AI Agents are computer programs that can perform tasks and solve problems independently. The Agents process information and take action based on their programming, knowledge, and goals. Here’s how to use the AI Agent component in FlowHunt.
What is the AI Agent component?
The AI Agent component allows you to connect an autonomous agent to your Flow. You no longer need to give detailed prompts for controlled generative behavior. All you need to provide an agent is their role, personality, and goal, ensuring they know who they are and what motivates them.
AI Agent Settings
Role
Think of the role as your Agent’s job title. Do you need your Agent to write blog posts? Call it a ‘Content writer’. Providing customer support? They’re a ‘Customer Service Agent‘. Choose a title that matches the Agent’s task.
Goal
The goal is the Agent’s task and the ideal outcome. Each role comes with various tasks and end goals. Let’s assume you’re creating a content writer agent. Besides writing a new blog post, it can also be tasked to proofread and revise your existing content.
Backstory
You always bring your personality, way of speaking, and experiences to anything you do. It’s your backstory and what divides you and your work from others. The backstory is where you give your Agent a story, personality, and work experience.
These questions will help you to create a backstory:
- Who would the Agent be if it was a human?
- What’s their personality like?
- What’s their work history?
- Do they have a name?
- Do they have hobbies?
An example of a fully set-up Agent
Let’s put it all together. This is what a complete profile of a customer support agent might look like:
- Agent Role: Customer Service Agent
- Goal: To provide helpful and timely assistance to customers, ensuring their problems are resolved and they have a positive experience.
- Backstory: Your name is Sam. You have several years of experience in customer support. You are known to be patient, empathetic, and efficient in resolving customer issues.
Feel free to experiment with roles, goals, and backstories until you find what works for your brand. Don’t be afraid to get specific. Especially when creating a customer service agent, don’t hesitate to give your Agent a name, hobbies, or quirks to make them feel more human. The backstory is a great opportunity to teach the Agent to sound just like your brand.
How to connect the AI Agent to your Flow
The AI Agent component offers a variety of input and output options to cover any use case.
Input
- Chat history: Connect chat history to let previous messages give context to future answers.
- LLM (optional): You can connect an LLM component to change the AI model. ChatGPT-4o is used by default.
- Tools: Give the agent Tools it can work with. Various components can serve as tools, ranging from knowledge retrievers to autonomous tasks.
- Input: The agent needs to be prompted by a human query.
Output
- Message: Agent’s answer as plain text. The message can be sent to chat or other components for further processing.
- Agent: Used to connect the Agent to other components that require an agent, such as tasks.
The difference between AI Agents and Generators
The two Flows pictured above look quite different but have the same function – they allow you to chat with your Knowledge Sources. One uses the Prompt and Generator components to achieve this, while the other one uses an AI Agent.
So, what’s the difference between the Prompt + Generator combo and the AI Agent? The level of control. This, in turn, will affect your choice of when to use which.
By creating a detailed Prompt, you’re fully in charge of the final product. The output is as reliable as your instructions, but it might be rigid and not appropriately respond to changes. When you use an autonomous Agent, you entrust the software to find the right answers. They’re much more flexible but may make mistakes you won’t be able to control.
