README.md

metadata

title: Northwestern CS Kiosk
emoji: 🎓
colorFrom: purple
colorTo: blue
sdk: docker
app_port: 7860
pinned: false

Northwestern CS Kiosk (Vanilla LM)

Chat kiosk for Northwestern CS department questions, powered by a local decoder-only tool-calling LM (no cloud APIs).

• Planner: local LM picks a tool + JSON arguments
• Executor: CSV archive lookups (faculty, office hours, locations, etc.)
• Responder: local LM writes a short answer; rule-based template fallback when LM prose is degraded

What's bundled

Path	Purpose
models/best.pt	Trained checkpoint (~158 MB, Git LFS)
models/tokenizer/	Tokenizer from the same training run
MSAI_Text_Generation/src/	Minimal inference runtime only (16 files — not full training repo)
Archive/	Department CSV data
backend/ + frontend/	FastAPI API + React UI

Local Docker test

docker build -t kiosk-vanilla .
docker run --rm -p 7860:7860 kiosk-vanilla

Open http://localhost:7860

Hugging Face Space

This repo is the Docker Space at monish563/kiosk_vanilla.

After pushing, HF builds the image and serves on port 7860. First query loads the model (may take ~30s).

Push updates

Develop in this repo (kiosk_vanilla/). After retraining or code changes:

cd kiosk_vanilla
./scripts/prepare_hf_deploy.sh   # refresh best.pt + tokenizer + MSAI runtime
git add -A
git commit -m "Update kiosk"
git push "https://monish563:$(hf auth token)@huggingface.co/spaces/monish563/kiosk_vanilla" main

Environment (set in Dockerfile)

Variable	Value in container
MSAI_ROOT	/app/MSAI_Text_Generation
VANILLA_CHECKPOINT	/app/models/best.pt
VANILLA_TOKENIZER	/app/models/tokenizer
VANILLA_DEVICE	auto (CUDA on GPU Spaces, else CPU)