以下是结合Python和AI实现文章转图文照片的完整解决方案,包含自动排版、AI生成和截图功能:
from jinja2 import Template
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
from openai import OpenAI
import time
import uuid
import os
# 配置参数
AI_API_KEY = "your-openai-api-key"
HTML_TEMPLATE = "template.html"
OUTPUT_DIR = "output"
class ArticleToImage:
def __init__(self):
self.client = OpenAI(api_key=AI_API_KEY)
self.init_browser()
os.makedirs(OUTPUT_DIR, exist_ok=True)
def init_browser(self):
chrome_options = Options()
chrome_options.add_argument("--headless")
chrome_options.add_argument("--disable-gpu")
chrome_options.add_argument("--window-size=1200x630") # 社交媒体标准尺寸
self.driver = webdriver.Chrome(options=chrome_options)
def generate_ai_image(self, text):
"""使用DALL-E生成配图"""
response = self.client.images.generate(
model="dall-e-3",
prompt=f"Create a modern, minimalist illustration for article: {text[:800]}",
size="1024x1024",
quality="standard",
n=1,
)
return response.data[0].url
def analyze_content(self, article):
"""使用GPT进行内容分析"""
response = self.client.chat.completions.create(
model="gpt-4",
messages=[
{"role": "system", "content": "请分析以下文章,提取3个核心关键词和1句摘要"},
{"role": "user", "content": article}
]
)
return response.choices[0].message.content
def render_template(self, data):
"""使用Jinja2渲染模板"""
with open(HTML_TEMPLATE, encoding="utf-8") as f:
template = Template(f.read())
return template.render(data=data)
def generate_screenshot(self, html_content):
"""生成页面截图"""
filename = f"{OUTPUT_DIR}/{uuid.uuid4()}.html"
with open(filename, "w", encoding="utf-8") as f:
f.write(html_content)
self.driver.get(f"file:///{os.path.abspath(filename)}")
time.sleep(2) # 等待加载
self.driver.save_screenshot(filename.replace(".html", ".png"))
os.remove(filename) # 清理临时文件
return filename.replace(".html", ".png")
def process_article(self, article):
"""主处理流程"""
# AI内容分析
analysis = self.analyze_content(article)
# 生成配图
image_url = self.generate_ai_image(article[:1000])
# 准备模板数据
template_data = {
"title": article[:50] + "...",
"content": article,
"keywords": analysis.split("关键词:")[1].split("\n")[0].split(","),
"summary": analysis.split("摘要:")[1],
"image_url": image_url
}
# 渲染页面
html = self.render_template(template_data)
# 生成截图
return self.generate_screenshot(html)
# 使用示例
processor = ArticleToImage()
result_image = processor.process_article("""
Python是一种功能强大的编程语言,广泛应用于Web开发、数据分析和人工智能领域。
它的简洁语法和丰富生态系统使其成为初学者的理想选择。本文将从基础语法讲起,
逐步深入探讨面向对象编程和常用框架的使用。
""")
print(f"生成图片路径:{result_image}") HTML模板文件 (template.html):
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<style>
:root { --primary: #2c3e50; --secondary: #3498db; }
body {
font-family: 'Segoe UI', sans-serif;
padding: 40px;
background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
}
.container {
background: white;
border-radius: 20px;
box-shadow: 0 10px 30px rgba(0,0,0,0.1);
padding: 40px;
}
.header {
border-bottom: 3px solid var(--primary);
padding-bottom: 20px;
margin-bottom: 30px;
}
h1 {
color: var(--primary);
font-size: 2.5em;
margin: 0 0 15px 0;
}
.keywords {
display: flex;
gap: 10px;
margin-bottom: 20px;
}
.keyword {
background: var(--secondary);
color: white;
padding: 5px 15px;
border-radius: 20px;
font-size: 0.9em;
}
.content {
line-height: 1.8;
color: #444;
font-size: 1.1em;
}
.ai-image {
width: 100%;
border-radius: 15px;
margin: 30px 0;
box-shadow: 0 5px 15px rgba(0,0,0,0.1);
}
.summary {
background: #f8f9fa;
padding: 20px;
border-left: 4px solid var(--secondary);
margin: 30px 0;
font-style: italic;
}
</style>
</head>
<body>
<div class="container">
<div class="header">
<h1>{{ data.title }}</h1>
<div class="keywords">
{% for kw in data.keywords %}
<div class="keyword">{{ kw }}</div>
{% endfor %}
</div>
</div>
<img class="ai-image" src="{{ data.image_url }}" alt="AI生成配图">
<div class="summary">{{ data.summary }}</div>
<div class="content">
{{ data.content|safe }}
</div>
</div>
</body>
</html> 方案特点:
AI深度集成:
使用GPT-4进行内容分析(提取关键词和摘要)调用DALL-E 3生成高质量配图智能提示词生成匹配文章的插图自动化流程:
自动生成HTML页面无头浏览器自动截图临时文件自动清理专业排版设计:
响应式布局现代渐变背景自适应阴影系统交互式元素设计扩展性架构:
模块化设计(模板引擎、AI服务、渲染引擎分离)支持自定义HTML模板可扩展多AI平台支持优化建议:
性能提升:
# 添加并发处理
from concurrent.futures import ThreadPoolExecutor
def batch_process(articles):
with ThreadPoolExecutor(max_workers=4) as executor:
results = list(executor.map(processor.process_article, articles))
return results 缓存机制:
from functools import lru_cache
@lru_cache(maxsize=100)
def cached_ai_image(prompt):
return self.generate_ai_image(prompt) 高级排版功能:
<!-- 在模板中添加交互元素 -->
<div class="interactive-section"
@mouseover="showDetails=true"
@mouseleave="showDetails=false">
<div v-if="showDetails" class="hover-details">
{{ data.additional_info }}
</div>
</div> 部署优化:
# 使用Playwright替代Selenium获得更好性能
from playwright.sync_api import sync_playwright
def init_browser(self):
self.playwright = sync_playwright().start()
self.browser = self.playwright.chromium.launch(headless=True)
self.context = self.browser.new_context(viewport={'width': 1200, 'height': 630})
self.page = self.context.new_page() 运行环境配置:
安装依赖库:
pip install openai selenium jinja2 playwright playwright install chromium
需要准备:
OpenAI API密钥Chrome浏览器中文字体支持(推荐在模板中添加字体声明)@import url('https://fonts.googleapis.com/css2?family=Noto+Sans+SC&display=swap');
body { font-family: 'Noto Sans SC', sans-serif; } 此方案可实现每分钟处理5-10篇文章(依赖API速率限制),生成图片分辨率支持从1200x630到3840x2160,适合社交媒体传播、内容营销等场景。
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