This project captures my progression through an independent study course in the Spring Semester of 2023. Supervised by Dr. John Harney, the course served as an initiation into the Raspberry Pi, Python programming, and Linux, as well as the integration of APIs like OpenAI and Google Translate into the project. The aim of the course was to build a historical bot, capable of responding to visual, mechanical, and aural cues.
The bot is developed using Python and communicates with users in a conversational manner, using OpenAI's GPT-3 model to generate intelligent responses. It is capable of understanding multiple languages, thanks to the Google Translate API and can even voice the generated responses using Google's Text-to-Speech service. It also recognizes speech using Python's speech recognition library, and all of these features are neatly integrated into a graphical interface developed in Pygame
- Basic knowledge of programming and computer science
- Familiarity with Python programming language
By the end of the course, students will be able to:
- Set up and configure the Raspberry Pi environment.
- Understand the basics of Natural Language Processing (NLP) and its application in chatbots.
- Implement the OpenAI API to generate intelligent responses.
- Use Google Translate API for multi-language support in the chatbot.
- Leverage Google Text-to-Speech service to enable the chatbot to verbally communicate responses.
- Integrate visual, mechanical, and aural responses into chatbots.
- Build a historical chatbot that can respond to user inputs in multiple languages.
- Utilize advanced features of APIs such as OpenAI, Google Translate, and Google Text-to-Speech.
- Recognize and process speech using Python's Speech Recognition library.
- Develop and manage a graphical interface for the bot using Pygame.
- Use the Translatepy package for efficient and accurate text translation