Authorization notice. JEV Sees is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.
Credentials. Use an environment variable for TYPESAFE_API_KEY rather than hard-coding the key in the script.
Who it is forA warehouse operations lead who reviews shelf or dock photos and needs a consistent obstruction grade for each package.
The problemChecking each package in many photos against the same standard by eye produces uneven results.
The outcomeA structured export of one score per package, with the rubric text the application supplied.
What you need first
- Python 3.10 or newer
- A JEV API key from console.typesafe.ai/keys
- Internet access for the first run, unless the Florence-2 and CLIP weights are already available locally
- Git and a terminal
Steps
- Clone the project with
git clone https://github.com/CharlesFeng0314/JEV_sees.git. - Enter the folder with
cd JEV_sees. - Install it with
python -m pip install -e .. - Set your key on macOS or Linux with
export TYPESAFE_API_KEY="your-key", or in PowerShell with$env:TYPESAFE_API_KEY = "your-key". - Write a short Python script that imports Sees from jev_sees and calls Sees().for_each("package").score(...) on your photo with your rubric, then sets json="output.json" to export the results. (inferred, check the README)
Prompt for your agent
In the JEV_sees repo at <repo path>, write and run a Python script that calls Sees().for_each("package").score(...) on <photo path> with the rubric 0: clear, 1: partly obstructed, 2: heavily obstructed. Expect one score per package in output.json; verify that every score is one of the three rubric levels.
Caveat. The score method is part of an experimental v0.1.0 API that the README says may continue to change, so pin the version you test.
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