Python+AI自动化办公的核心思路

利用Python结合AI工具（如OpenAI API、LangChain等）可以高效处理重复性办公任务。以下为常见场景的实现方法：

批量处理Excel/CSV文件

import pandas as pd
from openai import OpenAI

client = OpenAI(api_key="your_key")

def ai_process_data(df):
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": f"分析这段数据:{df.to_string()}"}]
    )
    return response.choices[0].message.content

data = pd.read_excel("data.xlsx")
result = ai_process_data(data)
print(result)

自动生成文档报告

def generate_report(template_path, data):
    with open(template_path) as f:
        template = f.read()
    
    prompt = f"根据以下数据生成报告:\n数据:{data}\n模板:{template}"
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": prompt}]
    )
    return response.choices[0].message.content

邮件自动处理系统

import imaplib
import email

def process_emails():
    mail = imaplib.IMAP4_SSL('imap.gmail.com')
    mail.login('your@email.com', 'password')
    mail.select('inbox')
    
    _, data = mail.search(None, 'UNSEEN')
    for num in data[0].split():
        _, msg_data = mail.fetch(num, '(RFC822)')
        raw_email = msg_data[0][1]
        email_message = email.message_from_bytes(raw_email)
        
        # 使用AI分析邮件内容
        response = client.chat.completions.create(
            model="gpt-3.5-turbo",
            messages=[{"role": "user", "content": f"处理这封邮件:{email_message.get_payload()}"}]
        )
        print(response.choices[0].message.content)

会议纪要自动化

def summarize_meeting(audio_path):
    audio_file = open(audio_path, "rb")
    transcript = client.audio.transcriptions.create(
        file=audio_file,
        model="whisper-1",
        response_format="text"
    )
    
    summary = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": f"总结会议内容:\n{transcript}"}]
    )
    return summary.choices[0].message.content

自动化数据可视化

import matplotlib.pyplot as plt

def smart_visualize(data):
    analysis = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": f"建议最适合这段数据的图表类型:\n{data.to_string()}"}]
    )
    chart_type = analysis.choices[0].message.content.lower()
    
    if "bar" in chart_type:
        data.plot.bar()
    elif "line" in chart_type:
        data.plot.line()
    elif "pie" in chart_type:
        data.plot.pie()
    plt.savefig("auto_chart.png")

这些代码片段展示了如何结合Python与AI技术实现办公自动化。实际应用中需要根据具体需求调整API调用参数和处理逻辑。