Upload app.py

app.py

@@ -12,41 +12,13 @@ logger = logging.getLogger(__name__)
 load_dotenv()
 
 
-# --- 2. 安全機構（保険）の実装 (辞書と関数ベース) ---
+# --- 2. 安全機構（保険）の実装 (【デバッグのため一時的に無効化】) ---
 
 # グローバルな安全設定
-RATE_LIMIT_MAX_REQUESTS = 15
-RATE_LIMIT_IN_SECONDS = 60
 MAX_INPUT_LENGTH = 1000
 MAX_HISTORY_TURNS = 100
 
-def create_limiter_state():
-    """レートリミッターの初期状態（辞書）を作成する関数"""
-    return {
-        "timestamps": [],
-        "is_blocked": False
-    }
-
-def check_limiter(limiter_state):
-    """
-    リミッターの状態をチェックし、呼び出し可否を判断して状態を更新する関数。
-    呼び出しが許可されればTrueを、拒否されればFalseを返す。
-    """
-    if limiter_state["is_blocked"]:
-        logger.warning("API呼び出しは永続的にブロックされています。")
-        return False
-
-    now = time.time()
-    limiter_state["timestamps"] = [t for t in limiter_state["timestamps"] if now - t < RATE_LIMIT_IN_SECONDS]
-
-    if len(limiter_state["timestamps"]) >= RATE_LIMIT_MAX_REQUESTS:
-        logger.error(f"レートリミット超過！ {RATE_LIMIT_IN_SECONDS}秒以内に{RATE_LIMIT_MAX_REQUESTS}回を超えました。このセッションのAPI呼び出しを永久にブロックします。")
-        limiter_state["is_blocked"] = True
-        return False
-    
-    limiter_state["timestamps"].append(now)
-    return True
-
+# 【デバッグのためAPILimiter関連の関数はすべて一旦無視します】
 
 # --- 3. APIクライアント初期化 ---
 try:
@@ -54,7 +26,6 @@ try:
     if not TOGETHER_API_KEY:
         raise ValueError("環境変数 TOGETHER_API_KEY が設定されていません。Hugging Face SpaceのSecretsに設定してください。")
     
-    # Together AIはOpenAIのライブラリと互換性がある
     client = OpenAI(
         api_key=TOGETHER_API_KEY,
         base_url="https://api.together.xyz/v1",
@@ -107,11 +78,8 @@ def get_sentiment_analyzer():
             logger.error(f"感情分析モデルのロードに失敗: {e}")
     return sentiment_analyzer
 
-def call_llm(system_prompt, user_prompt, limiter_state, is_json_output=False):
-    """Together AIを呼び出す共通関数。必ずリミッターを通過させる。"""
-    if not check_limiter(limiter_state):
-        return None
-
+def call_llm(system_prompt, user_prompt, is_json_output=False):
+    """Together AIを呼び出す共通関数"""
     messages = [
         {"role": "system", "content": system_prompt},
         {"role": "user", "content": user_prompt}
@@ -128,11 +96,9 @@ def call_llm(system_prompt, user_prompt, limiter_state, is_json_output=False):
         return chat_completion.choices[0].message.content
     except Exception as e:
         logger.error(f"Together AIのAPI呼び出し中に致命的なエラー: {e}", exc_info=True)
-        limiter_state["is_blocked"] = True
-        logger.error("APIエラーのため、このセッションのAPI呼び出しをブロックします。")
         return None
 
-def detect_scene_change(history, message, limiter_state):
+def detect_scene_change(history, message):
     history_text = "\n".join([f"ユーザー: {u}\n麻理: {m}" for u, m in history[-3:]])
     available_keywords = ", ".join(THEME_URLS.keys())
     system_prompt = "あなたは会話分析のエキスパートです。ユーザーの提案とキャラクターの反応から、シーン（場所）が変更されるか判断し、指定されたキーワードでJSON形式で出力してください。"
@@ -146,7 +112,7 @@ def detect_scene_change(history, message, limiter_state):
 合意していない場合は {{"scene": "none"}} と出力してください。
 キーワード: {available_keywords}
 """
-    response_text = call_llm(system_prompt, user_prompt, limiter_state, is_json_output=True)
+    response_text = call_llm(system_prompt, user_prompt, is_json_output=True)
     if response_text:
         try:
             result = json.loads(response_text)
@@ -158,7 +124,7 @@ def detect_scene_change(history, message, limiter_state):
             logger.error(f"シーン検出のJSON解析に失敗")
     return None
 
-def generate_dialogue(history, message, affection, stage_name, scene_params, limiter_state, instruction=None):
+def generate_dialogue(history, message, affection, stage_name, scene_params, instruction=None):
     history_text = "\n".join([f"ユーザー: {u}\n麻理: {m}" for u, m in history[-5:]])
     user_prompt = f"""
 # 現在の状況
@@ -172,7 +138,7 @@ def generate_dialogue(history, message, affection, stage_name, scene_params, lim
 {f"【特別指示】{instruction}" if instruction else f"ユーザーの発言「{message}」に応答してください。"}
 
 麻理の応答:"""
-    response_text = call_llm(SYSTEM_PROMPT_MARI, user_prompt, limiter_state)
+    response_text = call_llm(SYSTEM_PROMPT_MARI, user_prompt)
     return response_text if response_text else "（…うまく言葉が出てこない。少し時間を置いてほしい）"
 
 def get_relationship_stage(affection):
@@ -193,22 +159,16 @@ def update_affection(message, affection):
 
 
 # --- 6. Gradio応答関数 ---
-def respond(message, chat_history, affection, history, scene_params, limiter_state):
+def respond(message, chat_history, affection, history, scene_params):
     try:
-        # 保険: ブロック状態、入力長、履歴長のチェック
-        if limiter_state["is_blocked"]:
-            bot_message = "（…少し混乱している。時間をおいてから、ページを再読み込みして試してくれないか？）"
-            chat_history.append((message, bot_message))
-            return "", chat_history, affection, get_relationship_stage(affection), affection, history, scene_params, limiter_state, gr.update()
-
         if not message.strip():
-            return "", chat_history, affection, get_relationship_stage(affection), affection, history, scene_params, limiter_state, gr.update()
+            return "", chat_history, affection, get_relationship_stage(affection), affection, history, scene_params, gr.update()
 
         if len(message) > MAX_INPUT_LENGTH:
             logger.warning(f"入力長超過: {len(message)}文字")
             bot_message = f"（…長すぎる。{MAX_INPUT_LENGTH}文字以内で話してくれないか？）"
             chat_history.append((message, bot_message))
-            return "", chat_history, affection, get_relationship_stage(affection), affection, history, scene_params, limiter_state, gr.update()
+            return "", chat_history, affection, get_relationship_stage(affection), affection, history, scene_params, gr.update()
 
         if len(history) > MAX_HISTORY_TURNS:
             logger.error("会話履歴が長すぎます。システム保護のため、会話をリセットします。")
@@ -216,25 +176,23 @@ def respond(message, chat_history, affection, history, scene_params, limiter_sta
             chat_history = []
             bot_message = "（…ごめん、少し話が長くなりすぎた。最初からやり直そう）"
             chat_history.append((message, bot_message))
-            return "", chat_history, affection, get_relationship_stage(affection), affection, history, scene_params, limiter_state, gr.update()
+            return "", chat_history, affection, get_relationship_stage(affection), affection, history, scene_params, gr.update()
         
-        # 通常処理
         new_affection = update_affection(message, affection)
         stage_name = get_relationship_stage(new_affection)
         final_scene_params = scene_params.copy()
         
         bot_message = ""
-        new_scene_name = detect_scene_change(history, message, limiter_state)
+        new_scene_name = detect_scene_change(history, message)
         
         if new_scene_name and new_scene_name != final_scene_params.get("theme"):
             logger.info(f"シーンチェンジ実行: {final_scene_params.get('theme')} -> {new_scene_name}")
             final_scene_params["theme"] = new_scene_name
             instruction = f"ユーザーと一緒に「{new_scene_name}」に来た。周囲の様子を見て、最初の感想をぶっきらぼうに一言つぶやいてください。"
-            bot_message = generate_dialogue(history, message, new_affection, stage_name, final_scene_params, limiter_state, instruction)
+            bot_message = generate_dialogue(history, message, new_affection, stage_name, final_scene_params, instruction)
         else:
-            bot_message = generate_dialogue(history, message, new_affection, stage_name, final_scene_params, limiter_state)
+            bot_message = generate_dialogue(history, message, new_affection, stage_name, final_scene_params)
 
-        # bot_messageがNoneや空の場合のフォールバック
         if not bot_message:
             bot_message = "（…うまく言葉にできない）"
 
@@ -244,14 +202,13 @@ def respond(message, chat_history, affection, history, scene_params, limiter_sta
         theme_url = THEME_URLS.get(final_scene_params.get("theme"), THEME_URLS["default"])
         background_html = f'<div class="background-container" style="background-image: url({theme_url});"></div>'
         
-        return "", chat_history, new_affection, stage_name, new_affection, new_history, final_scene_params, limiter_state, background_html
+        return "", chat_history, new_affection, stage_name, new_affection, new_history, final_scene_params, background_html
 
     except Exception as e:
         logger.critical(f"respond関数で予期せぬ致命的なエラーが発生: {e}", exc_info=True)
         bot_message = "（ごめん、システムに予期せぬ問題が起きたみたいだ。ページを再読み込みしてくれるか…？）"
         chat_history.append((message, bot_message))
-        limiter_state["is_blocked"] = True
-        return "", chat_history, affection, get_relationship_stage(affection), affection, history, scene_params, limiter_state, gr.update()
+        return "", chat_history, affection, get_relationship_stage(affection), affection, history, scene_params, gr.update()
 
 
 # --- 7. Gradio UIの構築 ---
@@ -263,11 +220,9 @@ except FileNotFoundError:
     custom_css = ""
 
 with gr.Blocks(css=custom_css, theme=gr.themes.Soft(primary_hue="rose", secondary_hue="pink"), title="麻理チャット") as demo:
-    # 内部状態管理用
     scene_state = gr.State({"theme": "default"})
     affection_state = gr.State(30)
     history_state = gr.State([])
-    limiter_state = gr.State(create_limiter_state())
     
     background_display = gr.HTML(f'<div class="background-container" style="background-image: url({THEME_URLS["default"]});"></div>')
 
@@ -275,7 +230,12 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft(primary_hue="rose", secondar
         gr.Markdown("# 麻理チャット", elem_classes="header")
         with gr.Row():
             with gr.Column(scale=3):
-                chatbot = gr.Chatbot(label="麻理との会話", height=550, elem_classes="chatbot", avatar_images=(None, "https://cdn.pixabay.com/photo/2016/03/31/21/40/bot-1296595_1280.png"))
+                chatbot = gr.Chatbot(
+                    label="麻理との会話",
+                    height=550,
+                    elem_classes="chatbot",
+                    avatar_images=(None, "https://cdn.pixabay.com/photo/2016/03/31/21/40/bot-1296595_1280.png"),
+                )
                 with gr.Row():
                     msg_input = gr.Textbox(placeholder="麻理に話しかけてみましょう...", lines=2, scale=4, container=False)
                     submit_btn = gr.Button("送信", variant="primary", scale=1, min_width=100)
@@ -285,8 +245,8 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft(primary_hue="rose", secondar
                     affection_gauge = gr.Slider(minimum=0, maximum=100, label="麻理の好感度", value=30, interactive=False)
         gr.Markdown("""<div class='footer'>Background Images & Icons: <a href="https://pixabay.com" target="_blank">Pixabay</a></div>""", elem_classes="footer")
 
-    outputs = [msg_input, chatbot, affection_gauge, stage_display, affection_state, history_state, scene_state, limiter_state, background_display]
-    inputs = [msg_input, chatbot, affection_state, history_state, scene_state, limiter_state]
+    outputs = [msg_input, chatbot, affection_gauge, stage_display, affection_state, history_state, scene_state, background_display]
+    inputs = [msg_input, chatbot, affection_state, history_state, scene_state]
     
     submit_btn.click(respond, inputs, outputs)
     msg_input.submit(respond, inputs, outputs)
@@ -297,6 +257,5 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft(primary_hue="rose", secondar
 
 
 if __name__ == "__main__":
-    # 感情分析モデルのプレロード（任意）
     get_sentiment_analyzer()
     demo.launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", 7860)))