Prompt Chain

Generate Configurable Python Test Cases from Templates

Dynamically generate Python test cases with configurable parameters, enabling reusable test functions customized through YAML configuration.

Works with pythonopenai

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Updated 18 days ago
Version 0.121.18

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Why it matters

Enable developers to dynamically generate Python test cases with customizable parameters, allowing reusable test generation functions that can be configured differently for various testing scenarios without code changes.

Outcomes

What it gets done

01

Pass configuration objects to Python test generator functions

02

Control test case generation with parameters like language lists and row limits

03

Generate test cases from CSV files with configurable row constraints

04

Maintain backward compatibility with legacy test generator formats

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/pfoo-config-python-test-cases | bash

Steps

Steps in the chain

01
Install Python Dependencies
02
Set Environment Variables
03
Run Evaluation

Overview

Config Python Test Cases

This example demonstrates how to use Python functions to generate test cases with configurable parameters using the TestGeneratorConfig feature. Use this when you need to generate multiple variations of test cases from a single Python function by passing different configuration parameters, such as specifying different language pairs or limiting the number of test cases generated from CSV files.

What it does

This example demonstrates how to use Python functions to generate test cases with configurable parameters using the TestGeneratorConfig feature. It allows you to pass configuration objects to customize test generation, enabling you to control languages, row limits, and other parameters while maintaining backward compatibility with existing test generators.

When to use - and when NOT to

Use this when you need to generate multiple variations of test cases from a single Python function by passing different configuration parameters, such as specifying different language pairs or limiting the number of test cases generated from CSV files. Use it when you want reusable test generation functions that can be customized without code changes. Do not use this if you only need static test cases that never change, as simple YAML-defined tests would be more straightforward. Do not use this if you don't have Python installed or cannot manage Python dependencies.

Inputs and outputs

You provide Python functions that accept an optional config parameter and a promptfoo configuration YAML file that references these functions with configuration objects specifying parameters like languages or max_rows. For example:

tests:
  - path: file://test_cases.py:generate_simple_tests
    config:
      languages: [German, Italian]

The Python function receives the config dictionary:

from typing import Optional, Dict, Any

def generate_simple_tests(config: Optional[Dict[str, Any]] = None):
    languages = ["Spanish", "French"]  # defaults

    if config:
        languages = config.get("languages", languages)

    # Generate test cases using the configuration...

Integrations

This example works with pandas for CSV-based test case generation. The test generator functions are called by promptfoo during evaluation runs.

Who it's for

This is for prompt engineers and QA teams who need to generate test cases programmatically with varying parameters. The backward compatibility feature means existing promptfoo users can adopt this incrementally without breaking current workflows.

Setup

Install the example:

npx promptfoo@latest init --example config-python-test-cases
cd config-python-test-cases

Install Python dependencies:

pip install pandas

Set your API key:

export OPENAI_API_KEY=your_api_key_here

Run the evaluation:

promptfoo eval
Source README

config-python-test-cases (Python Test Cases with Configuration)

You can run this example with:

npx promptfoo@latest init --example config-python-test-cases
cd config-python-test-cases

This example demonstrates how to use Python functions to generate test cases with configurable parameters using the new TestGeneratorConfig feature.

Overview

Previously, test generators could only be called without parameters:

tests:
  - file://test_cases.py:generate_simple_tests

Now you can pass configuration objects to customize the test generation:

tests:
  - path: file://test_cases.py:generate_simple_tests
    config:
      languages: [German, Italian]

Requirements

  1. Python Dependencies:

    pip install pandas
    
  2. Environment Variables:

    export OPENAI_API_KEY=your_api_key_here
    

Usage

Run the evaluation with:

promptfoo eval

Features Demonstrated

1. Backward Compatibility

The old format still works:

- file://test_cases.py:generate_simple_tests

2. Simple Configuration

Pass configuration to customize test generation:

- path: file://test_cases.py:generate_simple_tests
  config:
    languages: [German, Italian]

3. Row Limiting

Control how many test cases are generated:

- path: file://test_cases.py:generate_from_csv
  config:
    max_rows: 2

Implementation

The Python functions accept an optional config parameter:

from typing import Optional, Dict, Any

def generate_simple_tests(config: Optional[Dict[str, Any]] = None):
    languages = ["Spanish", "French"]  # defaults

    if config:
        languages = config.get("languages", languages)

    # Generate test cases using the configuration...

This enables:

  • Backward compatibility: Existing generators work unchanged
  • Flexible configuration: Pass any parameters as JSON
  • Reusable functions: Same function, different configurations

FAQ

Common questions

Discussion

Questions & comments · 0

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