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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)
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