Search Results for "kotlin"
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Showing 16 open source projects for "kotlin"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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OpenAI API client for Kotlin
OpenAI API client for Kotlin with multiplatform capabilities
OpenAI API client for Kotlin with multiplatform and coroutines capabilities. -
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Koog
Koog is the official Kotlin framework for building AI agents
Koog is a Kotlin‑based framework for building and running AI agents entirely in idiomatic Kotlin, supporting both single‑run agents that process individual inputs and complex workflow agents with custom strategies and configurations. It features pure Kotlin implementation, seamless Model Control Protocol (MCP) integration for enhanced model management, vector embeddings for semantic search, and a flexible system for creating and extending tools that access external systems and APIs. ... -
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AutoDev
The AI-powered coding wizard
The AI-powered coding wizard with multilingual support, auto code generation, and a helpful bug-slaying assistant. Customizable prompts and a magic Auto Dev/Testing/Document/Agent feature are included. -
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RunVSAgent
Run VSCode-based coding agents and extensions seamlessly
...It is designed to bridge the VS Code agent ecosystem with editors such as IntelliJ IDEA, WebStorm, PyCharm, PhpStorm, CLion, GoLand, Rider, Android Studio, and more. The project uses a Kotlin-based JetBrains plugin, a Node.js extension host, an editor bridge, and RPC communication to provide VS Code API compatibility outside VS Code. It supports agents such as Roo Code, Cline, and Kilo Code, making them available in IDEs where they would not normally run. This helps developers keep their preferred IDE while still using popular VS Code-native AI coding tools. ... -
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sherpa-onnx
Speech-to-text, text-to-speech, and speaker recognition
Speech-to-text, text-to-speech, and speaker recognition using next-gen Kaldi with onnxruntime without an Internet connection. Support embedded systems, Android, iOS, Raspberry Pi, RISC-V, x86_64 servers, websocket server/client, C/C++, Python, Kotlin, C#, Go, NodeJS, Java, Swift, Dart, JavaScript, Flutter. -
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Gradle MCP Server
A Model Context Protocol (MCP) server
The Gradle MCP Server is a Model Context Protocol implementation that enables AI tools to interact programmatically with Gradle projects. It uses the Gradle Tooling API to query project information and execute tasks, facilitating seamless integration with AI-driven development tools. -
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Shire
Empower Your Dev Ecosystem with AI Agents
Shire is an AI-driven development ecosystem that empowers developers with AI agents to automate coding tasks, enhance productivity, and elevate code quality. The concept of Shire has its roots in AutoDev, a subproject of UnitMesh. Within AutoDev, we envisioned an AI-driven integrated development environment for developers, which included Shire’s predecessor, DevIns. DevIns was designed to empower users to create custom AI agents tailored to their own IDEs, thus forging a personalized... -
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multi-agent-shogun
Samurai-inspired multi-agent system for Claude Code
multi-agent-shogun is a multi-agent orchestration system designed to coordinate multiple AI coding agents working in parallel. Inspired by the hierarchy of a feudal Japanese military structure, the system organizes agents into roles such as Shogun, Karo, and Ashigaru, which correspond to strategist, coordinator, and worker agents. A user interacts primarily with the Shogun agent by issuing natural language instructions that describe the desired tasks. The system then automatically... -
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Embabel Agent Framework
Agent framework for the JVM. Pronounced Em-BAY-bel
Embabel Agent Framework is a JVM-based framework for building advanced AI agent systems that combine structured programming with large language model interactions to execute complex, goal-oriented workflows. The framework introduces a planning-driven approach where agents dynamically determine sequences of actions required to achieve objectives, rather than relying on fixed pipelines or predefined flows. It models agent behavior through concepts such as goals, actions, and conditions,... -
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Voqal
Natural speech programming assistant for the software developers
Voqal is a programming assistant built for software developers looking to enhance their productivity with natural speech programming. Using Voqal, you can navigate, write, run, and debug software in JetBrains IDEs using your voice. Write code faster, reduce repetitive strain injuries, and improve focus and productivity. Voqal is promptable and privacy-focused, allowing you to customize your experience and control your data. -
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ProxyAI
The leading open-source AI copilot for JetBrains
ProxyAI is an open-source AI-powered coding assistant designed primarily for JetBrains IDEs, offering a highly customizable alternative to tools like GitHub Copilot while maintaining flexibility across multiple AI providers and deployment environments. It allows developers to connect to a wide range of language models, including cloud-based services and locally hosted models, enabling both online and fully offline workflows depending on user preferences. The platform emphasizes deep... -
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RunAnywhere
Production ready toolkit to run AI locally
RunAnywhere SDKs are a set of cross-platform development tools that enable applications to run artificial intelligence models directly on user devices instead of relying on cloud infrastructure. The toolkit allows developers to integrate language models, speech recognition, and voice synthesis capabilities into mobile or desktop applications while keeping all computation local. By running models entirely on device, the platform eliminates network latency and protects user data because... -
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Model Context Protocol (MCP)
Specification and documentation for the Model Context Protocol
...It gives developers a consistent way to expose tools, prompts, resources, and server capabilities to language models. Its broader ecosystem supports many languages, including TypeScript, Python, Java, Kotlin, C#, Go, PHP, Ruby, Rust, and Swift. -
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Discord4J
Reactive library to enable quick and easy development of bots
Discord4J is a fast, powerful, unopinionated, reactive library to enable quick and easy development of Discord bots for Java, Kotlin, and other JVM languages using the official Discord Bot API. Discord4J follows the reactive-streams protocol to ensure Discord bots run smoothly and efficiently regardless of size. Automatic rate-limiting, automatic reconnection strategies, and consistent naming conventions are among the many features Discord4J offers to ensure your Discord bots run-up to Discord's specifications and to provide the least amount of surprises when interacting with our library. ... -
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askimo
AI desktop app with local RAG, privacy-first, multi-model support
Askimo is an open-source, privacy-first AI desktop application designed to help users work with multiple AI models from a single, consistent interface. It supports popular AI providers such as OpenAI, Anthropic (Claude), Gemini, Ollama, LocalAI, Docker AI, LM Studio, and X AI, allowing users to switch models easily without vendor lock-in. A core feature of Askimo is Retrieval-Augmented Generation (RAG). Users can connect the app to local files, documents, and project folders so the AI can... -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning models in production environments.
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