allora/app.py

import json
import pickle
import pandas as pd
import numpy as np
from datetime import datetime
from flask import Flask, jsonify, Response
from model import download_data, format_data, train_model, training_price_data_path
from config import model_file_path

app = Flask(__name__)


def update_data():
    """Download price data, format data and train model."""
    download_data()
    format_data()
    train_model()


def get_inference(token, period):
    try:
        with open(model_file_path, "rb") as f:
            loaded_model = pickle.load(f)

        # Загружаем последние данные из файла
        price_data = pd.read_csv(training_price_data_path)

        # Используем последние значения признаков для предсказания
        last_row = price_data.iloc[-1]

        # Получаем последний timestamp
        last_timestamp = last_row["timestamp"]

        # Преобразуем период в секунды (пример)
        period_seconds = convert_period_to_seconds(period)

        # Рассчитываем новый временной штамп на основе периода
        new_timestamp = last_timestamp + period_seconds

        # timestamp
        X_new = np.array(
            [
                new_timestamp,
                last_row["price_diff"],
                last_row["volatility"],
                last_row["volume"],
                last_row["moving_avg_7"],
                last_row["moving_avg_30"],
            ]
        ).reshape(1, -1)

        # Предсказание
        future_price_pred = loaded_model.predict(X_new)

        return future_price_pred[0]

    except Exception as e:
        print(f"Error during inference: {str(e)}")
        raise


def convert_period_to_seconds(period):
    """Конвертируем период в секунды."""
    if period.endswith("min"):
        return int(period[:-3]) * 60
    elif period.endswith("h"):
        return int(period[:-1]) * 3600
    elif period.endswith("d"):
        return int(period[:-1]) * 86400
    else:
        raise ValueError(f"Unknown period format: {period}")


@app.route("/inference/<string:token>/<string:period>")
def generate_inference(token, period):
    """Generate inference for given token and period."""
    try:
        inference = get_inference(token, period)
        return Response(str(inference), status=200)
    except Exception as e:
        return Response(
            json.dumps({"error": str(e)}), status=500, mimetype="application/json"
        )


@app.route("/update")
def update():
    """Update data and return status."""
    try:
        update_data()
        return "0"
    except Exception:
        return "1"


if __name__ == "__main__":
    update_data()
    app.run(host="0.0.0.0", port=8127)