# app.py import streamlit as st from textsumm import 摘要 from pdfsum import 提取_pdf摘要 import requests st.set_page_config(page_title="PDF 工具箱", page_icon="📄", layout="wide") # 側邊欄 st.sidebar.title("📄 PDF 工具箱") st.sidebar.write("請輸入 OpenAI API 金鑰(非必填)") api_key = st.sidebar.text_input("sk-...", type="password") # GPT 模型選擇 model = st.sidebar.radio("選擇 GPT 模型", options=["gpt-4", "gpt-4.0", "gpt-4.1", "gpt-4.5"], index=0) # 工具選擇 tool = st.sidebar.radio("選擇功能", options=["文字摘要", "PDF 摘要", "論文搜尋"]) st.title("PDF 工具箱") if tool == "文字摘要": st.header("📝 文字摘要") user_text = st.text_area("請輸入要摘要的中文內容") if st.button("生成摘要"): with st.spinner("摘要生成中..."): if user_text.strip(): summary = 摘要(user_text.strip()) st.success("摘要結果:") st.write(summary) else: st.warning("請輸入內容!") elif tool == "PDF 摘要": st.header("📄 PDF 摘要") uploaded_file = st.file_uploader("上傳你的 PDF 文件", type=["pdf"]) if uploaded_file is not None and st.button("產生 PDF 摘要"): with st.spinner("摘要生成中..."): summary = 提取_pdf摘要(uploaded_file, 摘要) st.success("摘要結果:") st.write(summary) elif tool == "論文搜尋": st.header("🔎 論文搜尋(arXiv)") keyword = st.text_input("輸入主題或關鍵字", "量子") max_results = st.slider("結果數量", 1, 20, 5) start_year = st.number_input("起始年份", min_value=1990, max_value=2025, value=2019) end_year = st.number_input("結束年份", min_value=1990, max_value=2025, value=2025) if st.button("搜尋論文"): st.info("搜尋中...") url = f"http://export.arxiv.org/api/query?search_query=all:{keyword}&start=0&max_results={max_results}" resp = requests.get(url) if resp.ok: import xml.etree.ElementTree as ET root = ET.fromstring(resp.content) found = False for entry in root.findall("{http://www.w3.org/2005/Atom}entry"): published = entry.find("{http://www.w3.org/2005/Atom}published").text[:4] if start_year <= int(published) <= end_year: found = True title = entry.find("{http://www.w3.org/2005/Atom}title").text.strip() link = entry.find("{http://www.w3.org/2005/Atom}id").text.strip() st.markdown(f"**[{title}]({link})**({published})") if not found: st.warning("在所選年份範圍內沒有找到相關論文。") else: st.error("arXiv 查詢失敗")