GPT Chatbot with API Calling | Real-Time Chatbot
Neha
January 22, 2024
GPT Chatbots with Function Calling, or API Calling, are a big step forward in chatbot technology. By adding API calls to a GPT chatbot, it can interact in real-time and more dynamically. This means the chatbot can get and show data from other places right away, making it much more useful and versatile. In this blog post, we are going to look at how to set up a GPT chatbot that can do custom API calls. This feature turns your chatbot into a better, smarter chatbot for engaging users and sharing information.
API (Application Programming Interface) integration in chatbots allows the chatbot to access and interact with external data and services. Essentially, it enables the chatbot to extend its capabilities beyond knowledgebase responses, allowing the chatbot to fetch real-time data, interact with other software, and perform dynamic actions based on user requests.
Integrating API calls into your custom GPT chatbot greatly improves its capabilities, allowing your chatbot to provide users with real-time data, making interactions more informative, relevant, and engaging. Whether it is for customer service, data retrieval, or providing personalised content, the ability to call APIs in real time opens up a world of possibilities. Let us see how we can setup.
Follow the steps below to integrate your custom API with GPT Chatbot:
Go to the chatbot dashboard. Here, you will find the Studio section that is your playground for developing and updating chatbot scenarios. In the studio, you can configure your chatbot to execute a range of activities based on user interactions.
Once in the studio, your first step is to create a new scenario. Scenarios are essentially the backbone of your chatbot’s interaction flow. They define how the chatbot should respond to different user intents. Think of them as the script your chatbot follows during its conversations with users.
Capture to feature to store the response in FLOW.response. This stored response can then be used in various parts of your chatbot’s conversation flow.Suggested Reading
These are some use cases of real-time chatbots in different industries, which improve customer engagement, assistance, and operational efficiency. Real-time chatbots find applications in a variety of industries, including:
A GPT chatbot can become much more than just a conversational agent by integrating function calls. This allows the chatbot to provide real-time data and responses, improve the user experience, and add substantial value to the services it can provide. The applications your chatbot can be used for are only limited by your creativity.
Nearly 70% of shoppers who add something to their cart leave without buying (glued). Some were never serious. But a lot of them had a question, needed a fast answer, and moved on when one did not come. That is the actual problem AI chatbots solve in DTC, when built correctly. A specific shopper, a […]
Small and medium businesses are facing a structural shift. Customers expect instant responses. Work happens across dozens of tools. Teams remain lean. Costs keep rising. Yet service quality is expected to match large enterprises. For years, businesses depended on chatbots, helpdesks, and manual workflows. These systems offered limited relief, handling basic questions and ticket routing […]
Automation defines how modern enterprises execute, respond, and grow. Customer conversations are handled by AI. Transactions move through automated workflows. Approvals route across departments without manual follow-ups. In high-performing organizations, intelligent systems are embedded directly into revenue operations, service delivery, finance, and internal support. Investment trends confirm this shift. The global conversational AI market surpassed […]
Access to clear, accurate information now sits at the center of customer experience and internal operations. People search first when setting up products, reviewing policies, or resolving issues, making structured knowledge essential for fast, consistent answers. A knowledge base organizes repeatable information such as guides, workflows, documentation, and policies into a searchable system that supports […]
TL;DR Agent mining shifts AI from answering questions to executing real work across systems through controlled, repeatable workflows with verification. By automating repetitive operations with guardrails and observability, agents reduce friction, improve consistency, and let humans focus on decisions and edge cases. For a decade, AI was mostly framed as something that answers. It explains, […]
Say “AI” and most people still think ChatGPT. A chat interface where you type a question and get an answer back. Fast, helpful, sometimes impressive. Three years after ChatGPT went viral, surveys show that’s still how most people think about AI. For many, ChatGPT isn’t just an example of AI. It is AI. The entire […]