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# config-python-test-cases (Python Test Cases with Configuration)
You can run this example with:
```bash
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:
```yaml
tests:
- file://test_cases.py:generate_simple_tests
```
Now you can pass configuration objects to customize the test generation:
```yaml
tests:
- path: file://test_cases.py:generate_simple_tests
config:
languages: [German, Italian]
```
## Requirements
1. **Python Dependencies**:
```bash
pip install pandas
```
2. **Environment Variables**:
```bash
export OPENAI_API_KEY=your_api_key_here
```
## Usage
Run the evaluation with:
```bash
promptfoo eval
```
## Features Demonstrated
### 1. Backward Compatibility
The old format still works:
```yaml
- file://test_cases.py:generate_simple_tests
```
### 2. Simple Configuration
Pass configuration to customize test generation:
```yaml
- path: file://test_cases.py:generate_simple_tests
config:
languages: [German, Italian]
```
### 3. Row Limiting
Control how many test cases are generated:
```yaml
- path: file://test_cases.py:generate_from_csv
config:
max_rows: 2
```
## Implementation
The Python functions accept an optional `config` parameter:
```python
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
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# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
description: Python test generators with configuration
prompts:
- 'Translate the following text to {{target_language}}: {{text}}'
providers:
- openai:gpt-4.1-mini
# Demonstrate test generators with and without configuration
tests:
# 1. Basic generator with default languages (Spanish, French)
- file://test_cases.py:generate_simple_tests
# 2. Same generator with different languages (German, Italian)
- path: file://test_cases.py:generate_simple_tests
config:
languages: [German, Italian]
# 3. CSV generator with row limit
- path: file://test_cases.py:generate_from_csv
config:
max_rows: 2
@@ -0,0 +1,63 @@
from typing import Any, Dict, Optional
import pandas as pd
def generate_simple_tests(config: Optional[Dict[str, Any]] = None):
"""Generate a simple set of test cases with optional configuration."""
# Default values
languages = ["Spanish", "French"]
phrases = ["Hello", "Thank you"]
# Override with config if provided
if config:
languages = config.get("languages", languages)
phrases = config.get("phrases", phrases)
test_cases = []
for phrase in phrases:
for lang in languages:
test_case = {
"vars": {"text": phrase, "target_language": lang},
"assert": [
{"type": "regex", "value": ".+"}
], # Just check for non-empty output
"description": f"Translate '{phrase}' to {lang}",
}
test_cases.append(test_case)
return test_cases
def generate_from_csv(config: Optional[Dict[str, Any]] = None):
"""Generate test cases from CSV data with optional row limit."""
# Default test data
data = {
"source_text": ["Good morning", "Thank you", "Goodbye"],
"target_language": ["French", "Spanish", "German"],
"expected_translation": ["Bonjour", "Gracias", "Auf Wiedersehen"],
}
# Use custom data if provided in config
if config and "data" in config:
data = config["data"]
df = pd.DataFrame(data)
# Limit rows if specified in config
if config and "max_rows" in config:
df = df.head(config["max_rows"])
test_cases = []
for _, row in df.iterrows():
test_case = {
"vars": {
"text": row["source_text"],
"target_language": row["target_language"],
},
"assert": [{"type": "contains", "value": row["expected_translation"]}],
"description": f"Translate '{row['source_text']}' to {row['target_language']}",
}
test_cases.append(test_case)
return test_cases