Choose a specific use-case in finance or healthcare that would benefit from a chatbot. For example:
Finance: a chatbot that can help users track their expenses, set budgets, and get personalized financial advice.
Healthcare: a chatbot that can provide users with information about common health conditions, help them find nearby clinics or hospitals, and answer basic medical questions.
Research existing chatbots in your chosen sector to get an idea of what features and functionality are already available. Look for gaps or areas where you think a new chatbot could add value.
Define the scope and requirements for your chatbot. This should include:
- The specific use-case and target audience.
- The features and functionality you want to include (e.g. natural language processing, personalized recommendations, integration with external APIs).
- Any technical or design constraints (e.g. programming language, platform, user interface).
Choose a GPT framework to use for your chatbot. Some popular options include:
- Hugging Face Transformers
- OpenAI GPT-3
- Google Cloud AI Platform
Develop a prototype of your chatbot using the chosen GPT framework. This will involve:
- Training the GPT model on relevant data (e.g. financial or medical terminology, user queries).
- Building a user interface for the chatbot (e.g. web app, mobile app, messaging platform).
- Testing and refining the chatbot based on user feedback.
- Document your development process and create a user manual or tutorial to help others use and maintain the chatbot.
Present your chatbot and documentation to your supervisor or mentor, and be prepared to answer questions and demonstrate the chatbot's functionality.
Reflect on your development process and identify areas where you could improve or expand the chatbot in the future. This could include adding new features, integrating with other systems, or using more advanced AI techniques.