Update ui.py

ui.py

@@ -1,14 +1,12 @@
 from __future__ import annotations
 
-# === Writable config dirs (must come right after future import) ===
+# === 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
-import uuid
+import json, uuid, random
 from datetime import datetime
 from typing import Dict
 
@@ -17,41 +15,35 @@ import pandas as pd
 
 from app.storage import (
     init_db, insert_variant, upsert_campaign, get_variant, get_metrics,
-    get_campaign_value_per_conversion, log_event
+    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] = {}
 
-# 固定カラム（常にこの形で返す）
 GENERATE_COLUMNS = ["variant_id", "status", "rejection_reason", "text"]
 REPORT_COLUMNS   = ["variant_id","impressions","clicks","conversions","ctr","cvr","expected_value"]
 
-# JSONモード前提の厳格プロンプト
 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"},
-    ...
-  ]
-}
-
+{"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}
@@ -62,24 +54,20 @@ GEN_USER_TEMPLATE = """
 
 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
+- 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:
-            # 失敗してもフォールバックあり
             pass
         _seasonality_cache[campaign_id] = m
     return _seasonality_cache[campaign_id]
 
-
 def _safe_get_variants(data, k: int):
-    """LLM応答から variants 配列を安全に取り出して正規化。失敗時は None を返す。"""
     items = []
     if isinstance(data, dict) and isinstance(data.get("variants"), list):
         items = data["variants"]
@@ -95,16 +83,8 @@ def _safe_get_variants(data, k: int):
         })
     return out
 
-
 def _local_variants(brand: str, product: str, k: int):
-    """LLMが不調でも UI を止めないための最終フォールバック生成（簡易・無害表現）。"""
-    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_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。",
@@ -114,128 +94,145 @@ def _local_variants(brand: str, product: str, k: int):
     ]
     out = []
     for i in range(k):
-        hi = base_head[i % len(base_head)]
-        bo = base_body[i % len(base_body)].format(brand=brand, product=product)
-        out.append({"headline": hi, "body": bo})
+        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)  # Slider の float を明示的に int 化
+    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
-    )
+    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,
+        brand=brand, product=product, target=target, tone=tone,
+        constraints=json.dumps(constraints, ensure_ascii=False), k=k_variants
     )
 
-    # まずは通常プロンプトで JSON モード呼び出し
     items = None
     try:
         data = await openai_chat_json(
-            [
-                {"role": "system", "content": GEN_SYSTEM},
-                {"role": "user", "content": user},
-            ],
-            temperature=0.2,
-            max_tokens=1200,
+            [{"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
-
-    # 失敗/空のときは、温度をさらに下げて再試行（より厳格に）
     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,
+                [{"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
-
-    # それでも無理ならローカル生成（UIを止めない）
     if not items:
         items = _local_variants(brand, product, k_variants)
 
     rows = []
     for it in items[:k_variants]:
-        headline = it["headline"]
-        body = it["body"]
+        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"))
-        rejection_reason = None
-        status = "approved"
-
-        if not ok_rule:
-            ok_llm, reasons, fixed = llm_check_and_fix(text)
-            if ok_llm:
-                text = fixed or text
-            else:
-                status = "rejected"
-                rejection_reason = "; ".join(bads + reasons)
-        else:
-            ok_llm, reasons, fixed = llm_check_and_fix(text)
-            if not ok_llm:
-                text = fixed or text
-
-        insert_variant(campaign_id, vid, text, status, rejection_reason)
-        rows.append({
-            "variant_id": vid,
-            "status": status,
-            "rejection_reason": rejection_reason or "",
-            "text": text,
-        })
+        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})
 
-    # 常に固定カラムで返す（空でもカラムを持つDataFrame）
     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):
-    ctx = {"hour": int(hour), "segment": (segment or "").strip() or None}
+def ui_serve(campaign_id: str, hour: int, segment: str, aa_min_impr: int):
+    ctx = _context(hour, segment)
     m = _seasonal(campaign_id)
-    bandit = ThompsonBandit(campaign_id)
-    vid, _ = bandit.sample_arm(ctx, m.expected_ctr)
-    if not vid:
+    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。")
 
-    row = get_variant(campaign_id, vid)
-    if not row:
+    # 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。")
 
-    # impression 記録
+    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):
+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)
@@ -247,34 +244,44 @@ def ui_report(campaign_id: str):
         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),
+            "impressions": imp, "clicks": clk, "conversions": conv,
+            "ctr": round(ctr, 4), "cvr": round(cvr, 4), "expected_value": round(ev, 6),
         })
-    # 常に固定カラムで返す（空でもカラムを持つDataFrame）
-    df = pd.DataFrame(rows, columns=REPORT_COLUMNS)
-    return df
-
-
-def ui_check(text: str):
-    ok_rule, bads = rule_based_check(text, [])
-    ok_llm, reasons, fixed = llm_check_and_fix(text)
-    status = "pass" if (ok_rule and ok_llm) else "needs_fix"
-    fixed_text = fixed or (text if status == "pass" else "")
-    reasons_joined = "; ".join(bads + reasons)
-    return status, reasons_joined, fixed_text
-
+    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）
-    **広告コピー自動生成 → Thompson Sampling（CTR×CVR） → レポート** を、Hugging Face Spaces 上で完結。
-    - LLM: OpenAI （`OPENAI_API_KEY` を Space Secrets に設定）
-    - DB: SQLite（`/data/app_data/data.db` など、書き込み可能ディレクトリ）
-    - 季節性: Prophet/NeuralProphet（なければ簡易ヒューリスティック）
+    # 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"):
@@ -291,36 +298,65 @@ with gr.Blocks(title="AdCopy MAB Optimizer", fill_height=True) as demo:
         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) Serve & Feedback"):
+    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], [served_vid, served_text])
+        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: ui_feedback(cid, vid, "click"), [campaign_id2, served_vid], [msg])
-        btn_conv.click(lambda cid, vid: ui_feedback(cid, vid, "conversion"), [campaign_id2, served_vid], [msg])
+        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("3) Report"):
+    with gr.Tab("4) Report & Ops"):
         campaign_id3 = gr.Textbox(label="campaign_id", value="cmp-demo")
-        btn_rep = gr.Button("更新")
-        table_rep = gr.Dataframe(headers=REPORT_COLUMNS, interactive=False)
-        btn_rep.click(ui_report, [campaign_id3], [table_rep])
-
-    with gr.Tab("4) Compliance Check"):
-        cand = gr.Textbox(label="チェックする文面", lines=5)
-        btn_chk = gr.Button("判定")
-        status = gr.Textbox(label="status")
-        reasons = gr.Textbox(label="reasons")
-        fixed = gr.Textbox(label="fixed (修正案)", lines=5)
-        btn_chk.click(ui_check, [cand], [status, reasons, fixed])
+        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)