bean-lens 0.1.0

Extract structured coffee bean info from package or card images using Vision LLM

bean-lens

Extract structured coffee bean info from package or card images using Vision LLM.

Installation

pip install bean-lens

Or with uv:

uv add bean-lens

Setup

Get a Gemini API key from Google AI Studio and set it as an environment variable:

export GEMINI_API_KEY=your-api-key

Usage

Python

from bean_lens import extract

result = extract("coffee_package.jpg")

print(result.roastery)        # "Fritz Coffee"
print(result.origin.country)  # "Ethiopia"
print(result.flavor_notes)    # ["Citrus", "Jasmine", "Honey"]

CLI

bean-lens image.jpg

Output:

  bean-lens

  Roastery:      Fritz Coffee
  Name:          Ethiopia Yirgacheffe
  Origin:        Ethiopia / Yirgacheffe / Konga
  Variety:       Heirloom
  Process:       Washed
  Roast Level:   Light
  Flavor Notes:  Citrus, Jasmine, Honey
  Roast Date:    2024.01.15
  Altitude:      1,800-2,000m

JSON output:

bean-lens image.jpg --json

Extracted Fields

Field	Description
roastery	Roastery or brand name
name	Coffee bean name
origin	Origin info (country, region, farm)
variety	Coffee varieties (e.g., Geisha, Typica)
process	Processing method (e.g., Washed, Natural)
roast_level	Roast level (e.g., Light, Medium, Dark)
flavor_notes	Flavor notes list
roast_date	Roast date
altitude	Growing altitude

License

MIT