How to build an AI Conditional Chatbot

Updated: June 2, 2025

VectorShift


Summary

This video provides a comprehensive guide on building a conditional chatbot using the Vector Shift no code builder. Viewers will learn about setting up standard pipelines for workflow automation, routing questions to specific data sources, and handling different types of questions using a question classifier. The tutorial also covers diverting general questions to a knowledge base for answers, merging paths to create a unified output, and deploying the chatbot with customized responses.


Introduction to Vector Shift

Introduction to building a conditional chatbot using the Vector Shift no code builder and overview of standard pipelines.

Setting Up Standard Pipeline

Explanation of setting up a standard pipeline with inputs and outputs for workflow automation.

Building Logic for Different Scenarios

Creating logic for routing questions to specific data sources like CSV query reader or knowledge base.

Handling Different Types of Questions

How to handle different types of questions using a question classifier and routing logic.

Diverting Questions to Knowledge Base

Setting up a path to divert questions classified as general to a knowledge base for answers.

Merging Paths for Chatbot Output

Explanation of merging different paths to create a single output for the chatbot.

Deploying the Chatbot

Instructions on how to deploy the chatbot and customize responses.


FAQ

Q: What is the Vector Shift no code builder used for?

A: The Vector Shift no code builder is used for building conditional chatbots and setting up standard pipelines for workflow automation.

Q: How can routing logic be used to direct questions to specific data sources?

A: Routing logic can be used to direct questions to specific data sources like CSV query readers or knowledge bases based on predefined conditions or classification.

Q: What is a question classifier and how is it utilized in a chatbot?

A: A question classifier is a tool used to categorize questions into different types or topics, enabling the chatbot to handle different question types effectively.

Q: How can questions classified as general be directed to a knowledge base for answers?

A: Questions classified as general can be directed to a knowledge base through routing logic, ensuring appropriate answers are provided to users.

Q: What is the purpose of merging different paths in a chatbot?

A: Merging different paths in a chatbot allows for the consolidation of outputs from various sources to provide a unified response to the user.

Q: What are the steps involved in deploying a chatbot and customizing its responses?

A: The steps involved in deploying a chatbot include setting up the necessary infrastructure, integrating with communication channels, and customizing responses to align with the intended use case.

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