Update ui.py

ui.py

@@ -24,6 +24,7 @@ from app.forecast import SeasonalityModel
 from app.compliance import rule_based_check, llm_check_and_fix
 from app.openai_client import openai_chat_json
 
+
 # 初期化
 init_db()
 _seasonality_cache: Dict[str, SeasonalityModel] = {}
@@ -64,18 +65,64 @@ GEN_USER_TEMPLATE = """
 - 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"]
+    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):
+    """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_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):
+        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})
+    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
     constraints = {"ng_words": [w.strip() for w in ng_words.splitlines() if w.strip()]} if ng_words else {}
 
     upsert_campaign(
@@ -91,20 +138,45 @@ async def ui_generate(campaign_id: str, brand: str, product: str, target: str, t
         k=k_variants,
     )
 
-    data = await openai_chat_json(
-        [
-            {"role": "system", "content": GEN_SYSTEM},
-            {"role": "user", "content": user},
-        ],
-        temperature=0.3,
-        max_tokens=1200,
-    )
+    # 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,
+        )
+        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,
+            )
+            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)
 
-    items = data.get("variants", data if isinstance(data, list) else [])
     rows = []
-    for it in (items[:k_variants] if isinstance(items, list) else []):
-        headline = (it.get("headline") or "").strip()
-        body = (it.get("body") or "").strip()
+    for it in items[:k_variants]:
+        headline = it["headline"]
+        body = it["body"]
         text = f"{headline}\n{body}".strip()
         vid = str(uuid.uuid4())[:8]
 
@@ -136,6 +208,7 @@ async def ui_generate(campaign_id: str, brand: str, product: str, target: str, t
     df = pd.DataFrame(rows, columns=GENERATE_COLUMNS)
     return df
 
+
 def ui_serve(campaign_id: str, hour: int, segment: str):
     ctx = {"hour": int(hour), "segment": (segment or "").strip() or None}
     m = _seasonal(campaign_id)
@@ -154,6 +227,7 @@ def ui_serve(campaign_id: str, hour: int, segment: str):
 
     return vid, row["text"]
 
+
 def ui_feedback(campaign_id: str, variant_id: str, event_type: str):
     if not variant_id:
         raise gr.Error("先に Serve してください。")
@@ -161,6 +235,7 @@ def ui_feedback(campaign_id: str, variant_id: str, event_type: str):
     ThompsonBandit.update_with_event(campaign_id, variant_id, 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)
@@ -183,6 +258,7 @@ def ui_report(campaign_id: str):
     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)
@@ -191,6 +267,7 @@ def ui_check(text: str):
     reasons_joined = "; ".join(bads + reasons)
     return status, reasons_joined, fixed_text
 
+
 with gr.Blocks(title="AdCopy MAB Optimizer", fill_height=True) as demo:
     gr.Markdown("""
     # AdCopy MAB Optimizer（HF UI）