app.py

from __future__ import absolute_import
from __future__ import division, print_function, unicode_literals
import openai
from sumy.parsers.html import HtmlParser
from sumy.parsers.plaintext import PlaintextParser
from sumy.nlp.tokenizers import Tokenizer
from sumy.summarizers.lsa import LsaSummarizer as Summarizer
from sumy.nlp.stemmers import Stemmer
from sumy.utils import get_stop_words
import gradio as gr



def maker(api_key, mode, input_text,detail,Spend_input_data_API_key_is_not_safed): 
    
    def cut_in_half(Text):
        list= Text.split('.')
        x=0
        for y in list:
            list[x] = str(list[x])+ "."
            x=x+1
        lenght = round(len(list)/2)
        x = 0
        Basis1 = ""
        Basis2 = ""
        while x != lenght:
            Basis1 = Basis1 + str(list[x])
            x =x+1
        
        while x  != lenght*2-1 :
            Basis2 = Basis2 + str(list[x])
            x =x+1
            
        Text = [Basis1, Basis2]
        return Text 
    def study_notes(Text):
        lenght = len(Text)
        if lenght > 20000:
            print("Over 20000 symboles. To much!")
        x = 0
        if lenght > 2200:
            Text = cut_in_half(Text)
            lenght = len(Text[0])
            x=1
            if lenght > 4000:
                Text1 = cut_in_half(Text[0])
                Text2 = cut_in_half(Text[1])
                Text = Text1 + Text2 
                x=3
        else:
            Text = [Text]
        return Text, x 

    def flashcards_maker(Text,x):  
        openai.api_key = api_key     
        response = openai.Completion.create(
        model="text-davinci-003",
        prompt="Please summarize the all important points from the following text and create a set of flashcards using Remnote's formatting. Each flashcard should have a question on the front and the corresponding short answer on the back. You can include additional information, such as definitions and examples, when possible. When you are finished, please provide the full set of flashcards in Remnote's format:\n\n" + Text[x] +"\n\nFlashcard \nQ: \nA: \n\n",
        temperature=0.7,
        max_tokens=600,
        top_p=1,
        frequency_penalty=0,
        presence_penalty=0
        )
        response1 = str(response["choices"][0]["text"]).replace("\n",":>")
        return response1

        #response1 = response1.replace(":>:>", "\n ")
    def flashcards_catorgizer(listsummery, response1,x):
        response1 = response1.split(":>:>")
        openai.api_key = api_key
        for y in response1:
            response = openai.Completion.create(
                model="text-davinci-003",
                prompt="Please give the main concept and the topic and the keywords to the flashcards, \"" + y + "\".\n\n",
                temperature=0.7,
                max_tokens=256,
                top_p=1,
                frequency_penalty=0,
                presence_penalty=0
            )
            
            response = (str(response["choices"][0]["text"]).replace("\n\n", "\n"))
            response = response.split("\n")
            
            listsummery = listsummery + response[0] + "\n" + response[1] +"\n   " + response[2]+ "\n      " + response[3]+ "\n" + "         " + y + "\n"
        
        return listsummery
    def summerizer(Text, detail):
        # Retrieve the input from the input box
        LANGUAGE = "english"
        SENTENCES_COUNT = round(len(Text)/(75*detail))
        
        if __name__ == "__main__":
            parser = PlaintextParser.from_string(Text, Tokenizer(LANGUAGE))
            stemmer = Stemmer(LANGUAGE)

            summarizer = Summarizer(stemmer)
            summarizer.stop_words = get_stop_words(LANGUAGE)
            Text = ""
            for sentence in summarizer(parser.document, SENTENCES_COUNT):
                Text = Text + str(sentence)
            
            return Text
    def concept_card_maker(api_key, input_text,detail,Spend_input_data_API_key_is_not_safed):
        concept_name =input_text
        openai.api_key = api_key
        response = openai.Completion.create(
        model="text-davinci-003",
        prompt="Describe \""+ concept_name + "\" as a concept with the point: name, concepts under it(listed in a list split by a comma), which are the bigger topics above it(listed in a list split by a comma), explanation, formula with a variable explanation if existed, use case, example.\n\nName:",
        temperature=0.7,
        max_tokens=800,
        top_p=1,
        frequency_penalty=0,
        presence_penalty=0
        )
        
        response = str(response["choices"][0]["text"])
        response = (response).replace("Formula (if existed): N/A\n\n", "")
        response = (response).replace("Formula (if existed): N/A\n", "")
        response = (response).replace("Formula: N/A\n", "")
        response = (response).replace("\n\n", "#\t\t")
        response = (response).replace("\n-", ";\t\t-")
        response = (response).replace("\n", "#\t\t")
        response = (response).replace(";", "\n")
        response = (response).replace("#", "\n\n")

        return concept_name + "\tConcept"+"\n\t\tName:" +response    
    
    Text = input_text
    if detail == "No summersiation":
        detail = 1
    elif detail == "low summersation":
        detail = 2
    elif detail == "medium summersation":
        detail = 6
    elif detail == "high summersation":
        detail = 12

    if mode == "flashcards with topics":
        catorgizer = 1
    if mode == "flashcards":
        catorgizer = 0
    if mode == "concepts cards":
        out = concept_card_maker(api_key, input_text,detail,Spend_input_data_API_key_is_not_safed)
            
        if Spend_input_data_API_key_is_not_safed == True:
            with open('\concept_data.txt', 'w', newline='') as f: 
                f.write([input_text,out,"concept"])
            
        return out

    if  detail != 1:
        Text = summerizer(Text, detail)
    
    Text, x = study_notes(Text)
    

    while x != -1:
        response1 = flashcards_maker(Text,x)
        listsummery = ""
        if catorgizer == 1:
            listsummery = flashcards_catorgizer(listsummery,response1,x)
            
        else:
            response1 = response1.replace(":>:>", "\n")
            listsummery =response1
            
        x = x-1

    listsummery = str(listsummery).replace('\n '," \n")
    out = f"{listsummery}"
    if Spend_input_data_API_key_is_not_safed == True:
        with open('\\flashcard_data.csv', 'w', newline='') as f:
            f.write([input_text,out])
    
    return out
  




iface =gr.Interface(fn = maker, allow_flagging= "never", inputs=
    [
    gr.Textbox(),
    gr.Dropdown(["flashcards", "concepts cards", "flashcards with topics"]),
    gr.Textbox( label = "Input Text", lines=10, placeholder="Enter your text here..."),
    gr.Dropdown(["No summersiation", "low summersation", "medium summersation", "high summersation"]),
    gr.Checkbox(value = True)
    
    ],
    outputs = "text", title = "Study cards maker", description= "This tool uses openAI GPT-3 to make study cards for you. This include flashcards, super usefull for Remnotes(reday to copy past). Please use yoru Openai api key. Which you get by sining up at https://openai.com/api/ "
)


if __name__ == "__main__":
    iface.launch()