Basic Examples¶

from agent_test import agent_test

def my_qa_agent(question):
    """Simple Q&A agent (replace with your implementation)."""
    responses = {
        "What is the capital of France?": "The capital of France is Paris.",
        "What is 2+2?": "2+2 equals 4.",
        "Who wrote Romeo and Juliet?": "William Shakespeare wrote Romeo and Juliet."
    }
    return responses.get(question, "I don't know the answer to that question.")

@agent_test(criteria=['similarity'])
def test_basic_qa():
    """Test basic question answering capability."""
    question = "What is the capital of France?"
    answer = my_qa_agent(question)

    return {
        "input": question,
        "actual": answer,
        "expected": "Paris is the capital of France."
    }

@agent_test(criteria=['similarity'])
def test_math_qa():
    """Test mathematical question answering."""
    question = "What is 2+2?"
    answer = my_qa_agent(question)

    return {
        "input": question,
        "actual": answer,
        "expected": "The answer is 4."
    }

@agent_test(criteria=['contains'])
def test_python_libraries():
    """Test if agent mentions required Python libraries."""

    def get_data_science_libraries():
        return "For data science in Python, you should use pandas for data manipulation, numpy for numerical computing, matplotlib for visualization, and scikit-learn for machine learning."

    response = get_data_science_libraries()

    return {
        "input": "What Python libraries should I use for data science?",
        "actual": response,
        "contains": ["pandas", "numpy", "matplotlib", "scikit-learn"]
    }

@agent_test(criteria=['contains'])
def test_recipe_ingredients():
    """Test if agent includes all required ingredients."""

    def get_pancake_recipe():
        return "To make pancakes, you need flour, eggs, milk, sugar, baking powder, and salt. Mix them together and cook on a griddle."

    response = get_pancake_recipe()

    return {
        "input": "How do I make pancakes?",
        "actual": response,
        "contains": ["flour", "eggs", "milk", "sugar", "baking powder", "salt"]
    }

@agent_test(criteria=['regex'])
def test_contact_extraction():
    """Test contact information extraction."""

    def extract_contact_info():
        return """
        Name: John Doe
        Email: john.doe@email.com
        Phone: 555-123-4567
        Date: 2024-06-26
        """

    extracted_info = extract_contact_info()

    return {
        "input": "Extract contact information from the document",
        "actual": extracted_info,
        "patterns": [
            r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b",  # Email
            r"\b\d{3}-\d{3}-\d{4}\b",                                 # Phone
            r"\b\d{4}-\d{2}-\d{2}\b"                                  # Date
        ]
    }

@agent_test(criteria=['regex'])
def test_url_generation():
    """Test if agent generates valid URLs."""

    def generate_urls():
        return "Check out these resources: https://www.python.org and http://github.com/user/repo"

    response = generate_urls()

    return {
        "input": "Generate some useful URLs",
        "actual": response,
        "patterns": [r"https?://[^\s]+"]  # URL pattern
    }

@agent_test(criteria=['similarity', 'contains', 'llm_judge'])
def test_explanation_quality():
    """Test explanation quality across multiple dimensions."""

    def explain_photosynthesis():
        return "Photosynthesis is the process by which plants convert sunlight, carbon dioxide, and water into glucose and oxygen. This process uses chlorophyll in the leaves and is essential for plant survival and oxygen production."

    explanation = explain_photosynthesis()

    return {
        "input": "Explain photosynthesis",
        "actual": explanation,
        "expected": "Photosynthesis converts sunlight into energy for plants using chlorophyll, carbon dioxide, and water.",
        "contains": ["sunlight", "chlorophyll", "carbon dioxide", "water", "oxygen"],
        "evaluation_criteria": ["accuracy", "clarity", "completeness"]
    }

@agent_test(criteria=['llm_judge', 'contains'])
def test_customer_support_greeting():
    """Test customer support greeting quality."""

    def customer_support_bot(message):
        if "hello" in message.lower() or "hi" in message.lower():
            return "Hello! Welcome to our customer support. I'm here to help you with any questions or issues you may have. How can I assist you today?"
        return "I'm here to help! What can I do for you?"

    response = customer_support_bot("Hello, I need help")

    return {
        "input": "Hello, I need help",
        "actual": response,
        "contains": ["hello", "help", "assist"],
        "evaluation_criteria": ["politeness", "helpfulness", "professionalism"]
    }