Pythonoutput_validation.py
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from typing import Literal
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from pydantic import BaseModel, field_validator
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from openai import OpenAI
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client = OpenAI()
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class ProductReview(BaseModel):
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    rating: int
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    sentiment: Literal["positive", "negative", "neutral"]
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    summary: str
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    key_points: list[str]
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    @field_validator("rating")
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    @classmethod
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    def validate_rating(cls, v: int) -> int:
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        if not 1 <= v <= 5:
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            raise ValueError(f"Rating must be 1-5, got {v}")
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        return v
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def analyze_review(review_text: str, max_retries: int = 3) -> ProductReview | None:
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    for attempt in range(max_retries):
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        try:
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            resp = client.beta.chat.completions.parse(
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                model="gpt-4o-mini",
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                messages=[
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                    {"role": "system", "content": "Analyze the product review and extract structured information."},
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                    {"role": "user", "content": review_text},
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                ],
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                response_format=ProductReview,
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            )
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            if resp.choices[0].message.refusal:
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                print(f"Refusal on attempt {attempt + 1}: {resp.choices[0].message.refusal}")
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                continue
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            return resp.choices[0].message.parsed
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        except Exception as e:
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            print(f"Attempt {attempt + 1} failed: {e}")
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    return None
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# Test
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reviews = [
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    "Amazing product! Works perfectly and arrived quickly. 5 stars.",
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    "Terrible quality. Broke after one day. Very disappointed.",
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    "It's okay, nothing special. Does what it says.",
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]
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for review in reviews:
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    result = analyze_review(review)
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    if result:
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        print(f"Rating: {result.rating}/5 | {result.sentiment} | {result.summary}")
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