SlugSyllabus (folder-only demo)

A pure-demo web app that stores uploaded syllabus PDFs in a folder and keeps metadata in a single JSON file (index.json). Insights are generated on-demand via prompt keys (LLM stubbed) and optionally cached as text files in cache/.

Prereqs

• Python 3.10+

from project root

rm -rf .venv

create fresh venv with a modern Python

python3.11 -m venv .venv source .venv/bin/activate

upgrade tooling

python -m pip install --upgrade pip setuptools wheel

install deps explicitly (no guessing)

python -m pip install
fastapi
"uvicorn[standard]"
jinja2
python-multipart
pypdf
markdown
google-generativeai

sanity checks (ALL must succeed)

python -c "import fastapi; print('fastapi ok')" python -c "import uvicorn; print('uvicorn ok')" python -c "import google.generativeai as genai; print('gemini ok')"

set your API key

export GEMINI_API_KEY="YOUR_KEY_HERE"

RUN THE APP (IMPORTANT)

python -m uvicorn app.main:app --reload Open:

• http://127.0.0.1:8000/

How it works

• PDFs are stored in uploads/
• Metadata lives in index.json (auto-created)
• Insights tabs call /insight/{slug}/{prompt_key} which:
  • checks cache/{slug}__{prompt_key}.txt
  • if missing, calls the LLM stub and writes the cache file

Where to plug in a real LLM

Edit app/llm.py:

• Replace run_llm(prompt_key, syllabus_text) with your provider call.
• For a demo, you can skip PDF->text and just send a short extracted snippet.

Suggested demo script

1. Upload 2 PDFs
2. Open a syllabus detail page
3. Click TLDR / WORKLOAD / GRADING / PREREQS tabs
4. Refresh the page and click again to show caching is instant

Gemini setup

Set your key:

export GEMINI_API_KEY="YOUR_KEY"

Install deps:

pip install -r requirements.txt