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Update src/streamlit_app.py
Browse files- src/streamlit_app.py +59 -43
src/streamlit_app.py
CHANGED
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@@ -3,26 +3,28 @@ import PyPDF2
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import pandas as pd
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import os
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import google.generativeai as genai
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import csv
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from datetime import datetime
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import logging
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import sys
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import io
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import tempfile
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import base64
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#
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler("pdf_processing.log"),
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logging.StreamHandler(sys.stdout)
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]
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)
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logger = logging.getLogger(__name__)
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#
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st.set_page_config(
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page_title="PDF處理與Gemini翻譯工具",
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page_icon="📄",
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@@ -30,46 +32,54 @@ st.set_page_config(
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initial_sidebar_state="expanded"
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)
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#
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st.title("📄 PDF處理與Gemini翻譯工具")
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st.markdown("上傳PDF檔案,選擇要處理的頁面,讓Gemini解釋內容並翻譯成繁體中文。")
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#
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with st.sidebar:
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st.header("設定")
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# API
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api_key = st.text_input(
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"Gemini API金鑰",
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value="
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type="password"
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)
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#
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uploaded_file = st.file_uploader("上傳PDF檔案", type=["pdf"])
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#
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with st.expander("處理選項", expanded=True):
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#
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if 'total_pages' not in st.session_state:
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st.session_state.total_pages = 0
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if 'page_content' not in st.session_state:
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st.session_state.page_content = {}
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#
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if uploaded_file is not None:
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#
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try:
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-
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st.session_state.total_pages = len(pdf_reader.pages)
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#
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if len(st.session_state.page_content) == 0:
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with st.spinner("正在加載PDF..."):
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for i in range(st.session_state.total_pages):
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st.session_state.page_content[i+1] = pdf_reader.pages[i].extract_text()
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#
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page_to_process = st.slider(
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"選擇要處理的頁面",
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min_value=1,
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@@ -79,31 +89,31 @@ with st.sidebar:
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st.info(f"PDF共有 {st.session_state.total_pages} 頁")
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except Exception as e:
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st.error(f"無法讀取PDF: {str(e)}")
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else:
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st.info("請先上傳PDF檔案")
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page_to_process = 1
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#
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with st.expander("進階選項"):
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#
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instruction = st.text_area(
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"給Gemini的指示詞",
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value="請詳細解釋以下內容的主要要點和重要信息",
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height=100
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)
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#
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output_filename = st.text_input(
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"輸出CSV檔名",
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value="gemini_translated_results.csv"
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)
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#
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def setup_gemini_api(api_key):
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"""設置Gemini API"""
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try:
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os.environ["GOOGLE_API_KEY"] = api_key
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genai.configure(api_key=api_key)
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return genai.GenerativeModel("gemini-1.5-flash")
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except Exception as e:
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@@ -145,12 +155,12 @@ def get_csv_download_link(df, filename="data.csv"):
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href = f'<a href="data:file/csv;base64,{b64}" download="{filename}">下載 CSV 檔案</a>'
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return href
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#
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if uploaded_file is not None:
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st.header("頁面內容預覽")
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#
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if page_to_process in st.session_state.page_content:
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page_text = st.session_state.page_content[page_to_process]
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st.text_area(
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@@ -162,40 +172,40 @@ if uploaded_file is not None:
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else:
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st.warning("無法獲取選定頁面的內容")
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#
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process_button = st.button("處理並翻譯", type="primary", use_container_width=True)
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#
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if process_button:
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if not api_key:
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st.error("請輸入Gemini API金鑰!")
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else:
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#
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progress_placeholder = st.empty()
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results_placeholder = st.empty()
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with st.spinner("正在處理中..."):
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progress_bar = progress_placeholder.progress(0)
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#
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model = setup_gemini_api(api_key)
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if model:
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progress_bar.progress(20)
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#
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page_text = st.session_state.page_content[page_to_process]
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progress_placeholder.text("正在使用Gemini解釋內容...")
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explanation = process_with_gemini(model, page_text, instruction)
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progress_bar.progress(60)
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progress_placeholder.text("正在翻譯成繁體中文...")
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translation = translate_with_gemini(model, explanation)
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progress_bar.progress(90)
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#
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results_data = {
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"時間戳記": [datetime.now().isoformat()],
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"原始內容": [page_text[:5000] + "..." if len(page_text) > 5000 else page_text],
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}
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results_df = pd.DataFrame(results_data)
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progress_bar.progress(100)
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progress_placeholder.empty()
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st.success("處理完成!")
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#
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tab1, tab2, tab3 = st.tabs(["Gemini解釋", "繁體中文翻譯", "CSV資料"])
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with tab1:
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st.markdown(get_csv_download_link(results_df, output_filename), unsafe_allow_html=True)
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st.info(f"CSV檔案已準備好下載。檔名: {output_filename}")
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else:
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st.info("👈 請從側邊欄上傳PDF檔案開始")
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#
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with st.expander("使用說明", expanded=True):
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st.markdown("""
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### 如何使用這個工具:
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1. **上傳PDF檔案** - 從側邊欄選擇並上傳PDF檔案
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2. **選擇頁面** - 使用滑桿選擇要處理的頁面
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3. **設定API金鑰** - 輸入您的Gemini API
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4. **自訂指示詞** - 可選擇修改給Gemini的指示詞
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5. **處理與翻譯** - 點擊"處理並翻譯"按鈕
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6. **查看結果** - 在選項卡中查看Gemini的解釋和繁體中文翻譯
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- 結果以CSV格式���存
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""")
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st.markdown("---")
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st.markdown("📄 PDF處理與Gemini翻譯工具 | 由Streamlit和Google Gemini AI提供技術支持")
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import pandas as pd
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import os
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import google.generativeai as genai
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from datetime import datetime
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import logging
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import sys
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import base64
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import tempfile
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# Create logs directory in a writable location
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log_dir = "/tmp/logs"
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os.makedirs(log_dir, exist_ok=True)
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler(os.path.join(log_dir, "pdf_processing.log")),
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logging.StreamHandler(sys.stdout)
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]
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)
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logger = logging.getLogger(__name__)
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# Page configuration
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st.set_page_config(
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page_title="PDF處理與Gemini翻譯工具",
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page_icon="📄",
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initial_sidebar_state="expanded"
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)
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# App title and introduction
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st.title("📄 PDF處理與Gemini翻譯工具")
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st.markdown("上傳PDF檔案,選擇要處理的頁面,讓Gemini解釋內容並翻譯成繁體中文。")
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# Sidebar - Settings area
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with st.sidebar:
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st.header("設定")
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# API key input - Using st.secrets is more secure but requires setup
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api_key = st.text_input(
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"Gemini API金鑰",
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value="", # Remove hardcoded API key
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type="password"
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)
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# Upload PDF file
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uploaded_file = st.file_uploader("上傳PDF檔案", type=["pdf"])
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# Processing options block
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with st.expander("處理選項", expanded=True):
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# Initialize session_state
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if 'total_pages' not in st.session_state:
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st.session_state.total_pages = 0
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if 'page_content' not in st.session_state:
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st.session_state.page_content = {}
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# Page selection (only shown after file upload)
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if uploaded_file is not None:
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# Read PDF and get page count
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try:
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# Create a temporary file to avoid potential security issues with direct file uploads
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with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as tmp_file:
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tmp_file.write(uploaded_file.getvalue())
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tmp_path = tmp_file.name
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pdf_reader = PyPDF2.PdfReader(tmp_path)
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st.session_state.total_pages = len(pdf_reader.pages)
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# Load PDF content to session_state (if not already loaded)
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if len(st.session_state.page_content) == 0:
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with st.spinner("正在加載PDF..."):
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for i in range(st.session_state.total_pages):
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st.session_state.page_content[i+1] = pdf_reader.pages[i].extract_text()
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# Remove the temporary file
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os.unlink(tmp_path)
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# Page selection slider
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page_to_process = st.slider(
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"選擇要處理的頁面",
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min_value=1,
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st.info(f"PDF共有 {st.session_state.total_pages} 頁")
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except Exception as e:
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logger.error(f"無法讀取PDF: {str(e)}")
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st.error(f"無法讀取PDF: {str(e)}")
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else:
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st.info("請先上傳PDF檔案")
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page_to_process = 1
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# Advanced options
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with st.expander("進階選項"):
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# Instructions for Gemini
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instruction = st.text_area(
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"給Gemini的指示詞",
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value="請詳細解釋以下內容的主要要點和重要信息",
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height=100
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)
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# Output filename
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output_filename = st.text_input(
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"輸出CSV檔名",
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value="gemini_translated_results.csv"
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)
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# Main function definitions
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def setup_gemini_api(api_key):
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"""設置Gemini API"""
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try:
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genai.configure(api_key=api_key)
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return genai.GenerativeModel("gemini-1.5-flash")
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except Exception as e:
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href = f'<a href="data:file/csv;base64,{b64}" download="{filename}">下載 CSV 檔案</a>'
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return href
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# Main content area
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if uploaded_file is not None:
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# Display page content preview
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st.header("頁面內容預覽")
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# Get selected page content from session_state
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if page_to_process in st.session_state.page_content:
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page_text = st.session_state.page_content[page_to_process]
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st.text_area(
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else:
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st.warning("無法獲取選定頁面的內容")
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# Process button
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process_button = st.button("處理並翻譯", type="primary", use_container_width=True)
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# When process button is clicked
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if process_button:
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if not api_key:
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st.error("請輸入Gemini API金鑰!")
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else:
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# Set up progress display
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progress_placeholder = st.empty()
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results_placeholder = st.empty()
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with st.spinner("正在處理中..."):
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progress_bar = progress_placeholder.progress(0)
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# Set up API
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model = setup_gemini_api(api_key)
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if model:
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progress_bar.progress(20)
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# Get selected page content
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page_text = st.session_state.page_content[page_to_process]
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# Process with Gemini
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progress_placeholder.text("正在使用Gemini解釋內容...")
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explanation = process_with_gemini(model, page_text, instruction)
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progress_bar.progress(60)
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# Translate to Traditional Chinese
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progress_placeholder.text("正在翻譯成繁體中文...")
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translation = translate_with_gemini(model, explanation)
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progress_bar.progress(90)
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# Create results DataFrame
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results_data = {
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"時間戳記": [datetime.now().isoformat()],
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"原始內容": [page_text[:5000] + "..." if len(page_text) > 5000 else page_text],
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}
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results_df = pd.DataFrame(results_data)
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# Save as CSV to a writable location
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csv_path = os.path.join("/tmp", output_filename)
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try:
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results_df.to_csv(csv_path, index=False, encoding="utf-8-sig")
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logger.info(f"CSV saved to {csv_path}")
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except Exception as e:
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logger.error(f"Failed to save CSV: {e}")
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st.error(f"無法保存CSV: {str(e)}")
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# Complete
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progress_bar.progress(100)
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progress_placeholder.empty()
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# Display results
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st.success("處理完成!")
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# Create tabs to display results
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tab1, tab2, tab3 = st.tabs(["Gemini解釋", "繁體中文翻譯", "CSV資料"])
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with tab1:
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st.markdown(get_csv_download_link(results_df, output_filename), unsafe_allow_html=True)
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st.info(f"CSV檔案已準備好下載。檔名: {output_filename}")
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else:
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# Content to display when no file is uploaded
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st.info("👈 請從側邊欄上傳PDF檔案開始")
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# Display usage instructions
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with st.expander("使用說明", expanded=True):
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st.markdown("""
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### 如何使用這個工具:
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1. **上傳PDF檔案** - 從側邊欄選擇並上傳PDF檔案
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| 259 |
2. **選擇頁面** - 使用滑桿選擇要處理的頁面
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| 260 |
+
3. **設定API金鑰** - 輸入您的Gemini API金鑰
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| 261 |
4. **自訂指示詞** - 可選擇修改給Gemini的指示詞
|
| 262 |
5. **處理與翻譯** - 點擊"處理並翻譯"按鈕
|
| 263 |
6. **查看結果** - 在選項卡中查看Gemini的解釋和繁體中文翻譯
|
|
|
|
| 271 |
- 結果以CSV格式���存
|
| 272 |
""")
|
| 273 |
|
| 274 |
+
# Footer
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| 275 |
st.markdown("---")
|
| 276 |
st.markdown("📄 PDF處理與Gemini翻譯工具 | 由Streamlit和Google Gemini AI提供技術支持")
|