# app.py
"""PROBIN - Intelligent Document Analysis System"""
import streamlit as st
import os
import sys
import uuid
from pathlib import Path
from streamlit_pdf_viewer import pdf_viewer

# 프로젝트 루트 경로 추가
sys.path.insert(0, str(Path(__file__).parent))

from core.pdf_loader import load_pdf
from core.chunker import chunk_text
from core.embedder import embed_chunks
from core.vectordb import VectorDB
from core.retriever import Retriever
from core.generator import Generator
from ui.styles import get_custom_css
from ui.components import render_sources_with_relevance
from utils.pdf_utils import get_text_coordinates
from config.settings import (
    CHUNK_SIZE, CHUNK_OVERLAP, TOP_K,
    APP_NAME, APP_SUBTITLE, APP_ICON, SHOW_STATS, PDF_HEIGHT
)

# 1. 페이지 설정
st.set_page_config(
    page_title=f"{APP_NAME} - {APP_SUBTITLE}",
    page_icon=APP_ICON,
    layout="wide",
    initial_sidebar_state="collapsed"
)

# 2. 세션 스테이트 초기화
if "session_id" not in st.session_state:
    st.session_state.session_id = str(uuid.uuid4())[:8]
    print(f"🆔 새 세션 ID 생성: {st.session_state.session_id}")

if "vectordb" not in st.session_state:
    st.session_state.vectordb = None
if "retriever" not in st.session_state:
    st.session_state.retriever = None
if "generator" not in st.session_state:
    st.session_state.generator = Generator()
if "pdf_processed" not in st.session_state:
    st.session_state.pdf_processed = False
if "messages" not in st.session_state:
    st.session_state.messages = []
if "current_page" not in st.session_state:
    st.session_state.current_page = 1
if "pdf_path" not in st.session_state:
    st.session_state.pdf_path = None
if "pdf_bytes" not in st.session_state:
    st.session_state.pdf_bytes = None
if "annotations" not in st.session_state:
    st.session_state.annotations = []
if "zoom_level" not in st.session_state:
    st.session_state.zoom_level = 500

# 3. CSS 적용
st.markdown(get_custom_css(), unsafe_allow_html=True)

# --------------------------------------------------------------------------
# 함수 정의
# --------------------------------------------------------------------------

def render_welcome_screen():
    """웰컴 화면 (PDF 업로드 전에만 표시)"""
    if not st.session_state.pdf_processed:
        st.markdown(
            f"""
            <div id="welcome" class="hero-container">
                <h1 class="hero-title">{APP_ICON} {APP_NAME}</h1>
                <p class="hero-subtitle">Experience Intelligent Document Analysis with AI</p>
            </div>
            """,
            unsafe_allow_html=True
        )


def move_to_page(page_num, text_content):
    """페이지 이동 및 하이라이트 (즉시 반영)"""
    st.session_state.current_page = page_num
    
    if st.session_state.pdf_path:
        highlights = get_text_coordinates(
            str(st.session_state.pdf_path), 
            page_num, 
            text_content
        )
        st.session_state.annotations = highlights
    
    # 즉시 페이지 이동 반영
    st.rerun()


def reset_app():
    """앱 완전 초기화"""
    print("\n🔄 앱 전체 초기화 시작...")
    
    # 1. 현재 컬렉션 삭제
    if st.session_state.vectordb is not None:
        try:
            print(f"   🗑️ 현재 컬렉션 삭제 (세션: {st.session_state.session_id})")
            st.session_state.vectordb.delete_collection()
            print("   ✅ 컬렉션 삭제 완료")
        except Exception as e:
            print(f"   ⚠️ 컬렉션 삭제 오류: {e}")
    
    # 2. 새 세션 ID 생성
    old_session_id = st.session_state.session_id
    new_session_id = str(uuid.uuid4())[:8]
    print(f"   🆔 세션 ID 변경: {old_session_id} → {new_session_id}")
    
    # 3. 세션 초기화
    keys_to_delete = list(st.session_state.keys())
    for key in keys_to_delete:
        del st.session_state[key]
    
    # 새 세션 ID 설정
    st.session_state.session_id = new_session_id
    st.session_state.pdf_processed = False
    st.session_state.pdf_path = None
    st.session_state.pdf_bytes = None
    
    print("   ✅ 세션 초기화 완료")
    print(f"🎉 초기화 완료! 새 세션: {new_session_id}\n")
    
    st.success("✅ 초기화 완료!")
    st.info("💡 **새 PDF를 업로드할 준비가 되었습니다!**")
    st.rerun()


def process_pdf(uploaded_file):
    """PDF 처리 파이프라인"""
    try:
        # 파일 저장
        save_dir = Path("./data/uploads")
        save_dir.mkdir(parents=True, exist_ok=True)
        pdf_path = save_dir / uploaded_file.name
        
        with open(pdf_path, "wb") as f:
            f.write(uploaded_file.getbuffer())
        
        st.session_state.pdf_path = pdf_path
        st.session_state.pdf_bytes = uploaded_file.getvalue()
        
        with st.spinner("🔄 문서를 분석하고 있습니다..."):
            # 1. PDF 로드
            print(f"\n📄 PDF 로드 중: {uploaded_file.name}")
            pdf_data = load_pdf(str(pdf_path))
            st.session_state.total_pages = pdf_data["total_pages"]
            print(f"   ✅ 총 {pdf_data['total_pages']} 페이지")
            
            # 2. 청킹
            print(f"\n✂️ 청킹 중...")
            chunks = chunk_text(pdf_data["pages"], CHUNK_SIZE, CHUNK_OVERLAP)
            st.session_state.total_chunks = len(chunks)
            print(f"   ✅ 총 {len(chunks)}개 청크 생성")
            
            # 3. 임베딩
            print(f"\n🔢 임베딩 생성 중...")
            embedded_chunks = embed_chunks(chunks)
            print(f"   ✅ 임베딩 완료")
            
            # 4. VectorDB 생성
            print(f"\n💾 VectorDB 초기화 (세션: {st.session_state.session_id})...")
            
            if st.session_state.vectordb is not None:
                print("   🗑️ 기존 컬렉션 삭제")
                try:
                    st.session_state.vectordb.delete_collection()
                except Exception as e:
                    print(f"   ⚠️ 삭제 오류: {e}")
            
            print("   🆕 새 VectorDB 생성")
            st.session_state.vectordb = VectorDB(
                session_id=st.session_state.session_id
            )
            
            initial_count = st.session_state.vectordb.count()
            print(f"   📊 초기 상태: {initial_count}개 청크")
            
            # 5. 청크 저장
            print(f"\n   💾 청크 저장: {len(embedded_chunks)}개")
            st.session_state.vectordb.add_chunks(embedded_chunks)
            
            # 6. Retriever 생성
            st.session_state.retriever = Retriever(st.session_state.vectordb)
            
            # 7. 상태 업데이트
            st.session_state.pdf_processed = True
            
            # 8. 최종 확인
            final_count = st.session_state.vectordb.count()
            print(f"\n✅ 최종: {final_count}개 청크 저장 완료")
            
            # 9. 초기화
            st.session_state.messages = []
            st.session_state.annotations = []
            st.session_state.current_page = 1
            
            print(f"\n🎉 PDF 처리 완료! (세션: {st.session_state.session_id})\n")
            st.success("✅ 문서 분석 완료!")
            st.rerun()
            
    except Exception as e:
        st.error(f"❌ 오류 발생: {str(e)}")
        print(f"\n❌ 오류:")
        import traceback
        print(traceback.format_exc())


# --------------------------------------------------------------------------
# 메인 UI
# --------------------------------------------------------------------------

# 웰컴 화면 출력
render_welcome_screen()

# --------------------------------------------------------------------------
# Sidebar
# --------------------------------------------------------------------------
with st.sidebar:
    st.title(f"{APP_ICON} {APP_NAME}")
    
    uploaded_file = st.file_uploader(
        "PDF 파일 업로드", 
        type=["pdf"], 
        key=f"pdf_uploader_{st.session_state.session_id}"
    )
    
    if uploaded_file and not st.session_state.pdf_processed:
        process_pdf(uploaded_file)
    
    st.divider()
    
    if st.button("🔄 초기화", use_container_width=True):
        reset_app()

# --------------------------------------------------------------------------
# PDF + Chat UI
# --------------------------------------------------------------------------
if st.session_state.pdf_processed:
    
    col1, col2 = st.columns([5, 5], gap="medium")
    
    # 왼쪽: PDF 뷰어
    with col1:
        # 툴바
        toolbar1, toolbar2, toolbar3, toolbar4 = st.columns([1, 1, 2, 2])
        
        with toolbar1:
            if st.button("◀", help="이전 페이지"):
                if st.session_state.current_page > 1:
                    st.session_state.current_page -= 1
                    st.rerun()
        
        with toolbar2:
            if st.button("▶", help="다음 페이지"):
                if st.session_state.current_page < st.session_state.total_pages:
                    st.session_state.current_page += 1
                    st.rerun()
        
        with toolbar3:
            st.write(f"Page {st.session_state.current_page} / {st.session_state.total_pages}")
        
        with toolbar4:
            new_zoom = st.slider("Zoom", 500, 1200, st.session_state.zoom_level, label_visibility="collapsed")
            if new_zoom != st.session_state.zoom_level:
                st.session_state.zoom_level = new_zoom
                st.rerun()
        
        # PDF 뷰어
        pdf_viewer(
            input=st.session_state.pdf_bytes,
            width=st.session_state.zoom_level,
            annotations=st.session_state.annotations,
            pages_to_render=[st.session_state.current_page],
            render_text=True
        )
    
    # 오른쪽: 채팅
    with col2:
        st.markdown("### 💬 PROBIN CHAT")
        
        # 채팅 컨테이너 (스크롤 가능 - 높이 줄임)
        chat_container = st.container(height=500)
        with chat_container:
            # 채팅 기록이 없을 때 가이드 표시
            if not st.session_state.messages:
                st.markdown("""
                <div class="chat-placeholder">
                    <div class="placeholder-title">👋 반가워요! 이렇게 활용해보세요</div>
                    <ol class="placeholder-steps">
                        <li>AI가 문서 내용을 분석하여 <strong>답변과 근거</strong>를 찾아줍니다.</li>
                        <li>답변의 <span class="highlight-box">노란색 하이라이트</span>를 확인하세요.</li>
                    </ol>
                </div>
                """, unsafe_allow_html=True)
                
            # 채팅 기록 표시
            else:
                for idx, msg in enumerate(st.session_state.messages):
                    with st.chat_message(msg["role"]):
                        st.markdown(msg["content"])
                        
                        if msg.get("sources"):
                            render_sources_with_relevance(
                                sources=msg["sources"],
                                message_idx=idx,
                                move_to_page_callback=move_to_page
                            )
        
        # 채팅 입력
        if query := st.chat_input("질문을 입력하세요..."):
            # 사용자 메시지 추가
            st.session_state.messages.append({
                "role": "user",
                "content": query
            })
            
            # 검색 및 답변 생성
            with st.spinner("🔍 PROBIN이 검색중입니다..."):
                print(f"\n🔍 질문: {query}")
                
                retrieved_chunks = st.session_state.retriever.retrieve(query, TOP_K)
                result = st.session_state.generator.generate_answer(query, retrieved_chunks)
                
                # AI 답변 추가
                st.session_state.messages.append({
                    "role": "assistant",
                    "content": result["answer"],
                    "sources": result["sources"]
                })
                
                # 첫 번째 출처로 이동
                if result["sources"]:
                    top_source = result["sources"][0]
                    highlights = get_text_coordinates(
                        str(st.session_state.pdf_path),
                        top_source["page_num"],
                        top_source["text"]
                    )
                    st.session_state.annotations = highlights
                    st.session_state.current_page = top_source["page_num"]
                
                print(f"✅ 답변 완료\n")
            
            st.rerun()