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2.8 KiB
2.8 KiB
eval-python-assert (Python Assertions)
Example configurations for testing LLM outputs using Python assertions with promptfoo.
You can run this example with:
npx promptfoo@latest init --example eval-python-assert
cd eval-python-assert
Purpose
This example demonstrates how to use Python assertions for custom output validation with:
- External Python files with assertion functions
- Inline Python code directly in configuration files
- Configuration-based assertions with custom parameters
- Different assertion return formats (boolean, score, detailed results)
Prerequisites
- Python 3.7+ installed and available in your PATH
- OpenAI API key (or other LLM provider)
Environment Variables
OPENAI_API_KEY- Your OpenAI API key (required)
Configurations
This example includes two different approaches:
External Python Files (promptfooconfig-external.yaml)
Uses external Python files for complex assertion logic:
promptfooconfig-external.yaml- Configuration with external Python assertionsassert.py- Basic assertion function with detailed scoringassert_with_config.py- Configuration-based assertion function
Inline Python Code (promptfooconfig-inline.yaml)
Demonstrates inline Python assertions directly in the configuration:
promptfooconfig-inline.yaml- Configuration with inline Python code- Shows simple boolean checks and complex scoring logic
Running the Examples
-
External Python assertions example:
promptfoo eval -c promptfooconfig-external.yaml -
Inline Python assertions example:
promptfoo eval -c promptfooconfig-inline.yaml -
View results:
promptfoo view
Python Assertion Patterns
Basic Boolean Return
def get_assert(output, context):
return "expected_word" in output.lower()
Score-Based Return
def get_assert(output, context):
if "perfect" in output.lower():
return 1.0
elif "good" in output.lower():
return 0.5
else:
return 0.0
Detailed Result Object
def get_assert(output, context):
return {
"pass": True,
"score": 0.8,
"reason": "Contains expected content",
"namedScores": {"quality": 0.9, "relevance": 0.7}
}
Expected Results
- External example: Shows advanced assertion patterns with detailed scoring and configuration support
- Inline example: Demonstrates quick assertions and simple validation logic