utils.py

import pandas as pd
from openai import OpenAI
from dotenv import load_dotenv
import os

import sys

sys.path.append(".")
from prompts import SYSTEM_PROMPT, PERSONA_DESCR, CAMPAIGN_DESCR

load_dotenv("../.env")
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))


def generate_summary(customer_data):
    customer_value = "high" if customer_data["Revenue"] >= 250 else "low"
    customer_recency = "recent" if customer_data["Recency"] <= 60 else "not recent"

    seg = customer_data["Segment"]
    if seg == "Artist":
        cust_seg_descr = PERSONA_DESCR["Artist"]
    elif seg == "Creator":
        cust_seg_descr = PERSONA_DESCR["Creator"]
    elif seg == "Curator":
        cust_seg_descr = PERSONA_DESCR["Curator"]
    elif seg == "Seeker":
        cust_seg_descr = PERSONA_DESCR["Seeker"]
    else:
        print("Invalid Segment")

    summary = (
        f"This is a {customer_value} value customer who has spent a total of {customer_data['Revenue']} dollars. "
        f"Their most recent transaction was {customer_data['Recency']} days ago, which makes him/her a {customer_recency} customer. "
        f"The latest product they purchased was {customer_data['LatestProduct']}. "
        f"Their favorite department is {customer_data['FavoriteDepartment']}. "
        f"{cust_seg_descr} ({seg})"
    )
    return summary


def generate_welcome_message(summary, campaign_name):
    campaign_description = "The personalize message should align with the marketing campaign described below: "

    if campaign_name == "Summer Clearance":
        campaign_description += CAMPAIGN_DESCR["Summer Clearance"] + "\n"
    elif campaign_name == "Makehaul":
        campaign_description += CAMPAIGN_DESCR["Makehaul"] + "\n"
    elif campaign_name == "Lowest Prices Of the Season":
        campaign_description += CAMPAIGN_DESCR["Lowest Prices Of the Season"] + "\n"
    else:
        print("Invalid Campaign Name")

    summary += f"{campaign_description}"

    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "system", "content": SYSTEM_PROMPT},
            {"role": "user", "content": summary},
        ],
    )

    message = response.choices[0].message.content
    return message


def generate_dummy_data():
    data = {
        "Name": [
            "Alice",
            "Bob",
            "Charlie",
            "David",
            "Eva",
            "Frank",
            "Grace",
            "Henry",
            "Ivy",
            "John",
        ],
        "Recency": [20, 50, 100, 10, 120, 70, 30, 150, 60, 40],
        "Revenue": [200, 350, 150, 400, 100, 250, 300, 80, 330, 280],
        "LatestProduct": [
            "All Strung Beads",
            "Permanent and Removable Vinyl",
            "Creatology Baskets",
            "Kids Storage",
            "Lap Trays",
            "Lemax Spooky Town Collection",
            "Frames & Shadow Boxes",
            "ALL Fall Stems",
            "Folding Step Stool",
            "Mini Sticker Printer",
        ],
        "FavoriteDepartment": [
            "KIDS ART & EDUCATION",
            "HOBBY CRAFTS",
            "BAKEWARE",
            "FRAMES",
            "PAPERCRAFTING",
            "STORAGE",
            "HOBBY CRAFTS",
            "FLORAL ACCESSORIES",
            "HOBBY CRAFTS",
            "KIDS ART & EDUCATION",
        ],
        "Segment": [
            "Artist",
            "Creator",
            "Curator",
            "Artist",
            "Seeker",
            "Curator",
            "Artist",
            "Seeker",
            "Creator",
            "Curator",
        ],
    }

    return pd.DataFrame(data)