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Create app.py

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import requests
from flask import Flask, request, jsonify, send_file
import logging
import re
import os
import time
import plotly.graph_objects as go
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from io import BytesIO
import matplotlib
matplotlib.use('Agg')

app = Flask(__name__)
app.static_folder = 'static'
logging.basicConfig(level=logging.DEBUG)

@app.route('/v2/images/generations', methods=['POST'])
def generate_image_cf():
    # 获取前端请求中的数据
    data = request.json
    logging.debug(f"Received request data: {data}")

    # 提取 Cloudflare 账户 ID 和 API 令牌
    cloudflare_account_id = data.get('CLOUDFLARE_ACCOUNT_ID')
    cloudflare_api_token = data.get('cloudflare_api_token')
    prompt = data.get('prompt')

    if not cloudflare_account_id or not cloudflare_api_token or not prompt:
        return jsonify({'error': 'Missing required parameters'}), 400

    # 构造 Cloudflare API 请求
    url = f"https://api.cloudflare.com/client/v4/accounts/{cloudflare_account_id}/ai/run/@cf/stabilityai/stable-diffusion-xl-base-1.0"
    headers = {"Authorization": f"Bearer {cloudflare_api_token}"}
    payload = {"prompt": prompt}

    # 发送请求到 Cloudflare API
    response = requests.post(url, headers=headers, json=payload)
    logging.debug(f"Response status code: {response.status_code}")

    # 检查响应状态码
    if response.status_code != 200:
        return jsonify({'error': 'Failed to generate image'}), response.status_code

    # 获取完整的响应内容
    response_data = response.content
    logging.debug(f"Response content: {response_data}")

    # 生成图像文件名
    img_filename = f'image_{int(time.time())}.png'
    save_path = os.path.join(app.static_folder, img_filename)

    # 将图像保存到 'static' 目录
    with open(save_path, 'wb') as f:
        f.write(response_data)

    # 构造返回给前端的数据
    img_url = f'https://mistpe-flask.hf.space/static/{img_filename}'
    result = {
        "created": int(time.time()),
        "data": [
            {"url": img_url}
        ]
    }
    return jsonify(result)

def preprocess_prompt(prompt):
    # 使用非捕获组 (?:...) 来匹配任意字符
    pattern = r'@startmindmap\n((?:.*?\n)*?)@endmindmap'
    match = re.search(pattern, prompt, re.DOTALL)
    if (match):
        mindmap_content = match.group(1)
        processed_prompt = f"@startmindmap\n{mindmap_content}\n@endmindmap"
    else:
        processed_prompt = prompt
    return processed_prompt

@app.route('/v1/images/generations', methods=['POST'])
def generate_image_plantuml():
    # 获取前端请求中的数据
    data = request.json
    logging.debug(f"Received request data: {data}")

    # 预处理 prompt
    processed_prompt = preprocess_prompt(data['prompt'])
    logging.debug(f"Processed prompt: {processed_prompt}")

    # 将数据发送到 https://mistpe-plantuml.hf.space/coder 接口
    response = requests.post('https://mistpe-plantuml.hf.space/coder', data=processed_prompt.encode('utf-8'))
    logging.debug(f"Response status code: {response.status_code}")

    # 检查响应状态码
    if response.status_code != 200:
        return jsonify({'error': 'Failed to generate image'}), response.status_code

    # 获取完整的响应内容
    response_data = response.content
    logging.debug(f"Response content: {response_data}")

    created = 1589478378 # 假设这是一个固定值
    url = f"https://mistpe-plantuml.hf.space/png/{response_data.decode('utf-8')}"

    # 构造返回给前端的数据
    result = {
        "created": created,
        "data": [
            {
                "url": url
            }
        ]
    }
    return jsonify(result)

@app.route('/api/3d-surface', methods=['POST'])
def generate_3d_surface():
    data = request.json
    prompt = data['prompt']

    # 提取#start和#end之间的代码
    start_index = prompt.find("#start") + len("#start")
    end_index = prompt.find("#end")
    code = prompt[start_index:end_index].strip()

    # 创建一个字典来存储局部变量
    local_vars = {}

    # 执行前端传入的代码,并传入局部变量字典
    exec(code, globals(), local_vars)

    # 从局部变量字典中获取 'fig' 对象
    fig = local_vars.get('fig')

    # 检查 'fig' 是否已定义
    if fig is None:
        return jsonify({"error": "No figure 'fig' defined in the provided code."}), 400

    # 保存图表为 HTML 文件
    html_filename = f'3d_surface_plot_{int(time.time())}.html'
    fig.write_html(f'static/{html_filename}')

    # 构建 HTML 文件的 URL
    html_url = f'https://mistpe-flask.hf.space/static/{html_filename}'

    # 保存 fig 对象为图像文件
    img_filename = f'3d_surface_plot_{int(time.time())}.png'
    fig.write_image(f'static/{img_filename}')

    # 构建图像文件的 URL
    img_url = f'https://mistpe-flask.hf.space/static/{img_filename}'

    # 返回 JSON 格式的响应, 包含 HTML 和图像的访问链接
    return jsonify({
        "created": int(time.time()),
        "data": [
            {"url": img_url},
            {"url": html_url}
        ]
    })

@app.route('/api/3d-sphere', methods=['POST'])
def generate_3d_sphere():
    # 获取请求中的代码
    code = request.json['prompt']

    # 判断代码是否以'''python开头和'''结尾
    if code.startswith("```python") and code.endswith("```"):
        # 如果是,则删除开头和结尾的字符串
        code = '\n'.join(code.split('\n')[1:-1])

    # 在主线程中执行代码生成 3D 图像
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    exec(code)

    # 将 3D 图像保存为 PNG 格式
    buf = BytesIO()
    plt.savefig(buf, format='png')
    buf.seek(0)

    # 生成图像文件名
    img_filename = f'3d_sphere_{int(time.time())}.png'
    save_path = os.path.join(app.static_folder, img_filename)

    # 将图像保存到 'static' 目录
    with open(save_path, 'wb') as f:
        f.write(buf.getvalue())

    # 返回 JSON 格式的响应,包含图像的访问链接
    img_url = f'https://mistpe-flask.hf.space/static/{img_filename}'
    return {
        "created": int(time.time()),
        "data": [
            {
                "url": img_url
            }
        ]
    }
    
@app.route('/', methods=['POST'])
def health_check():
    return jsonify({'status': 'OK'}), 200
    
if __name__ == '__main__':
    # 确保 static 目录存在
    if not os.path.exists('static'):
        os.makedirs('static')
    app.run(host='0.0.0.0', port=7860, debug=True)

	import requests
	from flask import Flask, request, jsonify, send_file
	import logging
	import re
	import os
	import time
	import plotly.graph_objects as go
	import numpy as np
	from mpl_toolkits.mplot3d import Axes3D
	import matplotlib.pyplot as plt
	from io import BytesIO
	import matplotlib
	matplotlib.use('Agg')

	app = Flask(__name__)
	app.static_folder = 'static'
	logging.basicConfig(level=logging.DEBUG)

	@app.route('/v2/images/generations', methods=['POST'])
	def generate_image_cf():
	# 获取前端请求中的数据
	data = request.json
	logging.debug(f"Received request data: {data}")

	# 提取 Cloudflare 账户 ID 和 API 令牌
	cloudflare_account_id = data.get('CLOUDFLARE_ACCOUNT_ID')
	cloudflare_api_token = data.get('cloudflare_api_token')
	prompt = data.get('prompt')

	if not cloudflare_account_id or not cloudflare_api_token or not prompt:
	return jsonify({'error': 'Missing required parameters'}), 400

	# 构造 Cloudflare API 请求
	url = f"https://api.cloudflare.com/client/v4/accounts/{cloudflare_account_id}/ai/run/@cf/stabilityai/stable-diffusion-xl-base-1.0"
	headers = {"Authorization": f"Bearer {cloudflare_api_token}"}
	payload = {"prompt": prompt}

	# 发送请求到 Cloudflare API
	response = requests.post(url, headers=headers, json=payload)
	logging.debug(f"Response status code: {response.status_code}")

	# 检查响应状态码
	if response.status_code != 200:
	return jsonify({'error': 'Failed to generate image'}), response.status_code

	# 获取完整的响应内容
	response_data = response.content
	logging.debug(f"Response content: {response_data}")

	# 生成图像文件名
	img_filename = f'image_{int(time.time())}.png'
	save_path = os.path.join(app.static_folder, img_filename)

	# 将图像保存到 'static' 目录
	with open(save_path, 'wb') as f:
	f.write(response_data)

	# 构造返回给前端的数据
	img_url = f'https://mistpe-flask.hf.space/static/{img_filename}'
	result = {
	"created": int(time.time()),
	"data": [
	{"url": img_url}
	]
	}
	return jsonify(result)

	def preprocess_prompt(prompt):
	# 使用非捕获组 (?:...) 来匹配任意字符
	pattern = r'@startmindmap\n((?:.?\n)?)@endmindmap'
	match = re.search(pattern, prompt, re.DOTALL)
	if (match):
	mindmap_content = match.group(1)
	processed_prompt = f"@startmindmap\n{mindmap_content}\n@endmindmap"
	else:
	processed_prompt = prompt
	return processed_prompt

	@app.route('/v1/images/generations', methods=['POST'])
	def generate_image_plantuml():
	# 获取前端请求中的数据
	data = request.json
	logging.debug(f"Received request data: {data}")

	# 预处理 prompt
	processed_prompt = preprocess_prompt(data['prompt'])
	logging.debug(f"Processed prompt: {processed_prompt}")

	# 将数据发送到 https://mistpe-plantuml.hf.space/coder 接口
	response = requests.post('https://mistpe-plantuml.hf.space/coder', data=processed_prompt.encode('utf-8'))
	logging.debug(f"Response status code: {response.status_code}")

	# 检查响应状态码
	if response.status_code != 200:
	return jsonify({'error': 'Failed to generate image'}), response.status_code

	# 获取完整的响应内容
	response_data = response.content
	logging.debug(f"Response content: {response_data}")

	created = 1589478378 # 假设这是一个固定值
	url = f"https://mistpe-plantuml.hf.space/png/{response_data.decode('utf-8')}"

	# 构造返回给前端的数据
	result = {
	"created": created,
	"data": [
	{
	"url": url
	}
	]
	}
	return jsonify(result)

	@app.route('/api/3d-surface', methods=['POST'])
	def generate_3d_surface():
	data = request.json
	prompt = data['prompt']

	# 提取#start和#end之间的代码
	start_index = prompt.find("#start") + len("#start")
	end_index = prompt.find("#end")
	code = prompt[start_index:end_index].strip()

	# 创建一个字典来存储局部变量
	local_vars = {}

	# 执行前端传入的代码,并传入局部变量字典
	exec(code, globals(), local_vars)

	# 从局部变量字典中获取 'fig' 对象
	fig = local_vars.get('fig')

	# 检查 'fig' 是否已定义
	if fig is None:
	return jsonify({"error": "No figure 'fig' defined in the provided code."}), 400

	# 保存图表为 HTML 文件
	html_filename = f'3d_surface_plot_{int(time.time())}.html'
	fig.write_html(f'static/{html_filename}')

	# 构建 HTML 文件的 URL
	html_url = f'https://mistpe-flask.hf.space/static/{html_filename}'

	# 保存 fig 对象为图像文件
	img_filename = f'3d_surface_plot_{int(time.time())}.png'
	fig.write_image(f'static/{img_filename}')

	# 构建图像文件的 URL
	img_url = f'https://mistpe-flask.hf.space/static/{img_filename}'

	# 返回 JSON 格式的响应, 包含 HTML 和图像的访问链接
	return jsonify({
	"created": int(time.time()),
	"data": [
	{"url": img_url},
	{"url": html_url}
	]
	})

	@app.route('/api/3d-sphere', methods=['POST'])
	def generate_3d_sphere():
	# 获取请求中的代码
	code = request.json['prompt']

	# 判断代码是否以'''python开头和'''结尾
	if code.startswith("```python") and code.endswith("```"):
	# 如果是,则删除开头和结尾的字符串
	code = '\n'.join(code.split('\n')[1:-1])

	# 在主线程中执行代码生成 3D 图像
	fig = plt.figure()
	ax = fig.add_subplot(111, projection='3d')
	exec(code)

	# 将 3D 图像保存为 PNG 格式
	buf = BytesIO()
	plt.savefig(buf, format='png')
	buf.seek(0)

	# 生成图像文件名
	img_filename = f'3d_sphere_{int(time.time())}.png'
	save_path = os.path.join(app.static_folder, img_filename)

	# 将图像保存到 'static' 目录
	with open(save_path, 'wb') as f:
	f.write(buf.getvalue())

	# 返回 JSON 格式的响应,包含图像的访问链接
	img_url = f'https://mistpe-flask.hf.space/static/{img_filename}'
	return {
	"created": int(time.time()),
	"data": [
	{
	"url": img_url
	}
	]
	}

	@app.route('/', methods=['POST'])
	def health_check():
	return jsonify({'status': 'OK'}), 200

	if __name__ == '__main__':
	# 确保 static 目录存在
	if not os.path.exists('static'):
	os.makedirs('static')
	app.run(host='0.0.0.0', port=7860, debug=True)