Create a chatbot Intent Classifier based on fine-tuned GPT3

Create a chatbot Intent Classifier based on fine-tuned GPT3

Intent classification is a pivotal process in natural language processing (NLP) where an AI system identifies the purpose or intention behind a user's input. This task involves analyzing a user's message and categorizing it into predefined intents, such as booking a flight, checking the weather, or requesting customer support. By understanding what the user wants to achieve, the chatbot can provide accurate and relevant responses.

Project Presentation

GitHub repo

The goal of this project was to implement a zero- or few-shot intent classifier that can be used to provide inferencing services via an HTTP interface. For this, I used the ATIS Dataset to fine-tuned the latest version of OpenAI GPT3, in order to improve intent predictions.

Project Research

See the project_research.ipynb notebook on Github for my review of the ATIS dataset, as well as in-depth research on testing and fine-tuning GPT3 to perform intent classification.

The required modules to run the notebook code are listed at the beginning. Create a virtual environment if necessary and run the Modules Installation cell.

This notebook is available on Kaggle too.

Run the Project

See the Readme on Github to clone the project, install the required modules and run the Flask server. A Docker file to run the project in a container is available too.

Feel free to play around with the instructions in the prompt and intents files to tweak the results to better match your use case.

You will need to fine-tune your own GPT3 model on the ATIS dataset, to get better results, as I cannot share my version. See the project research notebook for that.


While intent classification has significantly advanced, challenges remain. Ambiguity in user messages, evolving language use, and domain-specific jargon can complicate accurate intent detection.

The future of intent classification in AI chatbots lies in continuous learning and adaptation. As models become more sophisticated, they will better understand and predict user intentions, making chatbots even more integral to digital communication.

In conclusion, intent classification is a cornerstone of modern AI chatbots, enabling them to understand and respond to user needs effectively. As technology advances, its role will only become more significant, driving innovation and enhancing the way we interact with machines.