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Pi Scorer

pi is an alternative approach to model grading that uses a dedicated scoring model instead of the "LLM as a judge" technique. It can evaluate input and output pairs against criteria.

note

Important: Unlike llm-rubric which works with your existing providers, Pi requires a separate external API key from Pi Labs.

Alternative Approach​

Pi offers a different approach to evaluation with some distinct characteristics:

  • Uses a dedicated scoring model rather than prompting an LLM to act as a judge
  • Focuses on highly accurate numeric scoring without providing detailed reasoning
  • Aims for consistency in scoring the same inputs
  • Requires a separate API key and integration

Each approach has different strengths, and you may want to experiment with both to determine which best suits your specific evaluation needs.

Prerequisites​

To use Pi, you must first:

  1. Create a Pi API key from Pi Labs
  2. Set the WITHPI_API_KEY environment variable
export WITHPI_API_KEY=your_api_key_here

or set

env:
  WITHPI_API_KEY: your_api_key_here

in your promptfoo config

How to use it​

To use the pi assertion type, add it to your test configuration:

assert:
  - type: pi
    # Specify the criteria for grading the LLM output
    value: Is the response not apologetic and provides a clear, concise answer?

This assertion will use the Pi scorer to grade the output based on the specified criteria.

How it works​

Under the hood, the pi assertion uses the withpi SDK to evaluate the output based on the criteria you provide.

Compared to LLM as a judge:

  • The inputs of the eval are the same: llm_input and llm_output
  • Pi does not need a system prompt, and is pretrained to score
  • Pi always generates the same score, when given the same input
  • Pi requires a separate API key (see Prerequisites section)

Threshold Support​

The pi assertion type supports an optional threshold property that sets a minimum score requirement. When specified, the output must achieve a score greater than or equal to the threshold to pass.

assert:
  - type: pi
    value: Is not apologetic and provides a clear, concise answer
    threshold: 0.8 # Requires a score of 0.8 or higher to pass
info

The default threshold is 0.5 if not specified.

Metrics Brainstorming​

You can use the Pi Labs Copilot to interactively brainstorm representative metrics for your application. It helps you:

  1. Generate effective evaluation criteria
  2. Test metrics on example outputs before integration
  3. Find the optimal threshold values for your use case

Example Configuration​

prompts:
  - 'Explain {{concept}} in simple terms.'
providers:
  - openai:gpt-4.1
tests:
  - vars:
      concept: quantum computing
    assert:
      - type: pi
        value: Is the explanation easy to understand without technical jargon?
        threshold: 0.7
      - type: pi
        value: Does the response correctly explain the fundamental principles?
        threshold: 0.8

See Also​