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project/
├── promptfooconfig.yaml    # Main configuration
├── prompts/
│   ├── system.md           # System prompt
│   └── chat.json           # Chat format prompt
├── tests/
│   └── cases.yaml          # Test cases
└── scripts/
    └── metrics.py          # Custom Python assertions

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You are a helpful assistant.

Task: {{task}}
Context: {{context}}

[
  {"role": "system", "content": "{{system_prompt}}"},
  {"role": "user", "content": "{{user_input}}"}
]

[
  {"role": "system", "content": "{{system_prompt}}"},
  {"role": "user", "content": "Example input: {{example_input}}"},
  {"role": "assistant", "content": "{{example_output}}"},
  {"role": "user", "content": "Now process: {{actual_input}}"}
]

- description: "Test case 1"
  vars:
    system_prompt: file://prompts/system.md
    user_input: "Hello world"
    # Load content from files
    context: file://data/context.txt
  assert:
    - type: contains
      value: "expected text"
    - type: python
      value: file://scripts/metrics.py:custom_check
      threshold: 0.8

def get_assert(output: str, context: dict) -> dict:
    """Default assertion function."""
    vars_dict = context.get('vars', {})

    # Access test variables
    expected = vars_dict.get('expected', '')

    # Return result
    return {
        "pass": expected in output,
        "score": 0.8,
        "reason": "Contains expected content",
        "named_scores": {"relevance": 0.9}
    }

def custom_check(output: str, context: dict) -> dict:
    """Custom named assertion."""
    word_count = len(output.split())
    passed = 100 <= word_count <= 500

    return {
        "pass": passed,
        "score": min(1.0, word_count / 300),
        "reason": f"Word count: {word_count}"
    }

assert:
  - type: llm-rubric
    value: |
      Evaluate the response based on:
      1. Accuracy of information
      2. Clarity of explanation
      3. Completeness

      Score 0.0-1.0 where 0.7+ is passing.
    threshold: 0.7
    provider: openai:gpt-4.1  # Optional: override grader model

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export PROMPTFOO_PYTHON=python3

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**Use cases:**
- Preview prompt rendering before expensive API calls
- Verify Few-shot examples are loaded correctly
- Debug variable substitution issues
- Validate prompt structure

```bash

**Cost:** Free - no API tokens consumed.

[
  {"role": "system", "content": "{{system_prompt}}"},

  // Few-shot Example 1
  {"role": "user", "content": "Task: {{example_input_1}}"},
  {"role": "assistant", "content": "{{example_output_1}}"},

  // Few-shot Example 2 (optional)
  {"role": "user", "content": "Task: {{example_input_2}}"},
  {"role": "assistant", "content": "{{example_output_2}}"},

  // Actual test
  {"role": "user", "content": "Task: {{actual_input}}"}
]

tests:
  - vars:
      system_prompt: file://prompts/system.md
      # Few-shot examples
      example_input_1: file://data/examples/input1.txt
      example_output_1: file://data/examples/output1.txt
      example_input_2: file://data/examples/input2.txt
      example_output_2: file://data/examples/output2.txt
      # Actual test
      actual_input: file://data/test1.txt

providers:
  - id: anthropic:messages:claude-sonnet-4-5-20250929
    config:
      max_tokens: 8192  # Increase for long outputs

defaultTest:
  assert:
    - type: python
      value: file://scripts/metrics.py:check_length

import re

def strip_tags(text: str) -> str:
    """Remove HTML tags for pure text."""
    return re.sub(r'<[^>]+>', '', text)

def check_length(output: str, context: dict) -> dict:
    """Check output length constraints."""
    raw_input = context['vars'].get('raw_input', '')

    input_len = len(strip_tags(raw_input))
    output_len = len(strip_tags(output))

    reduction_ratio = 1 - (output_len / input_len) if input_len > 0 else 0

    return {
        "pass": 0.7 <= reduction_ratio <= 0.9,
        "score": reduction_ratio,
        "reason": f"Reduction: {reduction_ratio:.1%} (target: 70-90%)",
        "named_scores": {
            "input_length": input_len,
            "output_length": output_len,
            "reduction_ratio": reduction_ratio
        }
    }

tiaogaoren/
├── promptfooconfig.yaml          # Production config
├── promptfooconfig-preview.yaml  # Preview config (echo provider)
├── prompts/
│   ├── tiaogaoren-prompt.json   # Chat format with few-shot
│   └── v4/system-v4.md          # System prompt
├── tests/cases.yaml              # 3 test samples
├── scripts/metrics.py            # Custom metrics (reduction ratio, etc.)
├── data/                         # 5 samples (2 few-shot, 3 eval)
└── results/