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