Nittany Guesser

"Utilizing binary tree search, our tool asks smart questions to accurately determine your thoughts, saving time and ensuring poviding image results.

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Inspiration

While studying Data Structures and Algorithms, we noticed the power of certain algorithms like binary search trees and divide and conquer techniques. This sparked the idea of a different kind of guessing game where OpenAI wouldn’t just provide a text output but would visualize its guess. Thus, 'Nittany Guesser' was born.

What it does

'Nittany Guesser' employs binary search trees and divide-and-conquer methods. Through a series of questions, it determines the potential places you might be thinking of and then presents an AI-generated image based on its final guess.

How we built it

We chose Python as our programming language and integrated several packages to enhance functionality:

  • pip install tkinter
  • pip install customtkinter
  • pip install Pillow
  • pip install openai
  • pip install requests
  • pip install configparser

Our main challenge was integrating and customizing the OpenAI API. By thoroughly reviewing OpenAI's documentation, we provided specific instructions, refining our application's output.

Challenges we ran into

Adapting the OpenAI's vast capabilities to our needs was challenging. We strived to create a precise prompt and direct the API to produce specific results. We also had to ensure that while focusing on the text, our user interface remained user-friendly and effective.

Accomplishments that we're proud of

We successfully integrated the OpenAI API and got it to interact with other tools in our toolkit. It was rewarding to see different APIs working together, producing a cohesive output.

What we learned

This project taught us the importance of efficient workflows, project task delegation, team networking, and effective documentation review.

What's next for Nittany Guesser

Our next step is to consider training our model using OpenAI's API. By doing so, we aim to improve the accuracy and specificity of the guesses, offering users an even more refined experience.

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