app.py

from flask import Flask, request, Response, jsonify, send_from_directory
import os
import requests
import json
from dotenv import load_dotenv
from search import search
import prompts

# Загрузка переменных окружения из файла .env
load_dotenv()

app = Flask(__name__, static_url_path='/static', static_folder='static')

initial_prompt = """
{запрос пользователя}

Источники:
{источники}
"""

@app.route('/')
def index():
    return app.send_static_file('index.html')

@app.route('/send_message', methods=['POST'])
def send_message():
    data = request.json
    user_message = data.get('message')
    conversation_history = data.get('history', [])
    
    if user_message:
        # Добавляем системное сообщение, если его нет в истории
        if not any(msg['role'] == 'system' for msg in conversation_history):
            conversation_history.insert(0, {"role": "system", "content": prompts.SYSTEM_PROMPT})


        search_request = ". ".join([msg['display'] for msg in conversation_history if msg['role'] == 'user']) + ". "+user_message
        
        print('search', search_request)
        _, sources = search(search_request)
        
        print('results', sources)
        
        formatted_user_message = prompts.MESSAGE_PROMPT_TEMPLATE.format(
            ВОПРОС_ПОЛЬЗОВАТЕЛЯ=user_message,
            ПОЛЕЗНАЯ_ИНФОРМАЦИЯ='\n\n'.join(sources)
        )
        
        # Добавляем сообщение пользователя в историю
        conversation_history.append({"role": "user", "content": formatted_user_message, "display": user_message})
        
        # Отправляем историю сообщений в API
        response = fetch_deep_infra_response(conversation_history)
        
        # Добавляем ответ бота в историю
        conversation_history.append({"role": "assistant", "content": response, "display": response})
        
        # Используем json.dumps с ensure_ascii=False
        response_data = {
            'response': response,
            'history': conversation_history
        }
        return Response(json.dumps(response_data, ensure_ascii=False), content_type='application/json; charset=utf-8')
    return jsonify({'response': 'Please provide a message.', 'history': conversation_history}), 400

def fetch_deep_infra_response(conversation_history):
    api_url = 'https://api.deepinfra.com/v1/openai/chat/completions'
    api_key = os.getenv('DEEPINFRA_API_KEY') 
    if not api_key:
        raise ValueError("DEEPINFRA_API_KEY environment variable is not set")
    
    response = requests.post(
        api_url,
        headers={
            'Content-Type': 'application/json',
            'Authorization': f'{api_key}'
        },
        json={
            "model": os.getenv('LLM_NAME', "mistralai/Mixtral-8x7B-Instruct-v0.1"),
            "messages": conversation_history,
            "temperature": os.getenv('LLM_TEMPERATURE', 0),
            "max_tokens": os.getenv('LLM_MAX_TOKENS', 2000),
            "top_p": os.getenv('LLM_TOP_P', 0.95),
            "presence_penalty": os.getenv('LLM_PRESENSE_PENALTY', 1),
            "frequency_penalty": os.getenv('LLM_FREQUENCY_PENALTY', -0.001),
        }
    )
    if response.status_code == 200:
        data = response.json()
        return data['choices'][0]['message']['content'].strip()
    else:
        print(response.json())
        return 'Sorry, something went wrong.'

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=os.getenv('APP_PORT', 7860), debug=False)