import functions_framework
from flask import Flask, jsonify, send_file
from flask_cors import CORS
import matplotlib.pyplot as plt
from matplotlib.backends.backend_svg import FigureCanvasSVG
import io
import os
import torch

app = Flask(__name__)
CORS(app)

def create_svg_plot():
    weight = 0.7
    bias = 0.3

    start = 0
    end = 1
    step = 0.02
    X = torch.arange(start, end, step).unsqueeze(dim=1)
    Y = weight * X + bias
    # print(Y)

    x = [1, 2, 3, 4, 5]
    y = [2, 4, 6, 8, 10]

    fig, ax = plt.subplots()
    ax.plot(x, y)
    ax.set_title('Sample Plot')
    ax.set_xlabel('X-axis')
    ax.set_ylabel('Y-axis')

    svg_output = io.StringIO()
    canvas = FigureCanvasSVG(fig)
    canvas.print_svg(svg_output)

    # Close the plot to free up resources
    plt.close(fig)

    return svg_output.getvalue()

@functions_framework.http
def curvefit(request):
    """HTTP Cloud Function.
    Args:
        request (flask.Request): The request object.
        <https://flask.palletsprojects.com/en/1.1.x/api/#incoming-request-data>
    Returns:
        The response text, or any set of values that can be turned into a
        Response object using `make_response`
        <https://flask.palletsprojects.com/en/1.1.x/api/#flask.make_response>.
    """
    if request.method == 'OPTIONS':
        headers = {
            'Access-Control-Allow-Origin': '*',
            'Access-Control-Allow-Methods': 'GET, POST, OPTIONS',
            'Access-Control-Allow-Headers': 'Content-Type',
            # 'Access-Control-Max-Age': '3600'
        }

        return ('', 204, headers)

    headers = {
        'Access-Control-Allow-Origin': '*'
    }

    svg_plot = create_svg_plot()

    output_path = os.getcwd() + "/" + "plot.svg"

    with open(output_path,'rb') as f:
        file_data = io.BytesIO(f.read())

    # return (jsonify({"plot": svg_plot}), 200, headers)
    return send_file(file_data, as_attachment=False, download_name= "plot.svg", mimetype='image/svg+xml')