app.py

import os
import openai
import gradio as gr
import transformers

openai.api_key = os.environ["api"]


def generateBlogTopics(prompt1):
    response = openai.Completion.create(
        engine="text-davinci-002",
        prompt="Generate blog topics on: {}. \n \n 1.  ".format(prompt1),
        max_tokens=100,
        n=1,
        stop=None,
        temperature=0.7,
    )

    return response.choices[0].text

def generateBlogSections(prompt1):
    response = openai.Completion.create(
        engine="text-davinci-002",
        prompt="Expand the blog title in to high level blog sections: {} \n\n- Introduction: ".format(prompt1),
        max_tokens=100,
        n=1,
        stop=None,
        temperature=0.6,
    )

    return response.choices[0].text

def blogSectionExpander(prompt1):
    response = openai.Completion.create(
        engine="text-davinci-002",
        prompt="Expand the blog section in to a detailed professional, witty and clever explanation.\n\n {}".format(prompt1),
        max_tokens=400,
        n=1,
        stop=None,
        temperature=0.7,
    )

    return response.choices[0].text

input_text = gr.inputs.Textbox(lines=5, label="Enter prompt text here:")

title_section_output = gr.outputs.Textbox(label="Title & Sections")
section_expander_output = gr.outputs.Textbox(label="Section Expander")

gr.Interface(
    [generateBlogTopics, generateBlogSections],
    inputs=input_text,
    outputs=title_section_output,
    title="Blog Title & Sections Generator",
    description="Generate high level sections for your blog topic",
    live=False
).launch(share=True)

gr.Interface(
    blogSectionExpander,
    inputs=input_text,
    outputs=section_expander_output,
    title="Blog Section Expander",
    description="Expand your blog sections with professional and clever explanation",
    live=False
).launch(share=True)