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ALwrity/ToBeMigrated/ai_writers/ai_product_description_writer.py
2025-08-06 16:29:49 +05:30

116 lines
4.3 KiB
Python

import streamlit as st
import json
from ..gpt_providers.text_generation.main_text_generation import llm_text_gen
def generate_product_description(title, details, audience, tone, length, keywords):
"""
Generates a product description using OpenAI's API.
Args:
title (str): The title of the product.
details (list): A list of product details (features, benefits, etc.).
audience (list): A list of target audience segments.
tone (str): The desired tone of the description (e.g., "Formal", "Informal").
length (str): The desired length of the description (e.g., "short", "medium", "long").
keywords (str): Keywords related to the product (comma-separated).
Returns:
str: The generated product description.
"""
prompt = f"""
Write a compelling product description for {title}.
Highlight these key features: {', '.join(details)}
Emphasize the benefits of these features for the target audience ({audience}).
Maintain a {tone} tone and aim for a length of approximately {length} words.
Use these keywords naturally throughout the description: {', '.join(keywords)}.
Remember to be persuasive and focus on the value proposition.
"""
try:
response = llm_text_gen(prompt)
return response
except Exception as err:
logger.error(f"Exit: Failed to get response from LLM: {err}")
exit(1)
def display_inputs():
st.title("📝 AI Product Description Writer 🚀")
st.markdown("**Generate compelling and accurate product descriptions with AI.**")
col1, col2 = st.columns(2)
with col1:
product_title = st.text_input("🏷️ **Product Title**", placeholder="Enter the product title (e.g., Wireless Bluetooth Headphones)")
with col2:
product_details = st.text_area("📄 **Product Details**", placeholder="Enter features, benefits, specifications, materials, etc. (e.g., Noise Cancellation, Long Battery Life, Water Resistant, Comfortable Design)")
col3, col4 = st.columns(2)
with col3:
keywords = st.text_input("🔑 **Keywords**", placeholder="Enter keywords, comma-separated (e.g., wireless headphones, noise cancelling, Bluetooth 5.0)")
with col4:
target_audience = st.multiselect(
"🎯 **Target Audience**",
["Teens", "Adults", "Seniors", "Music Lovers", "Fitness Enthusiasts", "Tech Savvy", "Busy Professionals", "Travelers", "Casual Users"],
placeholder="Select target audience (optional)"
)
col5, col6 = st.columns(2)
with col5:
description_length = st.selectbox(
"📏 **Desired Description Length**",
["Short (1-2 sentences)", "Medium (3-5 sentences)", "Long (6+ sentences)"],
help="Select the desired length of the product description"
)
with col6:
brand_tone = st.selectbox(
"🎨 **Brand Tone**",
["Formal", "Informal", "Fun & Energetic"],
help="Select the desired tone for the description"
)
return product_title, product_details, target_audience, brand_tone, description_length, keywords
def display_output(description):
if description:
st.subheader("✨ Generated Product Description:")
st.write(description)
json_ld = {
"@context": "https://schema.org",
"@type": "Product",
"name": product_title,
"description": description,
"audience": target_audience,
"brand": {
"@type": "Brand",
"name": "Your Brand Name"
},
"keywords": keywords.split(", ")
}
def write_ai_prod_desc():
product_title, product_details, target_audience, brand_tone, description_length, keywords = display_inputs()
if st.button("Generate Product Description 🚀"):
with st.spinner("Generating description..."):
description = generate_product_description(
product_title,
product_details.split(", "), # Split details into a list
target_audience,
brand_tone,
description_length.split(" ")[0].lower(), # Extract length from selectbox
keywords
)
display_output(description)