SeeFood App

A Python implementation of the "SeeFood" app from HBO's Silicon Valley series. This app classifies images as either "Hotdog" or "Not Hotdog" using Ollama for inference.

This project was create using Cursor AI

Requirements

• Python 3.11+
• Poetry for dependency management
• Ollama runningwith llama3.2-vision model

Setup

1. Install dependencies:

poetry install

2. Set up environment variables: Create a .env file with:

OLLAMA_BASE_URL=http://localhost:11434

3. Run the application:

Start the Streamlit UI:

poetry run python run_ui.py

or

poetry run streamlit run app/main.py

Optionally, start the FastAPI server:

poetry run python run_api.py

or

poetry run uvicorn app.main:app --reload

The api isn't used by the app. The docs can be viewed at http://localhost:8000/docs.

Project Structure

• app/main.py: Main FastAPI and Streamit application
• app/models/hotdog_classifier.py: Image classification model
• app/utils/image_utils.py: Image processing utilities
• app/tests/: Test files
• images: Some sample images for testing