| from __future__ import annotations |
| import os, openai |
| from langchain.prompts import PromptTemplate |
| from langchain.chat_models import ChatOpenAI |
| from typing import Any |
| from langchain.base_language import BaseLanguageModel |
| from langchain.chains.llm import LLMChain |
| import gradio as gr |
|
|
| OPENAI_API_KEY = os.environ["OPENAI_API_KEY"] |
| prompt_file = "prompt_template.txt" |
|
|
|
|
| class ProductDescGen(LLMChain): |
| """LLM Chain specifically for generating multi paragraph rich text product description using emojis.""" |
|
|
| @classmethod |
| def from_llm( |
| cls, llm: BaseLanguageModel, prompt: str, **kwargs: Any |
| ) -> ProductDescGen: |
| """Load ProductDescGen Chain from LLM.""" |
| return cls(llm=llm, prompt=prompt, **kwargs) |
|
|
|
|
| def product_desc_generator(product_name, keywords): |
| with open(prompt_file, "r") as file: |
| prompt_template = file.read() |
|
|
| PROMPT = PromptTemplate( |
| input_variables=["product_name", "keywords"], template=prompt_template |
| ) |
| llm = ChatOpenAI( |
| model_name="gpt-4o", |
| temperature=0.7, |
| openai_api_key=OPENAI_API_KEY, |
| ) |
|
|
| ProductDescGen_chain = ProductDescGen.from_llm(llm=llm, prompt=PROMPT) |
| ProductDescGen_query = ProductDescGen_chain.apply_and_parse( |
| [{"product_name": product_name, "keywords": keywords}] |
| ) |
| return ProductDescGen_query[0]["text"] |
|
|
|
|
| with gr.Blocks() as demo: |
| gr.HTML("""<h1>Welcome to Product Description Generator</h1>""") |
| gr.Markdown( |
| "Generate Product Description for your products instantly!<br>" |
| "Provide product name and keywords related to that product. Click on 'Generate Description' button and multi-paragraph rich text product description will be genrated instantly.<br>" |
| "Note: Generated product description is SEO compliant and can be used to populate product information." |
| ) |
|
|
| with gr.Tab("Generate Product Description!"): |
| product_name = gr.Textbox( |
| label="Product Name", |
| placeholder="Nike Shoes", |
| ) |
| keywords = gr.Textbox( |
| label="Keywords (separated by commas)", |
| placeholder="black shoes, leather shoes for men, water resistant", |
| ) |
| product_description = gr.Markdown(label="Product Description", show_label=True, line_breaks=True) |
| click_button = gr.Button(value="Generate Description!") |
| click_button.click( |
| product_desc_generator, [product_name, keywords], product_description |
| ) |
|
|
| demo.launch() |
|
|
