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Source channel @lambdaexpression · Post #206 · 4月20日

前段时间一直被MajdataPlay的外键输入问题困扰:有玩家反映majplay会无征兆地出现拖判和吃音,但是内屏一切正常 因为我是第一次接触游戏开发,IO这方面也完全没经验 一开始我和bb本怀疑是线程调度的问题,即:IO线程时间片被其他线程挤占了,导致IO线程无法及时处理HID设备回报。为了验证这个猜想,我们尝试提高了IO线程的优先级,照旧 接下来我怀疑是我那套框架有问题:majplay是根据上一帧与这一帧的按键状态判断按键是不是"click"。为此我重写了这部分的实现,改进了IO线程与主线程之间的交互,问题照旧....... 到这里我已经怀疑这不是majplay的锅:IO线程没有任何异常,IO线程与主线程的交互没有问题,Note判定逻辑也没有问题,那就是设备确实没有回报给majplay或者设备发过来的回报中按键确实没有按下,但是大佬说hdd没有这种问题.....(人已经快崩溃了,这完全看不透也摸不着,因为我用单片机模拟玩家打高速纵连是完全没有问题的,我在家里用手台测试也没有问题) 到最后,bb本灵光一闪,说有没有可能是led刷新率过高,把按键控制板干爆炸了?我们让大佬把led刷新间隔从16ms改成100ms,吃音问题瞬间没有了,无语了 。。。。。。。。。。。。。。。。。。。。 adx是一个控制板同时管理按键和led,为什么我没有遇到吃音问题呢,因为我的手台不是adx的... #dev

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GitHub Trends

@githubtrending · Post #14663 · 2025/05/02 12:30

#python#agents#ai#ai_agents#api#developer_tools#function_calling#integration#llm#mcp#oauth2#open_source#permissions#tools ACI.dev is an open-source platform that helps build AI agents by providing easy access to over 600 tools. It simplifies authentication and tool integration, allowing AI agents to work with many services like Google Calendar and Slack without needing separate setups. This platform offers multi-tenant authentication, flexible access methods, and natural language permissions, making it easier to manage and secure AI agent capabilities. It's open-source and works with any framework, which means you can build AI agents without worrying about vendor lock-in. https://github.com/aipotheosis-labs/aci

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@githubtrending · Post #15214 · 2025/10/12 11:30

#python#agents#ai#ai_agents#api#developer_tools#discord#function_calling#integration#llm#mcp#mcp_client#mcp_server#oauth2#open_source Klavis AI helps developers connect AI tools to other services like GitHub, Gmail, and Slack easily. It offers hosted servers that handle authentication and client code automatically, making it simpler to integrate AI with various platforms. This saves time and effort by eliminating the need for custom authentication management and client library maintenance. Users can quickly set up and scale their AI applications without worrying about complex integrations, making it easier to deploy AI-powered workflows securely and efficiently. https://github.com/Klavis-AI/klavis

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@githubtrending · Post #15556 · 2026/03/12 12:30

#typescript#ai#ai_agents#coding#deno#embeddings#insforge#nextjs#oauth2#pgvector#postgresql#realtime#vectors#websockets InsForge is an open-source backend platform for AI coding agents, offering easy auth, Postgres database, S3 storage, edge functions, and model gateway via a simple semantic layer. Agents fetch context, configure services, and inspect state to build full-stack apps quickly. Set up locally with Docker or use cloud deploys. It boosts agent accuracy 1.7x, speed 1.6x, and cuts tokens 30% vs. rivals, letting you prototype and ship AI-driven apps faster with less hassle and cost. https://github.com/InsForge/InsForge

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@githubtrending · Post #14691 · 2025/05/10 00:00

#csharp#architecture#aspnetcore#clean_architecture#cqrs#ddd#dotnet#dotnetcore#event_driven_architecture#event_sourcing#kubernetes#masstransit#messaging#microservice#microservices#oauth2#opentelemetry#software_architecture#software_design#software_engineering#vertical_slice_architecture Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5]. https://github.com/meysamhadeli/monolith-to-cloud-architecture