Inspiration
The inspiration behind KoiosGPT stems from the need to simplify the process of comprehending research articles and personal documents. Often, individuals struggle with extracting the main points and key insights from lengthy texts. KoiosGPT aims to bridge this gap by utilizing AI and LLMs to provide users with concise summaries and valuable information.
What it does
KoiosGPT allows users to upload research articles and PDF documents as well as use a built-in search feature to find articles, which are then processed using advanced AI algorithms and LLMs.
How we built it
KoiosGPT is built using a combination of frontend and backend technologies. The frontend is developed using modern web technologies such as Next JS and React, while the backend utilizes Next JS and Cloud SDK. The AI part uses a variety of GPT APIs.
Challenges we ran into
- I had challenges incorporating the cloud server as there were many bugs with it
- I also had a challenging time making the PDF viewer
Accomplishments that we're proud of
- Incorporation of LLMs and GPT with understanding complex information that can help anyone, including researchers, students, and teachers
- User-Friendly Interface: We created a sleek and intuitive user interface that prioritizes usability and enhances the overall user experience.
- Cloud Integration: The seamless integration of the cloud SDK enables users to store and retrieve their files securely, enhancing the accessibility and convenience of the application.
What we learned
- I learned how to develop my own PDF viewer and I learned how to save and retrieve data from a cloud server.
What's next for Koios GPT
- More research articles providers other than Arvix
- Conversational history
- Multi-language support
- More information and analysis on articles
- Making page responsive
Built With
- deta
- nextjs
- openai

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