Inspiration
Marina Mogilko suggested helping her with inbound messages that she doesn't have bandwidth to handle atm
What it does
We've built a simple AI classification tool to sort through DMs and comments to identify problems and identify prospective leads. Then we engineered prompts for each classification
How we built it
We used Facebook and YouTube APIs to access comments and DMs, huggingface models to classify user messages and ChatGPT 3.5 to generate user responses.
Challenges we ran into
Facebook APIs and testing environment doesn't work. Classification didn't yield good results without models being fine-tuned
Accomplishments that we're proud of
Made the user message classifier work with a training dataset
What we learned
Facebook api sacks
What's next for Waterbear
Test it in real life, make it a fully-functioning product
Built With
- ipywidgets
- next.js
- supabase
- transformers
Log in or sign up for Devpost to join the conversation.