app.py

import gradio as gr
from gpt_s import GPT

summary_message = '''
You are a summarizer, you give a comprehensive summary of a transcription you will be provided with. 
Give back the summary in the same langugae of the text you recieve."
'''
insights_message = '''
You are an insights extractor, you give a comprehensive list of points that gives the main ideas and insights from a given transcription you will be provided with.
Give back the list as bullet points, with the same language of the text you receive.
'''

questions_message = '''
You are a question extractor, you give a deep insightful questions about the topics and points that are mentioned in the transcription of the talk you are provided with.
Be critical and smart.
Give back the questions as a list, in the same language of the text you recieve.
'''

summ_gpt = GPT(summary_message)
insights_gpt = GPT(insights_message)
ques_gpt = GPT(questions_message)
def process(input_text):
    return [summ_gpt.extract_insights(input_text), 
           insights_gpt.extract_insights(input_text),
           ques_gpt.extract_insights(input_text)]

iface = gr.Interface(
    fn=process, 
    inputs=gr.Textbox(lines=10, placeholder="Enter a big chunk of text here..."), 
    outputs=[gr.Textbox(lines=5, placeholder="Processed paragraph will appear here..."),
             gr.Textbox(lines=5, placeholder="Processed paragraph will appear here..."),
             gr.Textbox(lines=5, placeholder="Processed paragraph will appear here...")],
    title="Summarizer",
    description="This interface takes a large chunk of text and returns a processed paragraph."
)

iface.launch()