promptfoo/examples/image-classification

Image Classification Example with Promptfoo

This example demonstrates how to use Promptfoo for image classification tasks using the Fashion MNIST dataset. The example uses GPT-4o and GPT-4o-mini with a structured json schema to analyze images, including classification, color analysis, and additional attributes.

Getting Started

1. Set up your OpenAI API key:

   export OPENAI_API_KEY='your-api-key'
   

2. Run the evaluation:

   npx promptfoo@latest eval
   

3. View the results:

   npx promptfoo@latest view
   

4. Optionally, re-generate or update the dataset:

   python dataset_gen.py
   

   Note: You may need to install dependencies with:

   pip install -r requirements.txt
   

   This script creates a CSV file with 100 random images from the Fashion MNIST dataset and their labels. A CSV with 10 sample images is included so you can skip this step if preferred.

5. Experiment with the configuration:

   • Modify the JSON schema in promptfooconfig.yaml to add or adjust required fields
   • Try different models such as llama3.2 or Claude 3.5 by changing the provider in the config
   • Adjust the system prompt to improve classification accuracy
   • Add additional assertions to validate model outputs