++

backend/app/services/world_generator.py

@@ -72,23 +72,24 @@ active_agents_per_round_max should be about {max(3, int(population * 0.4))}"""
         if proposed_change:
             user_prompt += f'\n\nPROPOSED CHANGE being introduced into this world:\n"{proposed_change}"'
 
-        response = await self.llm.generate(
-            system=system,
-            user=user_prompt,
-            json_mode=True,
-            max_tokens=3000,
-        )
+        response = await self.llm.generate(
+            system=system,
+            user=user_prompt,
+            json_mode=True,
+            max_tokens=3000,
+            purpose="world_gen",
+        )
 
-        data = parse_json(response)
+        data = parse_json(response, purpose="世界生成")
         if not data:
-            logger.error("World generation produced empty result, using fallback")
+            logger.error("世界生成返回空结果，将使用备用世界")
             return self._fallback_blueprint(rules_text, population, duration_days, proposed_change)
 
         # Some LLMs occasionally return a list (e.g. citizens array) instead of
         # a blueprint object. Wrap it defensively so the rest of the code keeps
         # working.
         if isinstance(data, list):
-            logger.warning("World blueprint came back as a list, treating as fallback")
+            logger.warning("世界蓝图返回了列表，将使用备用世界")
             return self._fallback_blueprint(rules_text, population, duration_days, proposed_change)
 
         try:
@@ -135,7 +136,7 @@ active_agents_per_round_max should be about {max(3, int(population * 0.4))}"""
                 time_config=time_config,
             )
         except Exception as e:
-            logger.error("Failed to parse world blueprint: %s", e)
+            logger.error("世界蓝图解析失败：%s", e)
             return self._fallback_blueprint(rules_text, population, duration_days, proposed_change)
 
     @staticmethod
@@ -209,4 +210,4 @@ active_agents_per_round_max should be about {max(3, int(population * 0.4))}"""
                 active_agents_per_round_min=3,
                 active_agents_per_round_max=max(3, int(population * 0.4)),
             ),
-        )
+        )