In the live game, every API call that affected the player’s inventory triggered a write to the corresponding record in our Azure Cosmos database. From a player’s perspective, the game is constantly saving their progress. To achieve parity in the offline game, we exposed two functions in the AOT DLL for getting and setting a player’s inventory (equivalent to the Cosmos DB inventory document). When the game first starts up, the local save file on disk is read and the inventory is loaded into the DLL’s memory. As the various serverless HTTP operations occur throughout gameplay the DLL’s in-memory inventory state gets updated. After these operations, if the inventory was changed, the client fetches the new full inventory state from the DLL and saves it back to disk.
Thinking Mode:选中 Ring 模型后,你会发现它多了一个“深度思考”的 toggle。这背后是基于 RLVR(Reinforcement Learning with Verifiable Rewards)训练的 Dense Reward 机制,能让模型在输出结果前,进行多步推理和自我反思。
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The spot ran on YouTube and video on demand services, including ITV and Channel 5, in November 2025.