How to Create Your First AI Chatbot with Qknows
Building an AI chatbot can seem like a daunting task, especially for those without a technical background. However, with Qknows — an AI-powered natural language processing framework developed by QuickHelp Nigeria — creating a chatbot is an accessible and streamlined process. This guide provides a step-by-step approach to creating your first chatbot using Qknows.
Step 1: Sign Up on the Qknows Platform
To begin, navigate to the QuickHelp TalkingWebsite dashboard, where the Qknows framework is hosted. You can create an account by visiting the sign-up page at QuickHelp. Once your account is created, you will be granted access to the chatbot development interface.
During the account creation process, you’ll be required to define the primary function of your chatbot. The system will prompt you to answer the question, “What does your chatbot do?” This description serves as the pre-prompt that guides the chatbot’s interactions. For example, if you are creating a customer service bot for an e-commerce platform, you might specify that the chatbot handles customer inquiries, product recommendations, and order tracking.
Step 2: Write Knowets
Knowets are the building blocks of the Qknows framework. Each Knowet consists of a user request (intent) and a corresponding response. For instance, a simple Knowet could be:
How are you@I am fine, thank you!%
This format means that when the user inputs “How are you?” the chatbot will respond with “I am fine, thank you!” Knowets can also handle more complex interactions, including multiple responses, varying responses, and even sentiment-based responses.
Step 3: Integrate Context and Flows
To make your chatbot more dynamic, you can integrate context and flows into your Knowets. Context allows the chatbot to remember key details from previous interactions, while flows link multiple Knowets together to create a seamless conversation. For example, a flow might look like this:
How are you@I am fine#flow::What about you?::%
This structure ensures that the conversation continues naturally, with the chatbot asking a follow-up question based on the initial user input.
Step 4: Add Multi-Modal Responses
Qknows supports various response types beyond text, such as images, videos, buttons, and YouTube videos. To add these elements to your chatbot, simply use the appropriate templates within your Knowets. For instance, if you want the chatbot to display an image, you can write:
Show me a picture@Here is an image#image::example_image::%
This will prompt the chatbot to display the specified image when the user requests it.
Step 5: Test and Refine Your Chatbot
Once you have created your Knowets and set up your chatbot’s responses, it’s time to test it. The Qknows dashboard provides a testing environment where you can simulate user interactions and refine the chatbot’s responses based on real-time feedback. You can adjust the chatbot’s sensitivity, add new Knowets, and improve its performance by making tweaks to the script.
Step 6: Deploy Your Chatbot
After testing, you are ready to deploy your chatbot. Qknows integrates with platforms like WordPress, making it easy to add your chatbot to a website or digital interface. You can also explore advanced integrations with other NLP systems like DialogFlow or GPT to enhance the chatbot’s capabilities further.
By following these steps, you can create and deploy a functional AI chatbot using the Qknows framework, bringing automated conversational agents to your business or personal projects.
The technical foundation of Qknows is built on a natural language processing (NLP) system designed to simplify chatbot creation and interaction. At its core, Qknows utilizes “Knowets,” which are structured data entities that define user intents and corresponding responses. This framework allows for the creation of dynamic, context-aware chatbots without requiring extensive technical expertise.
Qknows also integrates key features such as sentiment analysis, context management, entity recognition, and multi-modal responses (text, images, videos), making it adaptable for various use cases. The system is designed to be transparent and interpretable, offering integration capabilities with larger AI platforms like Google DialogFlow, OpenAI GPT, and Hugging Face, while retaining a focus on explainability and user control. This technical structure makes Qknows a lightweight yet flexible tool for creating AI-powered conversational agents, particularly suited to the African technological landscape.
