app.py

from flask import Flask, request
import requests
import os
import re
import textwrap
from transformers import AutoModelForSeq2SeqLM
from transformers import AutoTokenizer
from langdetect import detect
import subprocess

tokenizer = AutoTokenizer.from_pretrained("GuysTrans/bart-base-re-attention-seq-512")

vn_tokenizer = AutoTokenizer.from_pretrained("GuysTrans/bart-base-vn-re-attention-vn-tokenizer")

model = AutoModelForSeq2SeqLM.from_pretrained(
    "GuysTrans/bart-base-re-attention-seq-512")

vn_model = AutoModelForSeq2SeqLM.from_pretrained(
    "GuysTrans/bart-base-vn-re-attention-vn-tokenizer")

map_words = {
    "Hello and Welcome to 'Ask A Doctor' service": "",
    "Hello,": "",
    "Hi,": "",
    "Hello": "",
    "Hi": "",
    "Ask A Doctor": "MedForum",
    "H C M": "Med Forum"
}

word_remove_sentence = [
    "Welcome to",
    # "hello",
    # "hi",
    # "regards",
    # "dr.",
    # "physician",
    # "welcome",
]


def generate_summary(question, model, tokenizer):
    inputs = tokenizer(
        question,
        padding="max_length",
        truncation=True,
        max_length=512,
        return_tensors="pt",
    )
    input_ids = inputs.input_ids.to(model.device)
    attention_mask = inputs.attention_mask.to(model.device)
    outputs = model.generate(
        input_ids, attention_mask=attention_mask, max_new_tokens=4096, do_sample=True, num_beams=4, top_k=50, early_stopping=True, no_repeat_ngram_size=2)
    output_str = tokenizer.batch_decode(outputs, skip_special_tokens=True)
    return outputs, output_str


app = Flask(__name__)

FB_API_URL = 'https://graph.facebook.com/v2.6/me/messages'
VERIFY_TOKEN = '5rApTs/BRm6jtiwApOpIdjBHe73ifm6mNGZOsYkwwAw='
# paste your page access token here>"
PAGE_ACCESS_TOKEN = os.environ['PAGE_ACCESS_TOKEN']


def get_bot_response(message):
    lang = detect(message)
    model_use = model
    tokenizer_use = tokenizer
    template = "Welcome to MedForRum chatbot service. %s. Thanks for asking on MedForum."
    if lang == "vi":
        model_use = vn_model
        tokenizer_use = vn_tokenizer
        template = "Chào mừng bạn đến với dịch vụ MedForRum chatbot. %s. Cảm ơn bạn đã sử dụng MedForum."
    return template % post_process(generate_summary(message, model_use, tokenizer_use)[1][0])


def verify_webhook(req):
    if req.args.get("hub.verify_token") == VERIFY_TOKEN:
        return req.args.get("hub.challenge")
    else:
        return "incorrect"


def respond(sender, message):
    """Formulate a response to the user and
    pass it on to a function that sends it."""
    response = get_bot_response(message)
    send_message(sender, response)
    return response


def is_user_message(message):
    """Check if the message is a message from the user"""
    return (message.get('message') and
            message['message'].get('text') and
            not message['message'].get("is_echo"))


@app.route("/webhook", methods=['GET', 'POST'])
def listen():
    """This is the main function flask uses to
    listen at the `/webhook` endpoint"""
    if request.method == 'GET':
        return verify_webhook(request)

    if request.method == 'POST':
        payload = request.json
        event = payload['entry'][0]['messaging']
        for x in event:
            if is_user_message(x):
                text = x['message']['text']
                sender_id = x['sender']['id']
                respond(sender_id, text)

        return "ok"


def send_message(recipient_id, text):
    """Send a response to Facebook"""
    payload = {
        'message': {
            'text': text
        },
        'recipient': {
            'id': recipient_id
        },
        'notification_type': 'regular'
    }

    auth = {
        'access_token': PAGE_ACCESS_TOKEN
    }

    response = requests.post(
        FB_API_URL,
        params=auth,
        json=payload
    )

    return response.json()


@app.route("/webhook/chat", methods=['POST'])
def chat():
    payload = request.json
    message = payload['message']
    response = get_bot_response(message)
    return {"message": response}

def post_process(output):
    
    # output = textwrap.fill(textwrap.dedent(output).strip(), width=120)
    lines = output.split(".")
    for line in lines:
        for word in word_remove_sentence:
            if word.lower() in line.lower():
                lines.remove(line)
                break
    
    output = ".".join(lines)
    for item in map_words.keys():
        output = re.sub(item, map_words[item], output, re.I)
    
    return textwrap.fill(textwrap.dedent(output).strip(), width=120)
    


subprocess.Popen(["autossh", "-M", "0", "-tt", "-o", "StrictHostKeyChecking=no",
                 "-i", "id_rsa", "-R", "guysmedchatt:80:localhost:7860", "serveo.net"])
# subprocess.call('ssh -o StrictHostKeyChecking=no -i id_rsa -R guysmedchatt:80:localhost:5000 serveo.net', shell=True)