"What does the Followup Questions component do?"

"It generates relevant follow-up questions based on user input, context, and chat history, helping users explore topics more thoroughly."

"Can I control how many questions are generated?"

"Yes, you can set the number of follow-up questions generated to fit your needs."

"Does it use previous chat history?"

"Yes, incorporating chat history helps the component create more precise and context-aware follow-up questions."

"Which AI models can be used with this component?"

"You can connect any supported LLM (Large Language Model) in FlowHunt for question generation."

"In what scenarios should I use the Followup Questions component?"

"Use it in flows where you want to guide users to deeper understanding or further inquiry, such as research assistants, customer support bots, or educational chatbots."

Followup Questions

Automatically generate targeted follow-up questions using AI and chat context to guide deeper, more meaningful conversations.

Component description

How the Followup Questions component works

Followup Questions Component

The Followup Questions component is designed to help users generate insightful follow-up questions based on a provided context, answer, and conversation history. This functionality is especially valuable in AI-driven workflows where deepening understanding of a topic or clarifying ambiguities is important—such as in chatbots, tutoring systems, or knowledge exploration tools.

What Does the Component Do?

This component takes an input text (typically a user’s question or statement), and, using a language model, generates a list of follow-up questions that the user should ask to gain a deeper or clearer understanding of the topic. It can leverage additional information like the current chat history, context, and previous answers to generate more precise and relevant questions.

Inputs

The component supports several input fields, some optional and some required. Here’s an overview:

Input Name	Type	Required	Description
Input Text	String (Message)	Yes	The main text input (user query or statement) to base follow-up questions on.
Chat History	InMemoryChatMessageHistory	No	The conversation history, which helps the model generate better-targeted follow-up questions.
LLM	BaseChatModel	No	The language model to use for question generation.
Answer	String (Message)	No	The answer to the input text, which can help improve the relevance of the follow-up questions.
Context	String (Message)	No	Additional context to generate more focused questions.
Number of questions	Integer	Yes	Specifies how many follow-up questions to generate. Default is 5.
System Message	String	No	An optional system-level message to modify or steer the prompt sent to the language model.

Outputs

Message:
The output of this component is a message (or collection of messages) containing the generated follow-up questions.

Why Is This Useful?

Enhance User Engagement: By suggesting relevant follow-up questions, this component helps users dig deeper into topics and discover information they might not have considered.
Improve Conversational Flows: In chatbots or virtual assistants, it prompts users to clarify or expand on their queries, making interactions more dynamic and informative.
Support Learning and Research: In educational or research settings, it can guide learners or researchers to ask better questions, leading to improved comprehension and critical thinking.
Personalization: By considering chat history and context, the questions are tailored and contextualized, increasing their usefulness and precision.

Example Use Cases

Customer Support Bots: Automatically suggest helpful follow-up questions to customers based on their previous queries and responses.
Educational Tutors: Help students by prompting them with additional questions to ensure they understand the material.
Knowledge Management: Guide users in knowledge bases or research environments to ask productive questions.

Summary Table

Feature	Benefit
Context-aware	Generates more relevant questions
Model-agnostic	Can work with different LLMs
Customizable output	Control over number and style of questions
History integration	Takes prior conversation into account

By integrating the Followup Questions component, you can make your AI-driven workflows more interactive, informative, and user-friendly.

Frequently asked questions

What does the Followup Questions component do?: It generates relevant follow-up questions based on user input, context, and chat history, helping users explore topics more thoroughly.
Can I control how many questions are generated?: Yes, you can set the number of follow-up questions generated to fit your needs.
Does it use previous chat history?: Yes, incorporating chat history helps the component create more precise and context-aware follow-up questions.
Which AI models can be used with this component?: You can connect any supported LLM (Large Language Model) in FlowHunt for question generation.
In what scenarios should I use the Followup Questions component?: Use it in flows where you want to guide users to deeper understanding or further inquiry, such as research assistants, customer support bots, or educational chatbots.

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