AI脚本开发完全教程

# 安装常用AI和数据处理库
pip install numpy pandas
pip install tensorflow torch
pip install openai-api
pip install selenium beautifulsoup4

import openai
import os

# 设置API密钥
openai.api_key = os.getenv("OPENAI_API_KEY")

def generate_text(prompt):
    response = openai.Completion.create(
        engine="text-davinci-003",
        prompt=prompt,
        max_tokens=150
    )
    return response.choices[0].text.strip()

# 使用脚本
result = generate_text("写一段关于AI脚本开发的介绍")
print(result)

import asyncio
import aiohttp

async def fetch_data(session, url):
    async with session.get(url) as response:
        return await response.text()

async def main():
    async with aiohttp.ClientSession() as session:
        tasks = []
        # 创建多个并发任务
        for url in url_list:
            task = asyncio.create_task(fetch_data(session, url))
            tasks.append(task)
        
        # 等待所有任务完成
        results = await asyncio.gather(*tasks)
        return results

# 运行异步主函数
data = asyncio.run(main())

import logging
import traceback

# 配置日志
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler("ai_script.log"),
        logging.StreamHandler()
    ]
)

def safe_ai_call(api_func, *args, **kwargs):
    try:
        result = api_func(*args, **kwargs)
        logging.info(f"API调用成功: {api_func.__name__}")
        return result
    except Exception as e:
        logging.error(f"API调用失败: {str(e)}")
        logging.error(traceback.format_exc())
        return None