from typing import Literal
from pydantic import BaseModel
from mellea import generative, start_session

class ReviewAnalysis(BaseModel):
    sentiment: Literal["positive", "negative", "neutral"]
    score: int    # 1-5
    summary: str  # one sentence

@generative
def analyze_review(text: str) -> ReviewAnalysis:
    """Extract sentiment, a 1-5 score, and a one-sentence summary."""
    ...

m = start_session()
result = analyze_review(m, text="Battery life is great but the screen is dim")

print(result.sentiment)  # "positive", "negative", or "neutral" — always
print(result.score)      # an int, 1-5 — always
print(result.summary)    # a str — always

import mellea
from mellea.stdlib.sampling import RejectionSamplingStrategy

def write_email_with_strategy(m: mellea.MelleaSession, name: str, notes: str) -> str:
    email_candidate = m.instruct(
        f"Write an email to {name} using the notes following: {notes}.",
        requirements=[
            "The email should have a salutation.",
            "Use a formal tone.",
        ],
        strategy=RejectionSamplingStrategy(loop_budget=3),
        return_sampling_results=True,
    )

    if email_candidate.success:
        return str(email_candidate.result)

    # If sampling fails, use the first generation
    print("Expect sub-par result.")
    return email_candidate.sample_generations[0].value

import mellea
from mellea.stdlib.requirements.safety.guardian import (
    GuardianCheck, GuardianRisk,
)

m = mellea.start_session()

response = m.instruct(
    "Write a helpful customer support response to: "
    "How do I reset my password?",
    requirements=[
        "Be concise and professional.",
        GuardianCheck(GuardianRisk.HARM),
        GuardianCheck(GuardianRisk.SOCIAL_BIAS),
    ],
)

print(response)  # validated — or retried until it passes