Athena was designed to be a hacky tool crrated to use LLMs (specifically, OpenAI's gpt-3.5-turbo
model) in a contextual educational setting. This demo shows how you could use large textual blocks for history or chemistry, and generate a summary, ask questions, get quizzed and get contextually rendered UI (you see nice timeline UIs for history, depending on what text you're analyzing) and you can render molecules for a chemistry chapter/paper.
-
Start the server:
cd server && docker-compose up
- This exposes the Flask endpoint on port 5000.
- To run the server in a detached mode, add the
-d
flag to thedocker-compose
command.
-
Start the client
cd client && npm install && npm start
- This starts up the client on port 3000
-
Navigate to the browser and go to
localhost:3000
.http://localhost:3000/chemistry
takes you to the chemistry viewerhttp://localhost:3000/history
takes you to the history viewer