10-B | Devpost

Inspiration

Since Chat GPT v3 was limited to text input only, we took matters into our own hands.

What it does

With this approach, instead of having to endure lengthy videos or read extensive texts, we can now obtain concise summaries, crucial insights, essential keywords, and even request further information in a fraction of the time.

How we built it

We built it using python as well as flask with html, css and javascript

Challenges we ran into

We constructed this system using Python, along with Flask for the backend, and incorporated HTML, CSS, and JavaScript for the frontend.

Accomplishments that we're proud of

We take pride in our ability to swiftly employ AI to address the challenge presented by our competitor, demonstrating our agility and innovation.

What we learned

We gained valuable experience in integrating AI into our daily coding routine by seamlessly incorporating Softtek's LLMSDK library into our Python code.

What's next for Transcriptify

There are numerous areas for improvement and expansion. Firstly, we can optimize the program to achieve faster and more efficient runtime. Additionally, we could implement a user account system, enabling users to log in and save their previous interactions. Expanding the program's capabilities to accept a wide range of file types, including images, and allowing users to choose different AI sources, such as OpenAI, is another avenue for enhancement. Furthermore, we can explore options for regenerating responses and address various other opportunities for improvement.