ui.py

from __future__ import annotations

# === Writable config dirs ===
import os
os.environ.setdefault("APP_DATA_DIR", "/data/app_data" if os.access("/data", os.W_OK) else "/tmp/app_data")
os.environ.setdefault("MPLCONFIGDIR", os.path.join(os.environ["APP_DATA_DIR"], "mplconfig"))
os.makedirs(os.environ["MPLCONFIGDIR"], exist_ok=True)

import json, uuid, random
from datetime import datetime
from typing import Dict

import gradio as gr
import pandas as pd

from app.storage import (
    init_db, insert_variant, upsert_campaign, get_variant, get_metrics,
    get_campaign, set_campaign_settings,
    get_campaign_value_per_conversion, log_event,
    export_csv, reset_all, evaluate_stop_rules,
    record_compliance_log, audit, get_variants
)
from app.bandit import ThompsonBandit
from app.linucb import LinUCB
from app.forecast import SeasonalityModel
from app.compliance import rule_based_check, llm_check_and_fix
from app.openai_client import openai_chat_json
from app.adapters import XAdapter, MetaAdapter, GoogleAdsAdapter

# 初期化
init_db()
_seasonality_cache: Dict[str, SeasonalityModel] = {}

GENERATE_COLUMNS = ["variant_id", "status", "rejection_reason", "text"]
REPORT_COLUMNS   = ["variant_id","impressions","clicks","conversions","ctr","cvr","expected_value"]

GEN_SYSTEM = """
あなたは日本語広告コピーのプロフェッショナルコピーライターです。
出力は**次のJSONオブジェクトのみ**で厳密に返してください。余計な文章・説明・前置きは禁止です。
形式:
{"variants":[{"headline":"全角15-25字程度","body":"全角40-90字程度"}, ...]}
ルール:
- 医薬効能の断定、100%、永久、即効、根拠のない数値などの誇大表現は禁止
- CTAは自然に
- 日本語で、句読点や記号は自然に
"""
GEN_USER_TEMPLATE = """
ブランド: {brand}
商品/サービス: {product}
想定ターゲット: {target}
トーン: {tone}
制約: {constraints}
生成本数: {k}

要件:
- "variants" 配列の要素数は **ちょうど {k}** 件にしてください
- 各要素は {{"headline":"...","body":"..."}} のみ
"""

def _seasonal(campaign_id: str) -> SeasonalityModel:
    if campaign_id not in _seasonality_cache:
        m = SeasonalityModel(campaign_id)
        try:
            m.fit()
        except Exception:
            pass
        _seasonality_cache[campaign_id] = m
    return _seasonality_cache[campaign_id]

def _safe_get_variants(data, k: int):
    items = []
    if isinstance(data, dict) and isinstance(data.get("variants"), list):
        items = data["variants"]
    elif isinstance(data, list):
        items = data
    if not items or not all(isinstance(x, dict) for x in items):
        return None
    out = []
    for it in items[:k]:
        out.append({
            "headline": str(it.get("headline", "")).strip(),
            "body": str(it.get("body", "")).strip(),
        })
    return out

def _local_variants(brand: str, product: str, k: int):
    base_head = ["使いやすさで選ばれています","日々の習慣をシンプルに","はじめてでも安心","続けやすいサポートを","いま必要な機能だけを"]
    base_body = [
        "{brand}の「{product}」。生活になじむ設計で、今日からムリなく始められます。まずは詳細をご覧ください。",
        "毎日を少しラクに。{brand}の{product}が、あなたの習慣づくりを後押しします。今すぐチェック。",
        "難しい操作は不要。{brand}の{product}なら、使い始めから自然に続けられます。詳しくはサイトへ。",
        "必要な情報をひと目で。{brand}の{product}で、日々の管理をシンプルに。詳細を見る。",
        "続けやすさを重視。{brand}の{product}で、小さな一歩から。"
    ]
    out = []
    for i in range(k):
        out.append({"headline": base_head[i % len(base_head)],
                    "body": base_body[i % len(base_body)].format(brand=brand, product=product)})
    return out

async def ui_generate(campaign_id: str, brand: str, product: str, target: str, tone: str, k_variants: int,
                      ng_words: str, value_per_conversion: float):
    k_variants = int(k_variants)
    constraints = {"ng_words": [w.strip() for w in ng_words.splitlines() if w.strip()]} if ng_words else {}
    upsert_campaign(campaign_id, brand, product, target, tone, "ja", constraints, value_per_conversion)

    user = GEN_USER_TEMPLATE.format(
        brand=brand, product=product, target=target, tone=tone,
        constraints=json.dumps(constraints, ensure_ascii=False), k=k_variants
    )

    items = None
    try:
        data = await openai_chat_json(
            [{"role": "system", "content": GEN_SYSTEM},{"role": "user", "content": user}],
            temperature=0.2, max_tokens=1200,
        )
        items = _safe_get_variants(data, k_variants)
    except Exception:
        items = None
    if not items:
        try:
            retry_user = user + "\n\n注意: 'variants' は必ず指定件数、各要素は {\"headline\":\"...\",\"body\":\"...\"} のみ。"
            data = await openai_chat_json(
                [{"role": "system", "content": GEN_SYSTEM},{"role": "user", "content": retry_user}],
                temperature=0.1, max_tokens=1000,
            )
            items = _safe_get_variants(data, k_variants)
        except Exception:
            items = None
    if not items:
        items = _local_variants(brand, product, k_variants)

    rows = []
    for it in items[:k_variants]:
        headline, body = it["headline"], it["body"]
        text = f"{headline}\n{body}".strip()
        vid = str(uuid.uuid4())[:8]

        ok_rule, bads = rule_based_check(text, (constraints or {}).get("ng_words"))
        status, rejection = "approved", None
        ok_llm, reasons, fixed = llm_check_and_fix(text)
        if not ok_rule and not ok_llm:
            status, rejection = "rejected", "; ".join(bads + reasons)
        elif not ok_rule and ok_llm:
            text = fixed or text
        elif ok_rule and not ok_llm:
            text = fixed or text

        insert_variant(campaign_id, vid, text, status, rejection)
        record_compliance_log(campaign_id, vid, status, bads, ok_llm, reasons, fixed)

        rows.append({"variant_id": vid, "status": status, "rejection_reason": rejection or "", "text": text})

    df = pd.DataFrame(rows, columns=GENERATE_COLUMNS)
    return df

def _policy_of(campaign_id: str) -> str:
    cfg = get_campaign(campaign_id)
    return str(cfg["policy"] or "thompson") if cfg else "thompson"

def _holdout_ratio_of(campaign_id: str) -> float:
    cfg = get_campaign(campaign_id)
    return float(cfg["holdout_ratio"] or 0.0) if cfg else 0.0

def _context(hour: int, segment: str) -> Dict[str, str | int | None]:
    return {"hour": int(hour), "segment": (segment or "").strip() or None}

def ui_set_settings(campaign_id: str, policy: str, holdout: float, stop_min_impr: int, stop_rel_ev: float):
    set_campaign_settings(campaign_id, policy, holdout, stop_min_impr, stop_rel_ev)
    return f"Updated: policy={policy}, holdout={holdout}, stop_min_impressions={stop_min_impr}, stop_rel_ev_threshold={stop_rel_ev}"

def _uniform_variant(campaign_id: str) -> str | None:
    vs = get_variants(campaign_id)
    if not vs: return None
    return random.choice(vs)["variant_id"]

def ui_serve(campaign_id: str, hour: int, segment: str, aa_min_impr: int):
    ctx = _context(hour, segment)
    m = _seasonal(campaign_id)
    policy = _policy_of(campaign_id)
    holdout = _holdout_ratio_of(campaign_id)
    mets = get_metrics(campaign_id)
    if not mets:
        raise gr.Error("配信可能なバリアントがありません。まずは Generate してください。")

    # A/Aテスト：各バリアントのimpressionsがしきい値未満なら一様ランダム
    if aa_min_impr and aa_min_impr > 0:
        for r in mets:
            if int(r["impressions"]) < int(aa_min_impr):
                vid = _uniform_variant(campaign_id)
                row = get_variant(campaign_id, vid)
                log_event(campaign_id, vid, "impression", datetime.utcnow().isoformat(), None)
                ThompsonBandit.update_with_event(campaign_id, vid, "impression")
                audit(campaign_id, "serve", {"variant_id": vid, "policy": "AA"})
                return vid, row["text"]

    # ホールドアウト：一定確率で一様ランダム
    if holdout > 0 and random.random() < float(holdout):
        vid = _uniform_variant(campaign_id)
        row = get_variant(campaign_id, vid)
        log_event(campaign_id, vid, "impression", datetime.utcnow().isoformat(), None)
        ThompsonBandit.update_with_event(campaign_id, vid, "impression")
        audit(campaign_id, "serve", {"variant_id": vid, "policy": "holdout"})
        return vid, row["text"]

    # 通常ポリシー
    if policy == "linucb":
        bandit = LinUCB(campaign_id)
        vid, _ = bandit.choose(ctx)
    else:
        bandit = ThompsonBandit(campaign_id)
        vid, _ = bandit.sample_arm(ctx, m.expected_ctr)

    if not vid:
        raise gr.Error("バリアントが見つかりません。")

    row = get_variant(campaign_id, vid)
    log_event(campaign_id, vid, "impression", datetime.utcnow().isoformat(), None)
    ThompsonBandit.update_with_event(campaign_id, vid, "impression")
    audit(campaign_id, "serve", {"variant_id": vid, "policy": policy})
    return vid, row["text"]

def ui_feedback(campaign_id: str, variant_id: str, event_type: str, hour: int, segment: str):
    if not variant_id:
        raise gr.Error("先に Serve してください。")
    ctx = _context(hour, segment)
    log_event(campaign_id, variant_id, event_type, datetime.utcnow().isoformat(), None)
    ThompsonBandit.update_with_event(campaign_id, variant_id, event_type)
    # LinUCBはclickのみで学習（CTRモデル）
    if event_type == "click" and _policy_of(campaign_id) == "linucb":
        LinUCB(campaign_id).update_click(variant_id, ctx, reward=1.0)
    audit(campaign_id, "feedback", {"variant_id": variant_id, "event": event_type})
    return f"{event_type} を記録しました。"

def ui_report(campaign_id: str):
    mets = get_metrics(campaign_id)
    vpc = get_campaign_value_per_conversion(campaign_id)
    rows = []
    for r in mets:
        imp = int(r["impressions"]); clk = int(r["clicks"]); conv = int(r["conversions"])
        ctr = (clk / imp) if imp > 0 else 0.0
        cvr = (conv / clk) if clk > 0 else 0.0
        ev  = ctr * cvr * vpc
        rows.append({
            "variant_id": r["variant_id"],
            "impressions": imp, "clicks": clk, "conversions": conv,
            "ctr": round(ctr, 4), "cvr": round(cvr, 4), "expected_value": round(ev, 6),
        })
    return pd.DataFrame(rows, columns=REPORT_COLUMNS)

def ui_apply_stop(campaign_id: str):
    paused = evaluate_stop_rules(campaign_id)
    if not paused:
        return "No changes."
    return "Paused: " + ", ".join([f"{vid}({reason})" for vid, reason in paused])

def ui_export_csv(campaign_id: str, table: str):
    path = export_csv(campaign_id, table)
    return path

def ui_reset_db(confirm_text: str):
    if (confirm_text or "").strip().upper() != "RESET":
        raise gr.Error("タイプミス: RESET と入力してください。")
    reset_all()
    return "DB was reset."

def ui_adapter_send(campaign_id: str, platform: str, variant_id: str, text: str, hour: int, segment: str):
    ctx = _context(hour, segment)
    if platform == "x":
        ad = XAdapter(campaign_id)
    elif platform == "meta":
        ad = MetaAdapter(campaign_id)
    else:
        ad = GoogleAdsAdapter(campaign_id)
    res = ad.send(variant_id, text, ctx)
    return json.dumps(res, ensure_ascii=False)

with gr.Blocks(title="AdCopy MAB Optimizer", fill_height=True) as demo:
    gr.Markdown("""
    # AdCopy MAB Optimizer（HF UI・拡張版）
    - 生成→審査→配信（Thompson / LinUCB）→レポート
    - A/Aテスト・ホールドアウト、撤退基準
    - CSVエクスポート、DBリセット、外部配信スタブ
    """)

    with gr.Tab("1) Generate"):
        with gr.Row():
            campaign_id = gr.Textbox(label="campaign_id", value="cmp-demo", scale=1)
            k_variants = gr.Slider(1, 10, value=5, step=1, label="生成本数")
            value_per_conv = gr.Number(value=5000, label="value_per_conversion")
        brand = gr.Textbox(label="ブランド", value="SFM")
        product = gr.Textbox(label="商品/サービス", value="HbA1c測定アプリ")
        target = gr.Textbox(label="ターゲット", value="30-50代の健康意識が高い層")
        tone = gr.Textbox(label="トーン", value="エビデンス重視で安心感")
        ng_words = gr.Textbox(label="NGワード（改行区切り）", value="治る\n奇跡")
        btn_gen = gr.Button("広告案を生成＆審査＆保存")
        table_gen = gr.Dataframe(headers=GENERATE_COLUMNS, interactive=False)
        btn_gen.click(ui_generate, [campaign_id, brand, product, target, tone, k_variants, ng_words, value_per_conv], [table_gen])

    with gr.Tab("2) Settings"):
        with gr.Row():
            campaign_id_set = gr.Textbox(label="campaign_id", value="cmp-demo", scale=1)
            policy = gr.Dropdown(choices=["thompson", "linucb"], value="thompson", label="Policy")
            holdout = gr.Slider(0.0, 0.5, value=0.0, step=0.05, label="Holdout ratio")
        with gr.Row():
            stop_min_impr = gr.Number(value=200, label="撤退判定の最小impressions")
            stop_rel_ev = gr.Slider(0.1, 0.9, value=0.5, step=0.05, label="EVの相対しきい値（劣後停止）")
        btn_set = gr.Button("設定を保存")
        msg_set = gr.Markdown()
        btn_set.click(ui_set_settings, [campaign_id_set, policy, holdout, stop_min_impr, stop_rel_ev], [msg_set])

    with gr.Tab("3) Serve & Feedback"):
        with gr.Row():
            campaign_id2 = gr.Textbox(label="campaign_id", value="cmp-demo", scale=1)
            hour = gr.Slider(0, 23, value=20, step=1, label="hour")
            segment = gr.Textbox(label="segment (任意)")
            aa_min_impr = gr.Number(value=0, label="A/Aテスト閾値（各variantのimpressionsがこの数に達するまで均等ランダム）")
        btn_serve = gr.Button("Serve Ad（impressionを記録）")
        served_vid = gr.Textbox(label="served variant_id", interactive=False)
        served_text = gr.Textbox(label="served text", lines=6, interactive=False)
        btn_serve.click(ui_serve, [campaign_id2, hour, segment, aa_min_impr], [served_vid, served_text])

        with gr.Row():
            btn_click = gr.Button("Clickを記録")
            btn_conv = gr.Button("Conversionを記録")
            msg = gr.Markdown()
        btn_click.click(lambda cid, vid, h, s: ui_feedback(cid, vid, "click", h, s), [campaign_id2, served_vid, hour, segment], [msg])
        btn_conv.click(lambda cid, vid, h, s: ui_feedback(cid, vid, "conversion", h, s), [campaign_id2, served_vid, hour, segment], [msg])

        gr.Markdown("### 外部配信スタブ")
        with gr.Row():
            platform = gr.Dropdown(choices=["x", "meta", "google"], value="x", label="プラットフォーム")
            btn_send = gr.Button("この広告を外部に送る（スタブ）")
            send_res = gr.Textbox(label="送信結果", lines=3)
        btn_send.click(ui_adapter_send, [campaign_id2, platform, served_vid, served_text, hour, segment], [send_res])

    with gr.Tab("4) Report & Ops"):
        campaign_id3 = gr.Textbox(label="campaign_id", value="cmp-demo")
        with gr.Row():
            btn_rep = gr.Button("レポート更新")
            table_rep = gr.Dataframe(headers=REPORT_COLUMNS, interactive=False)
            btn_rep.click(ui_report, [campaign_id3], [table_rep])
        with gr.Row():
            btn_stop = gr.Button("撤退基準を適用（自動pause）")
            msg_stop = gr.Markdown()
            btn_stop.click(ui_apply_stop, [campaign_id3], [msg_stop])

        gr.Markdown("#### CSVエクスポート")
        table_sel = gr.Dropdown(choices=["events","metrics","variants","compliance_logs","audit_logs"], value="metrics", label="テーブル")
        btn_exp = gr.Button("エクスポート")
        file_out = gr.File(label="ダウンロード", interactive=False)
        btn_exp.click(ui_export_csv, [campaign_id3, table_sel], [file_out])

        gr.Markdown("#### 管理用：DBリセット（全削除）")
        confirm = gr.Textbox(label="タイプ: RESET", value="")
        btn_reset = gr.Button("DBを初期化")
        msg_reset = gr.Markdown()
        btn_reset.click(ui_reset_db, [confirm], [msg_reset])

if __name__ == "__main__":
    demo.queue().launch(server_name="0.0.0.0", server_port=7860)