AIGC 办公场景实战教程

import openai
import streamlit as st

st.title("AI 邮件助手")

email_content = st.text_area("输入邮件内容:")
tone = st.selectbox("选择语气:", ["正式", "友好", "简洁"])

if st.button("生成回复"):
    prompt = f"请用 {tone} 语气回复这封邮件: {email_content}"
    response = openai.ChatCompletion.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}]
    )
    st.write("AI 生成的回复：")
    st.write(response["choices"][0]["message"]["content"])

import whisper
import openai

# 语音转文字
model = whisper.load_model("base")
result = model.transcribe("meeting_audio.mp3")

# 生成会议纪要
prompt = f"请总结以下会议内容：\n{result['text']}"
summary = openai.ChatCompletion.create(
    model="gpt-4",
    messages=[{"role": "user", "content": prompt}]
)
print("AI 生成的会议纪要：\n", summary["choices"][0]["message"]["content"])

import pandas as pd
import openai
import streamlit as st

st.title("AI Excel 分析助手")

uploaded_file = st.file_uploader("上传 Excel 文件", type=["xlsx"])
if uploaded_file:
    df = pd.read_excel(uploaded_file)
    st.write("数据预览:", df.head())

    question = st.text_input("输入问题:")
    if st.button("分析数据"):
        prompt = f"基于以下数据回答问题: {df.to_string()}\n问题: {question}"
        response = openai.ChatCompletion.create(
            model="gpt-4",
            messages=[{"role": "user", "content": prompt}]
        )
        st.write("AI 结果:", response["choices"][0]["message"]["content"])

from langchain.document_loaders import PyPDFLoader
from langchain.vectorstores import FAISS
from langchain.embeddings import OpenAIEmbeddings
from langchain.llms import OpenAI

# 1. 解析 PDF 并创建向量数据库
loader = PyPDFLoader("company_docs.pdf")
documents = loader.load()
vector_store = FAISS.from_documents(documents, OpenAIEmbeddings())

# 2. 用户查询
query = "公司最新的考勤制度是什么？"
retrieved_docs = vector_store.similarity_search(query)
print("相关文档内容：", retrieved_docs[0].page_content)

from pptx import Presentation
import openai

# 生成 PPT 大纲
topic = "市场营销计划"
prompt = f"为主题 '{topic}' 生成一个 5 页的 PPT 大纲"
response = openai.ChatCompletion.create(
    model="gpt-4",
    messages=[{"role": "user", "content": prompt}]
)
outline = response["choices"][0]["message"]["content"].split("\n")

# 创建 PPT
prs = Presentation()
for slide_title in outline:
    slide = prs.slides.add_slide(prs.slide_layouts[1])
    slide.shapes.title.text = slide_title

prs.save("AI_PPT.pptx")
print("PPT 生成完成！")