app.py

import gradio as gr
import requests
import os
import numpy as np
import pandas as pd
import json
import csv
import huggingface_hub
from huggingface_hub import Repository
# from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoModelForSequenceClassification
from questiongenerator import QuestionGenerator

qg = QuestionGenerator()

HF_TOKEN = os.environ.get("HF_TOKEN")
DATASET_NAME = "Question_Generation_T5"
DATASET_REPO_URL = f"https://huggingface.co/datasets/pragnakalp/{DATASET_NAME}"
DATA_FILENAME = "que_gen_logs.csv"
DATA_FILE = os.path.join("que_gen_logs", DATA_FILENAME)
DATASET_REPO_ID = "pragnakalp/Question_Generation_T5"
print("is none?", HF_TOKEN is None)
# REPOSITORY_DIR = "data"
# LOCAL_DIR = 'data_local'
# os.makedirs(LOCAL_DIR,exist_ok=True)

try:
    hf_hub_download(
        repo_id=DATASET_REPO_ID,
        filename=DATA_FILENAME,
        cache_dir=DATA_DIRNAME,
        force_filename=DATA_FILENAME
    )
    
except:
    print("file not found")

repo = Repository(
    local_dir="que_gen_logs", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
)

def get_device_ip_address():
    result = {}
    if os.name == "nt":
        result = "Running on Windows"
        hostname = socket.gethostname()
        ip_address = socket.gethostbyname(hostname)
        result['ip_addr'] = ip_address
        result['host'] = hostname
        return result
    elif os.name == "posix":
        gw = os.popen("ip -4 route show default").read().split()
        s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
        s.connect((gw[2], 0))
        ipaddr = s.getsockname()[0]
        gateway = gw[2]
        host = socket.gethostname()
        result['ip_addr'] = ipaddr
        result['host'] = host
        return result
    else:
        result = os.name + " not supported yet."
        return result
        
def generate_questions(article,num_que):
    result = ''
    try:
        if num_que == None or num_que == '':
            num_que = 5
        else:
            num_que = num_que
        generated_questions_list = qg.generate(article, num_questions=int(num_que))
        summarized_data = {
            "generated_questions" : generated_questions_list
        }
        generated_questions = summarized_data.get("generated_questions",'')
            
        for q in generated_questions:
            print(q)
            result = result + q + '\n'
        save_data_and_sendmail(article,generated_questions,num_que,result)
        return result
    except Exception as e:
        return "Error while generating question -->" + e
"""
Save generated details
"""
def save_data_and_sendmail(article,generated_questions,num_que,result):
    try:
        print("=====================================================>>>>>>>>>>>>>>>>")
        article1 = article
        generated_questions1 = []
        generated_questions1 = generated_questions
        num_que1 = num_que
        result1 = result
        hostname = get_device_ip_address()
        
        # url = 'https://pragnakalpdev35.pythonanywhere.com/HF_space_que_gen'
        url = 'http://pragnakalpdev33.pythonanywhere.com/HF_space_question_generator'
        myobj = {'article': article1,'gen_que':result1,'ip_addr':hostname.get("ip_addr",""),'host':hostname.get("host","")}
        print("myobj    ",myobj)
        x = requests.post(url, json = myobj)
        print(x) 
        add_csv = [article, generated_questions, num_que]
        with open(DATA_FILE, "a") as f:
            writer = csv.writer(f)
            # write the data
            writer.writerow(add_csv)
            commit_url = repo.push_to_hub()
            print("commit data   :",commit_url)
    # except Exception as e:
    #     return "Error while storing data -->" + e
        
    # try:  
          
        # with open(DATA_FILE, "r") as file:
        #     data = json.load(file)
        # data.append(entry)
        # with open(DATA_FILE, "w") as file:
        #     json.dump(data, file)
        #     commit_url = repo.push_to_hub()
    except Exception as e:
        return "Error while sending mail"
        
    return "Successfully save data"

## design 1
inputs=gr.Textbox(lines=5, label="Article/Text",elem_id="inp_div")
total_que = gr.Textbox(label="Number of Question want to generate",elem_id="inp_div")
outputs=gr.Textbox(lines=5, label="Generated Questions",elem_id="inp_div")

demo = gr.Interface(
    generate_questions,
    [inputs,total_que],
    outputs,
    title="Question Generation using T5",
    description="Feel free to give your feedback", 
    css=".gradio-container {background-color: lightgray} #inp_div {background-color: #7FB3D5;"
)
demo.launch(enable_queue = False)