Topics & Policy Predicates

from merit.predicates import has_topics

async def merit_covers_topics():
    response = """
    For your Paris trip, consider staying in the Marais district.
    The metro is the best way to get around. Must-see attractions
    include the Eiffel Tower, Louvre, and Notre-Dame.
    """
    
    # Check response covers required topics
    assert await has_topics(
        response,
        "accommodation, transportation, attractions"
    )

async def merit_article_coverage():
    article = generate_article("Python tutorial for beginners")
    
    # Must cover essential topics
    assert await has_topics(
        article,
        "installation, syntax basics, variables, functions, loops"
    )

async def merit_support_response():
    question = "I can't log in and my credit card was charged twice"
    response = support_bot(question)
    
    # Must address both issues
    assert await has_topics(
        response,
        "login issues, billing problems"
    )

from merit.predicates import follows_policy

async def merit_policy_compliance():
    response = chatbot("Tell me about your company")
    
    # Check response follows policies
    assert await follows_policy(
        response,
        "Must be professional, avoid making promises, include disclaimer"
    )

async def merit_brand_compliance():
    response = marketing_bot("Write a product description")
    
    # Check brand guidelines
    assert await follows_policy(
        response,
        """
        - Use friendly, conversational tone
        - Avoid technical jargon
        - Include a call-to-action
        - Maximum 3 sentences
        """
    )
    
    # Can combine with regular assertions
    assert len(response.split(".")) <= 3

async def merit_safety_check():
    response = chatbot("How do I treat a serious injury?")
    
    # Must follow medical disclaimer policy
    assert await follows_policy(
        response,
        "Must advise seeking professional medical help for serious conditions"
    )

async def merit_gdpr_compliance():
    response = generate_privacy_statement()
    
    # Check GDPR requirements
    assert await follows_policy(
        response,
        """
        Must include:
        - Right to access personal data
        - Right to deletion
        - Data retention period
        - Contact information for data controller
        """
    )

async def merit_comprehensive_requirements():
    response = generate_report("Q4 Financial Results")
    
    # Check required topics are covered
    assert await has_topics(
        response,
        "revenue, expenses, profit margin, future outlook"
    )
    
    # Check compliance policies
    assert await follows_policy(
        response,
        """
        - Use formal business language
        - Include specific numbers and percentages
        - Avoid speculative statements
        - Cite data sources
        """
    )

from merit.predicates import has_topics, follows_policy

async def merit_automated_email():
    context = {
        "customer": "Jane Smith",
        "issue": "damaged product received",
        "order_id": "12345"
    }
    
    email = generate_support_email(context)
    
    # Must address all key topics
    assert await has_topics(
        email,
        "apology, replacement offer, shipping details, timeline"
    )
    
    # Must follow company policy
    assert await follows_policy(
        email,
        """
        - Start with personalized greeting
        - Express empathy
        - Offer clear resolution
        - Professional and courteous tone
        - Include order reference number
        """
    )
    
    # Regular assertions
    assert context["customer"] in email
    assert context["order_id"] in email
    assert len(email) > 100

# ✅ Clear, specific, actionable
await follows_policy(
    text,
    "Must use second-person perspective (you, your) and include at least one question"
)

# ✅ Structured list
await follows_policy(
    text,
    """
    Requirements:
    - Start with a hook or question
    - Use short paragraphs (max 3 sentences)
    - End with call-to-action
    """
)

# ❌ Too vague
await follows_policy(text, "Be good")

# ❌ Too subjective
await follows_policy(text, "Sound professional")

# Better:
await follows_policy(
    text,
    "Use formal language, avoid contractions, address reader as 'you'"
)