agent teams.

Simulation

Simulation in the video refers to the ability of multi-agent frameworks to mimic real-world scenarios and interactions. Examples given include simulating conversations between different professionals, such as a Python programmer and a stock trader, to achieve a goal like building a trading bot. This capability is crucial for testing and developing AI agents' collaborative skills in a controlled environment.

GitHub

GitHub is a web-based platform for version control and collaboration used by developers to manage and contribute to software projects. In the video, GitHub is mentioned as the platform where chatDev and MetaGPT, the multi-agent frameworks, are hosted. It is where users can access, clone, and contribute to the development of these frameworks, highlighting the collaborative and open-source nature of the AI community.

Highlights

AI agents are becoming a hot topic with the advent of autonomous AI agents capable of performing complex tasks autonomously.

AI agents consist of four components: profile, memory, planning with large language models, and the ability to use tools and APIs.

Multi-agent frameworks like MetaGPT and chatDev allow for the creation of teams of agents with different specialties.

Frameworks provide a playground to simulate conversations between multiple agents for complex tasks.

Camel is an example of a multi-agent system that simulates conversations between different agents for social experiments.

ChatDev is a multi-agent framework that allows for customization and flexibility in creating AI agent teams.

Key components in ChatDev include roles, faces (tasks), and chat chains (stages).

ChatDev can be used to create software like a ping pong game, Flappy Bird, a calculator, or even an image editor.

Customization in ChatDev allows for the creation of specialized teams like a content operation team for 24/7 content creation.

AI content generation raises questions about potential penalties from search engines like Google and limitations to be aware of.

HubSpot and Jasper conducted research to explore the limitations and pitfalls of using AI in content creation.

Setting up ChatDev involves cloning the GitHub repo, setting up the Python environment, and installing dependencies.

An OpenAI API key is required for ChatDev, with different setup instructions for Mac and Windows.

ChatDev can generate tasks for a development team, such as building a classic snake game.

ChatDev provides a web app for visualizing how the team of agents works together on a task.

Customizing ChatDev involves setting up a company config with roles, faces, and chat chains.

A step-by-step guide is provided to create content operation teams or other specialized AI agent teams.

The process of creating an AI marketing agency team involves defining roles, tasks, and standard procedures.

ChatDev allows for the simulation of conversations between agents to generate ideas and content for marketing campaigns.

The final product of an AI agent team's task can be found in a project folder under the 'Warehouse' directory.