apppp.py

import requests
from flask import Flask, render_template, request, send_from_directory
from datetime import datetime
from bs4 import BeautifulSoup
from googletrans import Translator
app = Flask(__name__)
with open('i.txt', 'r') as file:
    data = file.read()

API_URL = "https://api-inference.huggingface.co/models/mistralai/Mixtral-8x7B-Instruct-v0.1"
headers = {"Authorization": f"Bearer hf{data}"}


def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.json()

conversation_history = []

def generate_response(user_input):
    bitcoin_price, current_time = get_bitcoin_price()
    result = get_div_content(url)
    new_query = {
        "inputs": f"you are helpful assistant and your name is (Niron) for btc trad and predicition start chat with user with use good Emojeis\n\nBtc Price Now :${bitcoin_price} date and time now: {current_time}\n\n Bitcoin history Tidy is (Date/open/high/low/close/adj close/Volume): {result}\n\nLast news:{news}\n\ntask:complete the reesponse:\n\nconversation history:{conversation_history}\n\nUser message:{user_input}\n\nmake sure to response about it and don't generate alot of words just based on the user message and Use Emojies\n\nresponse:",
        "parameters": {
            "top_k": 100,
            "top_p": 0.9,
            "temperature": 0.5,
            "repetition_penalty": 1.2,
            "max_new_tokens": 512,
            "max_time": 0,
            "return_full_text": True,
            "num_return_sequences": 1,
            "do_sample": False
        },
        "options": {
            "use_cache": False,
            "wait_for_model": False
        }
    }

    output = query(new_query)

    generated_text = output[0]['generated_text']

    response_start = generated_text.find('response:') + len('response:')
    response_end = generated_text.find('(end response)')

    response_text = generated_text[response_start:response_end].strip()

    note_index = response_text.find("Note:")
    if note_index != -1:
        response_text = response_text[:note_index].strip()

    instruction_index = response_text.find("### Instruction:")
    if instruction_index != -1:
        response_text = response_text[:instruction_index].strip()
    
    response_text = response_text.strip().replace('\n', '<br>')

    return response_text
def get_bitcoin_price():
    current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    url = 'https://api.coindesk.com/v1/bpi/currentprice.json'
    response = requests.get(url)

    if response.status_code == 200:
        data = response.json()
        bitcoin_price = data['bpi']['USD']['rate']
        return bitcoin_price, current_time
    


@app.route('/assets/<path:path>')
def send_static(path):
    return send_from_directory('assets', path)


@app.route('/')
def index():
    result = get_div_content(url)
    news = get_news(url)
    return render_template('admin.html')

@app.route('/chat', methods=['POST'])
def chat():
    user_input = request.get_json()['user_input']
    
    # Generate AI response based on user input
    response_text = generate_response(user_input)
    conversation_history.append({"User": user_input, "NIRON": response_text})
    
    # Update bitcoin price and current time
    bitcoin_price, current_time = get_bitcoin_price()

    return response_text

@app.route('/trans')
def trans():
    news = get_news(url)
    result = get_div_content(url)

    return render_template('arabic.html')


@app.route('/arabic', methods=['POST'])
def arabic():
    user_input = request.get_json()['user_input']
    
    # Generate AI response based on user input
    response_text = generate_response(user_input)
    
    # Translate the response to Arabic
    translator = Translator()
    translated_response = translator.translate(response_text, dest='ar').text
    
    conversation_history.append({"User": user_input, "AI": response_text})
    
    # Update bitcoin price and current time
    bitcoin_price, current_time = get_bitcoin_price()
    return translated_response

def get_div_content(url):
    response = requests.get(url)
    soup = BeautifulSoup(response.content, 'html.parser')
    
    div_content = soup.find('div', {'id': '45'})
    if div_content:
        return div_content
    else:
        return None

url = "https://dooratre-info.hf.space/?logs=container&__sign=eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sIm9uQmVoYWxmT2YiOnsia2luZCI6InVzZXIiLCJfaWQiOiI2NWIyYzMyNjJiZTk2NjBmMGIxMjg0MDAiLCJ1c2VyIjoiRG9vcmF0cmUifSwiaWF0IjoxNzEyNjgwNTY4LCJzdWIiOiIvc3BhY2VzL0Rvb3JhdHJlL2luZm8iLCJleHAiOjE3MTI3NjY5NjgsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.R_PX6Hw5SMheYTQWPGe1Qla9q8gVBU0mAFF_u8Iad06jSpZ9sPzZqquSowWn7PGVLRYBW21DnvqSwXIoNZ4CAA"

result = get_div_content(url)
print(result)



@app.route('/clear_history')
def clear_history():
    global conversation_history
    conversation_history = []
    return 'Conversation history cleared successfully'



def get_news(url):
    response = requests.get(url)
    soup = BeautifulSoup(response.content, "html.parser")

    news = []
    for text in soup.stripped_strings:
        news.append(text)

    return news

url = "https://www.newsbtc.com/"
news = get_news(url)
print(news)
    
if __name__ == '__main__':
    app.run(debug=True)