Coze | How to use "Multi-agent mode"

In this informative video, Josh MOS introduces the concept of 'Multi-agent mode,' a feature that enables multiple bots to collaborate and complete complex tasks more efficiently. He demonstrates how to transition from a single agent bot to a multi-agent setup, emphasizing the benefits of separating tasks among different bots, thus simplifying complex operations. The video showcases creating an email bot and a calendar bot, each with specific plugins and skills, and how they can be connected using jump conditions to form a workflow. Josh also explains how to enhance the system by adding more nodes and jump conditions for additional functionalities, such as Google Sheets integration. The multi-agent mode is portrayed as a powerful tool that distributes the workload among a team of bots, providing a more streamlined and effective user experience.

Takeaways

• 🤖 Multi-agent mode allows multiple bots to work together to complete complex tasks.
• 📈 It differs from single-agent mode, where one bot handles all tasks with a long prompt.
• 🔄 Bots in multi-agent mode can have their own roles and operate off of jump conditions to switch between tasks.
• 📂 The workspace has a middle section with nodes representing individual agents or bots with their own prompts and skills.
• 🔗 Jump conditions are used to connect different bots and determine when to switch from one bot to another.
• 📧 An example given is an email bot that can send and check emails using the Microsoft Outlook plugin.
• 📅 Another example is a calendar bot that can create, update, and list events on a calendar.
• 📈 By separating tasks into different bots, complex tasks can be completed more efficiently.
• 🔌 Additional plugins can be added to enhance the capabilities of each bot, such as managing Google Sheets.
• 🔙 A global jump condition can be set up to return to the main menu from any bot.
• 📚 For more information on multi-agent mode, refer to the Co documentation and join the community on Discord and Telegram.

Q & A

What is multi-agent mode?

Multi-agent mode is a feature that allows multiple bots to work together and collaborate to complete complex tasks. It differs from single-agent mode, where a single bot handles all tasks based on a long prompt and persona.

How does multi-agent mode help in completing complex tasks?

Multi-agent mode helps in completing complex tasks by separating responsibilities among different bots, each playing its own role. This approach allows for a more efficient and organized way to handle multiple tasks simultaneously.

What is the role of a node in multi-agent mode?

In multi-agent mode, a node represents an agent or a bot that operates based on a specific prompt. It can have skills applied to it, such as plugins, workflows, and knowledge, and can also operate based on jump conditions to transition from one bot to another.

How can a user switch between different bots in multi-agent mode?

A user can switch between different bots in multi-agent mode by triggering jump conditions based on keywords. These conditions are set up to respond to specific user requests, allowing the system to pass control from one bot to another as needed.

What is the purpose of creating a global jump condition?

A global jump condition is a jump condition that applies to all agents in the system. It is used to create a main menu or a central point of control that the user can return to at any time, providing a consistent interface for managing various tasks.

How does the email bot function in multi-agent mode?

The email bot in multi-agent mode is responsible for handling email-related tasks. It uses an Outlook email plugin to send and receive emails, and it can be connected to other bots through jump conditions to collaboratively complete tasks.

What skills can be added to the calendar bot?

The calendar bot can have skills such as creating events, listing events, and updating events. These skills are added through plugins that allow the bot to manage calendar tasks effectively.

Can a user enhance the capabilities of a bot?

Yes, a user can enhance the capabilities of a bot by adding more to the prompt, providing it with additional skills like plugins, workflows, and knowledge bases to improve its functionality.

How can a user connect more functionality to the multi-agent system?

A user can connect more functionality by adding additional nodes and connecting them to other nodes or plugins with jump conditions. This allows for the integration of services like Google Sheets, Notion, or custom plugins as needed.

What is the benefit of having a main menu in multi-agent mode?

Having a main menu in multi-agent mode provides a user with a centralized and easily accessible point to manage and initiate various tasks. It simplifies the interaction with the system and allows users to navigate between different bots and tasks seamlessly.

How does the multi-agent mode differ from single-agent mode in terms of user interaction?

In multi-agent mode, the user interacts with a team of bots, each specialized in different tasks, leading to a more dynamic and efficient experience. In contrast, single-agent mode relies on a single bot to handle all tasks, which might not be as efficient for complex or varied tasks.

What is the significance of jump conditions in multi-agent mode?

Jump conditions are crucial in multi-agent mode as they act as the 'glue' that connects different bots. They determine the flow of work and the transition between bots based on user input, ensuring that the right bot is activated for the task at hand.

Outlines

00:00

🤖 Introduction to Multi-Agent Mode

Josh MOS introduces the concept of multi-agent mode, which allows multiple bots to collaborate and complete complex tasks. He explains that this differs from single-agent mode, where a single bot handles all tasks with a long prompt. In multi-agent mode, bots can specialize in different tasks, which helps in separating concerns and managing complexity. He demonstrates how to set up a multi-agent bot by switching from single-agent mode and creating nodes for different agents, such as an email bot and a calendar bot, each with its own prompt and skills.

05:01

📆 Building a Multi-Agent Bot for Email and Calendar Management

Josh MOS demonstrates how to enhance a multi-agent bot by adding an email bot and a calendar bot. He connects these bots using jump conditions to respond to user commands about emails and calendar events. He shows how to authorize the email bot with Microsoft Outlook and how it can send and check emails. Additionally, he connects the calendar bot to the Outlook calendar plugin, enabling it to create, list, and update calendar events. He also discusses the potential to add more nodes for other functionalities like Google Sheets and emphasizes the importance of jump conditions in orchestrating the workflow among different bots.

Keywords

Multi-agent mode

Multi-agent mode refers to the capability of multiple AI agents or bots to work collaboratively to accomplish complex tasks. In the video, this concept is central as it allows the division of tasks among different bots, each with its own specialized skills, rather than having a single bot handle all responsibilities. This approach enhances efficiency and allows for the completion of more sophisticated tasks by leveraging the strengths of each bot.

Single agent mode

Single agent mode is a setup where a single AI bot is responsible for taking a prompt and using its skills to complete tasks. It contrasts with multi-agent mode, as depicted in the video where the host starts with a personal assistant bot in single agent mode that can send and check emails before transitioning to a more complex multi-agent setup.

Persona

In the context of the video, 'Persona' likely refers to the character or role that an AI bot is designed to play. It influences how the bot interacts with users and what tasks it is expected to perform. The persona is important as it guides the bot's behavior and the dialogue it engages in with users.

Prompt

A prompt in this AI context is an input or command given to the bot that triggers a specific action or response. It is a fundamental part of how users interact with the AI, as demonstrated when the host gives a command to check emails or create a calendar event, which the respective bots then act upon.

Plugins

Plugins in the video are additional functionalities that can be integrated into the AI bots to extend their capabilities. For instance, the Outlook email plugin allows the email bot to send and receive emails, while the Outlook calendar plugin enables the calendar bot to create and manage events. They are essential for customizing the bot's skills to perform specific tasks.

Workflows

Workflows are the sequences of steps that the AI bots are programmed to follow to complete a task. They are part of the bot's operational logic and are crucial in multi-agent mode for coordinating the actions of different bots to achieve a complex outcome. In the script, workflows are implied in the process of how bots handle email and calendar management.

Jump conditions

Jump conditions are triggers within the AI system that dictate when to switch from one bot or task to another. They are integral to the multi-agent mode, allowing for a seamless transition between different bots as the user's needs change. In the video, jump conditions are set up to respond to keywords and direct the user to the appropriate bot for their request.

Microsoft Outlook

Microsoft Outlook is an email and calendaring service used by the AI bots in the video to manage emails and calendar events. The use of Outlook plugins within the AI bots showcases how real-world applications can be integrated into AI systems to provide practical and familiar services to users.

Google Sheets

Google Sheets is a cloud-based spreadsheet service mentioned in the video as an additional service that could be integrated with AI bots through plugins. It illustrates the potential for AI to interface with various digital tools to assist with tasks such as data management and collaboration.

Authorization

In the context of the video, authorization refers to the process of granting permission for the AI bot to access and use a user's email account, as required by Microsoft Outlook. This step is crucial for the bot to perform email-related tasks on behalf of the user and highlights the importance of security and user consent in AI interactions.

Main menu

The main menu in the video serves as the primary interface for the user to interact with the AI bot. It is where the user can select different tasks or functionalities that the bot can perform. The concept of a main menu is important as it provides a clear and accessible point of entry for users to engage with the multi-agent system.

Highlights

Multi-agent mode allows multiple bots to collaborate and complete complex tasks.

It differs from single agent mode, which typically uses a long prompt and persona to complete tasks.

In multi-agent mode, bots can play distinct roles and offload responsibilities.

The transition between bots is facilitated by jump conditions triggered by keywords.

Creating a multi-agent bot involves defining a starting point and nodes for each agent.

Each node represents an agent with its prompt, skills, and jump conditions.

The system bot acts as a main menu, prompting the user for desired actions.

Email bot is created for managing email tasks using the Microsoft Outlook plugin.

Calendar bot is introduced for creating, updating, and listing calendar events.

Jump conditions are used to connect different bots and determine the workflow.

Adding more nodes allows for integration of additional functionalities like Google Sheets.

Global jump condition enables users to return to the main menu from any bot.

The multi-agent mode helps distribute tasks among bots, reducing the load on a single bot.

Bots can be enhanced by adding more skills like plugins, workflows, and knowledge bases.

Custom plugins can be created for services not natively supported.

The system demonstrates the ability to switch between email, calendar, and Google Sheets agents.

The multi-agent mode provides a scalable solution for handling complex and varied tasks.

For more information, users are directed to Coze's documentation and community channels.