app.py

# app.py — minimal for LLM + RAG (no MCP)
import os, json, random, uuid
from datetime import datetime
import streamlit as st
import rag_utils  # 你已經有的：提供 search_tarot / search_numerology / ensure_indexes
from data import load_tarot_data_full, numerology_data_full

TAROT_DATA = load_tarot_data_full()            # List[Dict]
NUMEROLOGY_DATA = numerology_data_full()       # List[Dict]

# 若你需要只要牌名/數字，可自行萃取：
TAROT_NAMES = [c.get("name") or c.get("card_name") for c in TAROT_DATA if (c.get("name") or c.get("card_name"))]




# ========== 基本設定 ==========
st.set_page_config(page_title="SoulCompass", page_icon="🧭", layout="wide")

# 使用者暫時 UID（未登入先用本機隨機 ID）
if "uid" not in st.session_state:
    st.session_state.uid = str(uuid.uuid4())[:8]
UID = st.session_state.uid
USER_DIR = os.path.join("data", "users", UID)
os.makedirs(USER_DIR, exist_ok=True)
JOURNAL_PATH = os.path.join(USER_DIR, "journal.jsonl")

st.markdown("""
<div style="text-align:center;background:linear-gradient(135deg,#6366F1,#C084FC);color:white;padding:1.4rem;border-radius:14px;margin-bottom:12px;">
  <h2 style="margin:0;">🧭 SoulCompass — Tarot • Numerology • Journal • Guide</h2>
</div>
""", unsafe_allow_html=True)

# ========== 讀取 Tarot / Numerology 資料 ==========
@st.cache_resource
def load_tarot_names():
    path = os.path.join("data", "tarot_data_full.json")
    with open(path, "r", encoding="utf-8") as f:
        data = json.load(f)
    names = []
    for c in data:
        nm = c.get("name") or c.get("card_name")
        if nm:
            names.append(nm)
    if not names:
        raise ValueError("No card names found in data/tarot_data_full.json")
    return names

@st.cache_resource
def load_numerology_data():
    path = os.path.join("data", "numerology_data_full.json")
    with open(path, "r", encoding="utf-8") as f:
        data = json.load(f)
    by_num, nums = {}, []
    for r in data:
        if "number" not in r: 
            continue
        n = int(r["number"])
        nums.append(n)
        by_num[n] = {
            "name": r.get("name",""),
            "keywords": r.get("keywords",[]),
            "description": r.get("description",""),
            "advice": r.get("advice","")
        }
    nums = sorted(set(nums))
    if not nums:
        raise ValueError("No numerology numbers found in data/numerology_data_full.json")
    return nums, by_num

def life_path_number_from_date(dt):
    s = dt.strftime("%Y%m%d")
    total = sum(int(d) for d in s)
    while total > 9 and total not in (11, 22, 33):
        total = sum(int(d) for d in str(total))
    return total

TAROT_NAMES = load_tarot_data_full()
NUMBERS, NUM_MAP = load_numerology_data_full()

# ========== Sidebar：模型與 RAG 參數 ==========
st.sidebar.header("⚙️ Settings")
model_choice = st.sidebar.selectbox(
    "LLM Model",
    ["cerebras/btlm-3b-8k-base", "mistralai/Mistral-7B-Instruct-v0.2"],
    help="BTLM 輕量、CPU 可跑；Mistral 口條更好但較吃資源。"
)
rag_k = st.sidebar.slider("RAG Top-K", 1, 5, 3)
temperature = st.sidebar.slider("Temperature", 0.2, 1.2, 0.7, 0.1)

# ========== RAG + LLM Loader ==========
@st.cache_resource
def load_rag():
    try:
        import rag_utils
        return rag_utils
    except Exception as e:
        st.warning("無法載入 rag_utils，請確認檔案存在於專案根目錄。")
        return None

@st.cache_resource
def load_llm(model_id: str):
    import torch
    from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
    tok = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
    model = AutoModelForCausalLM.from_pretrained(
        model_id,
        trust_remote_code=True,
        torch_dtype=torch.float32,     # 免費 CPU 最穩
        device_map="auto",
        low_cpu_mem_usage=True,
        offload_folder="/tmp",
    )
    return pipeline(
        "text-generation",
        model=model,
        tokenizer=tok,
        max_new_tokens=360,
        temperature=temperature,
        top_p=0.9,
        repetition_penalty=1.08,
        do_sample=True,
    )

rag = load_rag()
llm = load_llm(model_choice)

def rag_answer(query: str, domain: str = "Tarot", k: int = 3):
    if rag is None:
        return "RAG 模組未載入，請檢查 rag_utils.py。", []
    hits = rag.search_tarot(query, k) if domain == "Tarot" else rag.search_numerology(query, k)
    context = "\n\n".join([h["text"] for h in hits]) if hits else "（無檢索結果）"
    prompt = f"""You are SoulCompass, a compassionate spiritual guide.
Use ONLY the CONTEXT to answer the USER in Traditional Chinese with empathy and clarity.
If info is missing, admit briefly and suggest a next step.

CONTEXT:
{context}

USER QUESTION: {query}

請用 5~8 句繁體中文回覆，語氣溫柔、務實，最後給出 1 句可行的小建議。"""
    out = llm(prompt)[0]["generated_text"]
    answer = out[len(prompt):].strip()
    return answer, hits

# ========== Journal 長期保存（JSONL）==========
def load_journal(path=JOURNAL_PATH):
    entries = []
    if os.path.exists(path):
        with open(path, "r", encoding="utf-8") as f:
            for line in f:
                line = line.strip()
                if not line:
                    continue
                try:
                    entries.append(json.loads(line))
                except Exception:
                    pass
    return entries

def append_journal(entry: dict, path=JOURNAL_PATH):
    os.makedirs(os.path.dirname(path), exist_ok=True)
    with open(path, "a", encoding="utf-8") as f:
        f.write(json.dumps(entry, ensure_ascii=False) + "\n")

def save_all_journal(entries, path=JOURNAL_PATH):
    os.makedirs(os.path.dirname(path), exist_ok=True)
    with open(path, "w", encoding="utf-8") as f:
        for e in entries:
            f.write(json.dumps(e, ensure_ascii=False) + "\n")

def export_journal_csv(path=JOURNAL_PATH):
    if not os.path.exists(path):
        return None
    rows = load_journal(path)
    out_csv = os.path.join(USER_DIR, "journal_export.csv")
    import csv
    with open(out_csv, "w", encoding="utf-8", newline="") as f:
        w = csv.writer(f)
        w.writerow(["time", "mood", "emotion", "text"])
        for r in rows:
            w.writerow([r.get("time",""), r.get("mood",""), r.get("emotion",""), r.get("text","")])
    return out_csv

if "journal" not in st.session_state:
    st.session_state.journal = load_journal()

# ========== AI 心靈導師（安全護欄＋生成）==========
CRISIS_KEYWORDS = [
    "自殺","想死","結束生命","活不下去","傷害自己","割腕",
    "殺了我","想不開","無法活","輕生","自殘","不如死了"
]

def is_crisis(text: str) -> bool:
    if not text:
        return False
    # 中文大小寫無差；直接檢索原文關鍵字
    return any(k in text for k in CRISIS_KEYWORDS)

def guide_answer(user_msg: str, topic: str = "General"):
    if is_crisis(user_msg):
        crisis_reply = (
            "我聽見你現在非常難受，謝謝你願意說出來。你的感受很重要，也值得被好好照顧。\n\n"
            "目前這些想法可能代表你需要更即時、面對面的支持。請立刻聯絡你所在地的緊急服務，"
            "或尋求可信任的人陪伴（家人、朋友、學校輔導/公司 EAP）。\n\n"
            "你也可以尋找在地的心理諮商與危機支援資源（醫院身心科、社福單位、24 小時關懷專線）。\n\n"
            "現在先做三件小事：1) 找一個安全的空間，2) 打給一位你信任的人，3) 緩慢做 5 次深呼吸（吸4、停2、吐6）。\n\n"
            "我在這裡，願意繼續聽你說。"
        )
        return crisis_reply, []

    # 可選：混入少量 RAG 提示（用 Numerology 當中性語料）
    try:
        ctx_hits = rag.search_numerology("自我照顧 情緒 調節 建議", k=2) if rag else []
        context = "\n\n".join([h["text"] for h in ctx_hits]) if ctx_hits else "（無檢索）"
    except Exception:
        ctx_hits, context = [], "（無檢索）"

    prompt = f"""You are SoulCompass, a supportive, non-clinical companion.
- Respond in Traditional Chinese.
- Be empathetic, specific, and action-oriented.
- Do NOT diagnose conditions or offer medical advice.
- Offer 2~4 small, doable next steps, tailored to the user's message.
- Keep it under 10 sentences.

OPTIONAL CONTEXT (self-care ideas):
{context}

TOPIC: {topic}
USER: {user_msg}

請用溫柔、務實、去評判的語氣回覆，先同理、再聚焦、最後給 2~4 個可行的小步驟。"""
    out = llm(prompt)[0]["generated_text"]
    return out[len(prompt):].strip(), ctx_hits

# ========== Tabs ==========
tab1, tab2, tab3, tab4 = st.tabs(["🔮 Tarot", "🔢 Numerology", "📖 Journal", "🤖 AI 心靈導師"])

# ---- Tarot ----
with tab1:
    st.subheader("🔮 Tarot Reading")
    q = st.text_input("想詢問什麼？（例：我適合換工作嗎？）", key="tarot_q")
    spread = st.radio("抽牌陣列", ["Single (1)", "Three (3)", "Five (5)"], horizontal=True, key="tarot_spread")
    if st.button("抽牌並解讀", key="tarot_go"):
        if not q.strip():
            st.warning("請先輸入問題")
        else:
            n = 1 if "1" in spread else (3 if "3" in spread else 5)
            cards = random.sample(TAROT_NAMES, k=min(n, len(TAROT_NAMES)))
            st.success("你抽到：" + ", ".join(cards))
            query = f"問題：{q}；抽到的牌：{', '.join(cards)}。請用塔羅牌義做整體解讀。"
            with st.spinner("RAG 檢索 + 生成中…"):
                ans, refs = rag_answer(query, domain="Tarot", k=rag_k)
            st.markdown(ans)
            if refs:
                with st.expander("參考段落（RAG 來源）"):
                    for i, r in enumerate(refs, 1):
                        tag = r.get("card_name") or r.get("name") or "Card"
                        st.markdown(f"**#{i} {tag}** · score {r['score']:.3f}")
                        st.write(r["text"])
                        st.markdown("---")

# ---- Numerology ----
with tab2:
    st.subheader("🔢 Numerology")
    b = st.date_input("你的生日", key="dob")
    col1, col2 = st.columns(2)
    with col1:
        if st.button("計算生命靈數", key="lp_go"):
            if b:
                lp = life_path_number_from_date(b)
                st.success(f"你的生命靈數：{lp}（{NUM_MAP.get(lp,{}).get('name','')}）")
                qn = f"生命靈數 {lp} 的核心特質、盲點與行動建議？"
                with st.spinner("RAG 檢索 + 生成中…"):
                    ans, refs = rag_answer(qn, domain="Numerology", k=rag_k)
                st.markdown(ans)
    with col2:
        name = st.text_input("你的姓名（可選）", key="name_num")
        if st.button("名字數字", key="name_go"):
            if name.strip():
                n = (len(name.replace(" ", "")) % 9) + 1
                st.info(f"名字數字：{n}（{NUM_MAP.get(n,{}).get('name','')}）")
                qn = f"名字數字 {n} 的人在人際與自我表達上的建議？"
                ans, _ = rag_answer(qn, domain="Numerology", k=rag_k)
                st.write(ans)

# ---- Journal ----
with tab3:
    st.subheader("📖 Soul Journal")
    st.caption(f"本機使用者 ID：{UID}")
    mood = st.slider("今天的心情（1-10）", 1, 10, 7, key="mood")
    emotion = st.selectbox("主要情緒", ["😊 開心","😔 失落","😰 焦慮","😌 平靜","🤗 感恩"], key="emotion")
    entry = st.text_area("寫下今天的想法", height=140, placeholder="你最近在思考什麼？今天最感謝的一件事是？", key="entry")

    c1, c2, c3 = st.columns(3)
    with c1:
        if st.button("💾 儲存日記", key="save_journal"):
            if entry.strip():
                item = {
                    "time": datetime.now().strftime("%Y-%m-%d %H:%M"),
                    "mood": st.session_state.mood,
                    "emotion": st.session_state.emotion,
                    "text": entry.strip()
                }
                st.session_state.journal.append(item)
                append_journal(item)
                st.success("已儲存 🌟")
            else:
                st.warning("請先寫點內容")

    with c2:
        if st.button("⬇️ 匯出 CSV", key="export_journal"):
            out_csv = export_journal_csv()
            if out_csv and os.path.exists(out_csv):
                with open(out_csv, "rb") as f:
                    st.download_button("下載日記 CSV", f, file_name="journal_export.csv")
            else:
                st.warning("目前沒有日記可匯出")

    with c3:
        if st.button("🗑️ 清空全部日記", key="clear_journal"):
            save_all_journal([])
            st.session_state.journal = []
            st.success("全部日記已清空")

    if st.session_state.journal:
        st.markdown("---")
        st.markdown("**最近紀錄（新→舊）**")
        for j in reversed(st.session_state.journal[-50:]):
            st.markdown(f"- **{j['time']} · {j['emotion']} · 心情 {j['mood']}**  \n{j['text']}")

        if st.button("🧠 生成 7 日回顧建議", key="review7"):
            recent = "\n".join([j["text"] for j in st.session_state.journal[-20:]])
            qj = f"這是我最近的日記重點：\n{recent}\n請用溫柔務實的語氣，總結 3 點觀察，並給 3 個可行的小建議。"
            ans, _ = rag_answer(qj, domain="Numerology", k=2)  # 用較中性的語料
            st.markdown(ans)

# ---- AI 心靈導師 ----
with tab4:
    st.subheader("🤖 AI 心靈導師")
    st.caption("此功能提供一般性支持與自我照顧建議，非醫療或心理治療之替代。若有危機，請立即尋求在地緊急支援。")
    topic = st.selectbox(
        "主題",
        ["General", "Stress & Anxiety", "Relationships", "Work & Burnout", "Self-esteem", "Grief & Loss"],
        index=0,
        key="guide_topic"
    )
    user_msg = st.text_area("想跟我說點什麼？", height=140, placeholder="把現在的感受、困擾或情境說給我聽…", key="guide_msg")
    if st.button("💬 取得支持", key="guide_go"):
        if not user_msg.strip():
            st.warning("請先輸入一段想說的話")
        else:
            with st.spinner("AI 正在整理回應…"):
                reply, refs = guide_answer(user_msg, topic)
            st.markdown(reply)
            if refs:
                with st.expander("參考段落（RAG 來源）"):
                    for i, r in enumerate(refs, 1):
                        st.markdown(f"**#{i}** · score {r['score']:.3f}")
                        st.write(r["text"])
                        st.markdown("---")

# ========== Footer ==========
st.markdown("<hr>", unsafe_allow_html=True)
st.caption("🧭 SoulCompass · demo MVP · RAG + LLM powered")