import streamlit as st
import PyPDF2
import pandas as pd
import os
import google.generativeai as genai
from datetime import datetime
import logging
import sys
import base64
import tempfile

# Create logs directory in a writable location
log_dir = "/tmp/logs"
os.makedirs(log_dir, exist_ok=True)

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler(os.path.join(log_dir, "pdf_processing.log")),
        logging.StreamHandler(sys.stdout)
    ]
)
logger = logging.getLogger(__name__)

# Page configuration
st.set_page_config(
    page_title="PDF處理與Gemini翻譯工具",
    page_icon="📄",
    layout="wide",
    initial_sidebar_state="expanded"
)

# App title and introduction
st.title("📄 PDF處理與Gemini翻譯工具")
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。")

# Sidebar - Settings area
with st.sidebar:
    st.header("設定")
    
    # API key input - Using st.secrets is more secure but requires setup
    api_key = st.text_input(
        "Gemini API金鑰",
        value="",  # Remove hardcoded API key
        type="password"
    )
    
    # Upload PDF file
    uploaded_file = st.file_uploader("上傳PDF檔案", type=["pdf"])
    
    # Processing options block
    with st.expander("處理選項", expanded=True):
        # Initialize session_state
        if 'total_pages' not in st.session_state:
            st.session_state.total_pages = 0
        if 'page_content' not in st.session_state:
            st.session_state.page_content = {}
            
        # Page selection (only shown after file upload)
        if uploaded_file is not None:
            # Read PDF and get page count
            try:
                # Create a temporary file to avoid potential security issues with direct file uploads
                with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as tmp_file:
                    tmp_file.write(uploaded_file.getvalue())
                    tmp_path = tmp_file.name
                
                pdf_reader = PyPDF2.PdfReader(tmp_path)
                st.session_state.total_pages = len(pdf_reader.pages)
                
                # Load PDF content to session_state (if not already loaded)
                if len(st.session_state.page_content) == 0:
                    with st.spinner("正在加載PDF..."):
                        for i in range(st.session_state.total_pages):
                            st.session_state.page_content[i+1] = pdf_reader.pages[i].extract_text()
                
                # Remove the temporary file
                os.unlink(tmp_path)
                
                # Page selection slider
                page_to_process = st.slider(
                    "選擇要處理的頁面",
                    min_value=1,
                    max_value=st.session_state.total_pages,
                    value=1
                )
                
                st.info(f"PDF共有 {st.session_state.total_pages} 頁")
            except Exception as e:
                logger.error(f"無法讀取PDF: {str(e)}")
                st.error(f"無法讀取PDF: {str(e)}")
        else:
            st.info("請先上傳PDF檔案")
            page_to_process = 1
    
    # Advanced options
    with st.expander("進階選項"):
        # Instructions for Gemini
        instruction = st.text_area(
            "給Gemini的指示詞",
            value="請詳細解釋以下內容的主要要點和重要信息",
            height=100
        )
        
        # Output filename
        output_filename = st.text_input(
            "輸出CSV檔名",
            value="gemini_translated_results.csv"
        )

# Main function definitions
def setup_gemini_api(api_key):
    """設置Gemini API"""
    try:
        genai.configure(api_key=api_key)
        return genai.GenerativeModel("gemini-1.5-flash")
    except Exception as e:
        logger.error(f"Gemini API設置失敗: {e}")
        st.error(f"API設置失敗: {str(e)}")
        return None

def process_with_gemini(model, text, instruction):
    """使用Gemini處理文本"""
    try:
        prompt = f"{instruction}:\n\n{text}"
        response = model.generate_content(prompt)
        return response.text.strip()
    except Exception as e:
        logger.error(f"Gemini處理失敗: {e}")
        return f"處理失敗: {str(e)}"

def translate_with_gemini(model, text):
    """使用Gemini將文本翻譯成繁體中文"""
    try:
        prompt = f"""
        請將以下文本翻譯成繁體中文，保持專業和準確性：
        
        {text}
        
        只需要返回翻譯後的文本，不要加入其他解釋或備註。
        """
        
        response = model.generate_content(prompt)
        return response.text.strip()
    except Exception as e:
        logger.error(f"Gemini翻譯失敗: {e}")
        return f"翻譯失敗: {str(e)}"

def get_csv_download_link(df, filename="data.csv"):
    """生成CSV檔案下載連結"""
    csv = df.to_csv(index=False)
    b64 = base64.b64encode(csv.encode()).decode()
    href = f'<a href="data:file/csv;base64,{b64}" download="{filename}">下載 CSV 檔案</a>'
    return href

# Main content area
if uploaded_file is not None:
    # Display page content preview
    st.header("頁面內容預覽")
    
    # Get selected page content from session_state
    if page_to_process in st.session_state.page_content:
        page_text = st.session_state.page_content[page_to_process]
        st.text_area(
            f"第 {page_to_process} 頁內容",
            value=page_text,
            height=150,
            disabled=True
        )
    else:
        st.warning("無法獲取選定頁面的內容")
    
    # Process button
    process_button = st.button("處理並翻譯", type="primary", use_container_width=True)
    
    # When process button is clicked
    if process_button:
        if not api_key:
            st.error("請輸入Gemini API金鑰!")
        else:
            # Set up progress display
            progress_placeholder = st.empty()
            results_placeholder = st.empty()
            
            with st.spinner("正在處理中..."):
                progress_bar = progress_placeholder.progress(0)
                
                # Set up API
                model = setup_gemini_api(api_key)
                if model:
                    progress_bar.progress(20)
                    
                    # Get selected page content
                    page_text = st.session_state.page_content[page_to_process]
                    
                    # Process with Gemini
                    progress_placeholder.text("正在使用Gemini解釋內容...")
                    explanation = process_with_gemini(model, page_text, instruction)
                    progress_bar.progress(60)
                    
                    # Translate to Traditional Chinese
                    progress_placeholder.text("正在翻譯成繁體中文...")
                    translation = translate_with_gemini(model, explanation)
                    progress_bar.progress(90)
                    
                    # Create results DataFrame
                    results_data = {
                        "時間戳記": [datetime.now().isoformat()],
                        "原始內容": [page_text[:5000] + "..." if len(page_text) > 5000 else page_text],
                        "Gemini解釋": [explanation],
                        "繁體中文翻譯": [translation]
                    }
                    results_df = pd.DataFrame(results_data)
                    
                    # Save as CSV to a writable location
                    csv_path = os.path.join("/tmp", output_filename)
                    try:
                        results_df.to_csv(csv_path, index=False, encoding="utf-8-sig")
                        logger.info(f"CSV saved to {csv_path}")
                    except Exception as e:
                        logger.error(f"Failed to save CSV: {e}")
                        st.error(f"無法保存CSV: {str(e)}")
                    
                    # Complete
                    progress_bar.progress(100)
                    progress_placeholder.empty()
                    
                    # Display results
                    st.success("處理完成!")
                    
                    # Create tabs to display results
                    tab1, tab2, tab3 = st.tabs(["Gemini解釋", "繁體中文翻譯", "CSV資料"])
                    
                    with tab1:
                        st.subheader("Gemini解釋結果")
                        st.write(explanation)
                    
                    with tab2:
                        st.subheader("繁體中文翻譯")
                        st.write(translation)
                    
                    with tab3:
                        st.subheader("CSV資料預覽")
                        st.dataframe(results_df)
                        st.markdown(get_csv_download_link(results_df, output_filename), unsafe_allow_html=True)
                        st.info(f"CSV檔案已準備好下載。檔名: {output_filename}")
else:
    # Content to display when no file is uploaded
    st.info("👈 請從側邊欄上傳PDF檔案開始")
    
    # Display usage instructions
    with st.expander("使用說明", expanded=True):
        st.markdown("""
        ### 如何使用這個工具:
        
        1. **上傳PDF檔案** - 從側邊欄選擇並上傳PDF檔案
        2. **選擇頁面** - 使用滑桿選擇要處理的頁面
        3. **設定API金鑰** - 輸入您的Gemini API金鑰
        4. **自訂指示詞** - 可選擇修改給Gemini的指示詞
        5. **處理與翻譯** - 點擊"處理並翻譯"按鈕
        6. **查看結果** - 在選項卡中查看Gemini的解釋和繁體中文翻譯
        7. **下載結果** - 下載CSV格式的結果檔案
        
        ### 功能特點:
        
        - 逐頁預覽PDF內容
        - 使用Gemini AI解釋文本
        - 自動翻譯成繁體中文
        - 結果以CSV格式儲存
        """)

# Footer
st.markdown("---")
st.markdown("📄 PDF處理與Gemini翻譯工具 | 由Streamlit和Google Gemini AI提供技術支持")