"""율봇 WebUI — youlbot REST API를 호출하는 Gradio 프론트엔드.

실행:
    python app.py

환경변수 (.env):
    YOULBOT_API_URL=http://localhost:8000
    YOULBOT_API_TOKEN=           ← api.py에 API_TOKEN 설정 시 동일 값
"""
import asyncio
import html as _html
import os
import platform
import subprocess
import tempfile

import gradio as gr
from dotenv import load_dotenv

load_dotenv()

import api_client

USER_LABELS = ["아록", "근혜", "도율", "하율"]
DEFAULT_USER = "아록"

# ── STT (Whisper) — 로컬 실행 유지 ──────────────────────────────
_whisper_model = None
_WHISPER_SIZE = os.getenv("WHISPER_MODEL_SIZE", "small")
_TTS_VOICE = os.getenv("TTS_VOICE", "Yuna")                        # macOS say 보이스
_TTS_EDGE_VOICE = os.getenv("TTS_EDGE_VOICE", "ko-KR-SunHiNeural") # edge-tts 보이스


def _get_whisper():
    global _whisper_model
    if _whisper_model is None:
        import whisper
        _whisper_model = whisper.load_model(_WHISPER_SIZE)
    return _whisper_model


def transcribe_audio(filepath: str) -> str:
    if not filepath:
        return ""
    model = _get_whisper()
    result = model.transcribe(filepath, language="ko")
    return result["text"].strip()


async def tts_speak(text: str) -> str | None:
    """크로스플랫폼 TTS. macOS: say→edge-tts→pyttsx3 / Windows: edge-tts→pyttsx3"""
    if not text:
        return None

    # macOS: say 우선 (오프라인, 내장 한국어)
    if platform.system() == "Darwin":
        try:
            tmp = tempfile.NamedTemporaryFile(suffix=".aiff", delete=False)
            tmp.close()
            await asyncio.to_thread(
                subprocess.run,
                ["say", "-v", _TTS_VOICE, "-o", tmp.name, text],
                check=True,
                capture_output=True,
            )
            return tmp.name
        except Exception:
            pass

    # Windows 1순위 / macOS say 실패 시: edge-tts (온라인)
    try:
        import edge_tts
        tmp = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False)
        tmp.close()
        await edge_tts.Communicate(text, _TTS_EDGE_VOICE).save(tmp.name)
        return tmp.name
    except Exception:
        pass

    # 최종 폴백: pyttsx3 (오프라인)
    try:
        import pyttsx3
        tmp = tempfile.NamedTemporaryFile(suffix=".wav", delete=False)
        tmp.close()
        def _save():
            engine = pyttsx3.init()
            engine.save_to_file(text, tmp.name)
            engine.runAndWait()
        await asyncio.to_thread(_save)
        return tmp.name
    except Exception:
        return None


# ── 채팅 ─────────────────────────────────────────────────────────

async def respond(message, history, show_thinking, user_id, use_tts, run_ids):
    if not message.strip():
        yield history, "", None, run_ids, ""
        return

    history = list(history)
    run_ids = list(run_ids)
    history.append({"role": "user", "content": message})
    history.append({"role": "assistant", "content": ""})
    yield history, "", None, run_ids, ""  # thinking_box 초기화

    collected_run_id: str | None = None
    tts_text = ""            # 순수 답변만 누적 (TTS용)
    thinking_acc = ""        # 사고 과정 + 진행 로그 누적
    thinking_finalized = False  # 첫 답변 토큰 도착 시 박스 완료 처리

    try:
        async for token, run_id in api_client.chat(message, user_id, show_thinking):
            if run_id is not None:
                collected_run_id = run_id
                break

            # 사고 과정(LLM thinking) — 박스에 추가
            if isinstance(token, dict) and "__thinking" in token:
                thinking_acc += token["__thinking"]
                yield history, "", None, run_ids, _thinking_html(thinking_acc)
                continue

            # 진행 로그(LangGraph, 검색 등) — 박스에 추가 (챗봇에는 표시 안 함)
            if isinstance(token, dict) and "__meta" in token:
                thinking_acc += token["__meta"]
                yield history, "", None, run_ids, _thinking_html(thinking_acc)
                continue

            # 첫 답변 토큰 도착 — 박스를 완료 상태로 전환
            if thinking_acc and not thinking_finalized:
                thinking_finalized = True
                yield history, "", None, run_ids, _thinking_html(thinking_acc, done=True)

            tts_text += token
            history[-1]["content"] += token
            yield history, "", None, run_ids, gr.update()  # thinking_box 유지

    except Exception as e:
        history[-1]["content"] += f"\n\n[오류: {e}]"
        yield history, "", None, run_ids, gr.update()
        return

    run_ids.append(collected_run_id)

    if use_tts:
        audio_path = await tts_speak(tts_text)
        yield history, "", audio_path, run_ids, gr.update()
    else:
        yield history, "", None, run_ids, gr.update()


def handle_feedback(like_data: gr.LikeData, history, run_ids, user_id):
    idx = like_data.index
    if isinstance(idx, (list, tuple)):
        idx = idx[0]
    if not isinstance(idx, int) or idx < 0 or idx >= len(history):
        return
    if history[idx].get("role") != "assistant":
        return
    # idx 위치까지 등장한 assistant 메시지 수 = 이 메시지의 0-based 턴 번호
    asst_turn = sum(1 for m in history[:idx] if m.get("role") == "assistant")
    run_id = run_ids[asst_turn] if run_ids and asst_turn < len(run_ids) else None

    user_msg = str(history[idx - 1]["content"]) if idx > 0 else ""
    asst_msg = str(history[idx]["content"])
    rating = 1 if like_data.liked else -1

    try:
        asyncio.run(api_client.save_feedback(user_id, user_msg, asst_msg, rating, run_id))
    except Exception as e:
        print(f"[Feedback] 저장 실패: {e}")


def switch_user(user_id):
    return [], []


def reset_chat(user_id):
    try:
        asyncio.run(api_client.reset(user_id))
    except Exception as e:
        print(f"[Reset] 실패: {e}")
    return [], []


# ── 문서 관리 ─────────────────────────────────────────────────────

def ingest_files(files):
    if not files:
        return "파일을 선택해주세요."
    paths = [f if isinstance(f, str) else f.name for f in files]
    results = []
    for path in paths:
        try:
            result = asyncio.run(api_client.ingest(path))
            name = os.path.basename(path)
            results.append(f"{name} → {result.get('chunks', '?')}개 청크")
        except Exception as e:
            results.append(f"{os.path.basename(path)} 오류: {e}")
    return "\n".join(results)


def list_docs():
    try:
        sources = asyncio.run(api_client.list_documents())
        return [[os.path.basename(s), s] for s in sources]
    except Exception as e:
        return [[f"오류: {e}", ""]]


def delete_doc(source):
    if not source.strip():
        return "삭제할 파일 경로를 입력하세요.", list_docs()
    try:
        asyncio.run(api_client.delete_document(source.strip()))
        return f"삭제 완료: {os.path.basename(source.strip())}", list_docs()
    except Exception as e:
        return f"오류: {e}", list_docs()


# ── UI 구성 ──────────────────────────────────────────────────────

_THINKING_STYLE = (
    "background:#f9f9f9;border-left:3px solid #bbb;border-radius:6px;"
    "padding:10px 14px;max-height:220px;overflow-y:auto;"
    "font-size:0.85em;color:#555;white-space:pre-wrap;margin-bottom:6px;"
)


def _thinking_html(text: str, done: bool = False) -> str:
    icon = "💭" if done else "🤔"
    label = "분석 완료" if done else "분석 중..."
    cursor = "" if done else " ▌"
    return (
        f'<div style="{_THINKING_STYLE}">'
        f"<strong>{icon} {label}</strong><br><br>"
        f"{_html.escape(text)}{cursor}</div>"
    )


with gr.Blocks(title="율봇") as demo:
    gr.Markdown("# 율봇\n육아·금융 전문 AI 상담 도우미")

    user_state = gr.State(DEFAULT_USER)
    run_ids_state = gr.State([])

    with gr.Tab("대화"):
        with gr.Row():
            user_selector = gr.Dropdown(
                choices=USER_LABELS,
                value=DEFAULT_USER,
                label="사용자",
                scale=1,
            )

        thinking_box = gr.HTML(value="")
        chatbot = gr.Chatbot(label="율봇", height=500)
        with gr.Row():
            msg_box = gr.Textbox(
                placeholder="질문을 입력하세요... (Enter로 전송)",
                label="",
                scale=5,
                autofocus=True,
            )
            send_btn = gr.Button("전송", variant="primary", scale=1)

        with gr.Row():
            audio_input = gr.Audio(
                sources=["microphone"],
                type="filepath",
                label="음성으로 질문하기",
                scale=4,
            )
            transcribe_btn = gr.Button("음성 → 텍스트 변환", scale=1)

        with gr.Row():
            show_thinking = gr.Checkbox(label="사고 과정 표시", value=False)
            use_tts = gr.Checkbox(label="음성으로 답변 읽기 (TTS)", value=False)
            reset_btn = gr.Button("대화 초기화", size="sm")

        tts_output = gr.Audio(label="음성 답변", autoplay=True, visible=False)
        use_tts.change(lambda v: gr.Audio(visible=v), inputs=[use_tts], outputs=[tts_output])

        user_selector.change(
            switch_user,
            inputs=[user_selector],
            outputs=[chatbot, run_ids_state],
        ).then(
            lambda u: u, inputs=[user_selector], outputs=[user_state]
        )

        transcribe_btn.click(transcribe_audio, inputs=[audio_input], outputs=[msg_box])

        send_btn.click(
            respond,
            inputs=[msg_box, chatbot, show_thinking, user_state, use_tts, run_ids_state],
            outputs=[chatbot, msg_box, tts_output, run_ids_state, thinking_box],
        )
        msg_box.submit(
            respond,
            inputs=[msg_box, chatbot, show_thinking, user_state, use_tts, run_ids_state],
            outputs=[chatbot, msg_box, tts_output, run_ids_state, thinking_box],
        )
        reset_btn.click(reset_chat, inputs=[user_state], outputs=[chatbot, run_ids_state])

        chatbot.like(
            handle_feedback,
            inputs=[chatbot, run_ids_state, user_state],
            outputs=[],
        )

    with gr.Tab("문서 등록"):
        gr.Markdown("PDF 또는 TXT 파일을 업로드하면 율봇이 내용을 참고해 답변합니다.")
        file_input = gr.File(
            file_types=[".pdf", ".txt"],
            file_count="multiple",
            label="파일 선택",
        )
        ingest_btn = gr.Button("문서 수집", variant="primary")
        ingest_status = gr.Textbox(label="결과", interactive=False)
        ingest_btn.click(ingest_files, inputs=[file_input], outputs=[ingest_status])

    with gr.Tab("문서 관리"):
        gr.Markdown("Qdrant에 등록된 문서 목록입니다. 불필요한 문서를 삭제할 수 있습니다.")
        doc_table = gr.Dataframe(
            headers=["파일명", "전체 경로"],
            label="등록된 문서",
            interactive=False,
        )
        refresh_btn = gr.Button("새로고침")
        gr.Markdown("---")
        with gr.Row():
            delete_source = gr.Textbox(
                label="삭제할 파일 경로",
                placeholder="위 표에서 전체 경로를 복사해 붙여넣으세요",
                scale=4,
            )
            delete_btn = gr.Button("삭제", variant="stop", scale=1)
        delete_status = gr.Textbox(label="결과", interactive=False)

        refresh_btn.click(list_docs, outputs=[doc_table])
        delete_btn.click(delete_doc, inputs=[delete_source], outputs=[delete_status, doc_table])
        demo.load(list_docs, outputs=[doc_table])


if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860, theme=gr.themes.Soft())