Use Vision API to detect products and generate advertising copy¶

from pydantic import BaseModel, Field
from typing import List, Optional


class Product(BaseModel):
    """
    Represents a product extracted from an image using AI.

    The product attributes are dynamically determined based on the content
    of the image and the AI's interpretation. This class serves as a structured
    representation of the identified product characteristics.
    """

    name: str = Field(
        description="A generic name for the product.", example="Headphones"
    )
    key_features: Optional[List[str]] = Field(
        description="A list of key features of the product that stand out.",
        default=None,
    )

    description: Optional[str] = Field(
        description="A description of the product.",
        default=None,
    )

    # Can be customized and automatically generated
    def generate_prompt(self):
        prompt = f"Product: {self.name}\n"
        if self.description:
            prompt += f"Description: {self.description}\n"
        if self.key_features:
            prompt += f"Key Features: {', '.join(self.key_features)}\n"
        return prompt

from pydantic import BaseModel, Field
from typing import Optional, List


class IdentifiedProduct(BaseModel):
    """
    Represents a list of products identified in the images.
    """

    products: Optional[List[Product]] = Field(
        description="A list of products identified by the AI.",
        example=[
            Product(
                name="Headphones",
                description="Wireless headphones with noise cancellation.",
                key_features=["Wireless", "Noise Cancellation"],
            )
        ],
        default=None,
    )

    error: bool = Field(default=False)
    message: Optional[str] = Field(default=None)

from pydantic import BaseModel, Field


class AdCopy(BaseModel):
    """
    Represents a generated ad copy.
    """

    headline: str = Field(
        description="A short, catchy, and memorable headline for the given product. The headline should invoke curiosity and interest in the product.",
    )
    ad_copy: str = Field(
        description="A long-form advertisement copy for the given product. This will be used in campaigns to promote the product with a persuasive message and a call-to-action with the objective of driving sales.",
    )
    name: str = Field(description="The name of the product being advertised.")

def read_images(image_urls: list[str]) -> IdentifiedProduct:
    """
    Given a list of image URLs, identify the products in the images.
    """

    logger.info(f"Identifying products in images... {len(image_urls)} images")

    return client_image.chat.completions.create(
        model="gpt-4o-mini",
        response_model=IdentifiedProduct,
        max_tokens=1024,  # can be changed
        temperature=0,
        messages=[
            {
                "role": "user",
                "content": [
                    {
                        "type": "text",
                        "text": "Identify products using the given images and generate key features for each product.",
                    },
                    *[
                        {"type": "image_url", "image_url": {"url": url}}
                        for url in image_urls
                    ],
                ],
            }
        ],
    )

def generate_ad_copy(product: Product) -> AdCopy:
    """
    Given a product, generate an ad copy for the product.
    """

    logger.info(f"Generating ad copy for product: {product.name}")

    return client_copy.chat.completions.create(
        model="gpt-4o-mini",
        response_model=AdCopy,
        temperature=0.3,
        messages=[
            {
                "role": "system",
                "content": "You are an expert marketing assistant for all products. Your task is to generate an advertisement copy for a product using the name, description, and key features.",
            },
            {"role": "user", "content": product.generate_prompt()},
        ],
    )