Search Results for "runtime full"
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Showing 25 open source projects for "runtime full"
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Bolt.new
Prompt, run, edit, and deploy full-stack web applications
Bolt.new is an AI-powered full-stack development platform created by StackBlitz that enables users to build, run, edit, and deploy complete web applications directly from the browser without requiring any local setup or traditional development environment. It operates as an intelligent coding agent where users describe what they want to build in natural language, and the system generates functional applications, including frontend, backend, and infrastructure components. The platform is... -
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SWIFT LLM
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs
SWIFT LLM is a comprehensive framework developed within the ModelScope ecosystem for training, fine-tuning, evaluating, and deploying large language models and multimodal models. The platform provides a full machine learning pipeline that supports tasks ranging from model pre-training to reinforcement learning alignment techniques. It integrates with popular inference engines such as vLLM and LMDeploy to accelerate deployment and runtime performance. The framework also includes support for many modern training strategies, including preference learning methods and parameter-efficient fine-tuning techniques. ms-swift is designed to work with hundreds of language and multimodal models, providing a unified environment for experimentation and production deployment. -
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Grok Build
SpaceXAI's coding agent harness and TUI. Fullscreen, mouse interactive
Grok Build is a terminal-based AI coding agent that operates through a full-screen text interface. It can inspect repositories, edit files, run shell commands, search the web, and coordinate longer development tasks. Users can work interactively, invoke it headlessly in scripts or CI, or connect it to editors through the Agent Client Protocol. The Rust codebase includes separate components for the interface, agent runtime, tools, workspace control, configuration, and sandboxing. ... -
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Monty
A minimal, secure Python interpreter written in Rust for use by AI
...The project’s core goal is to enable code execution in environments where untrusted or model-produced code must be tightly sandboxed to reduce risk. Rather than offering a full “general-purpose Python runtime with everything enabled,” Monty is designed to be minimal and controlled, making it easier to reason about what code can do and what it cannot. It prioritizes guardrails like resource limits and restricted capabilities, which is especially useful for agentic workflows that need to execute small pieces of Python for data transforms, validation, or tool-like computations. ... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Vercel AI SDK
Build AI-powered applications with React, Svelte, Vue, and Solid
The Vercel AI SDK is a library for building AI-powered streaming text and chat UIs. -
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Crabtalk
Agents daemon that hides nothing
...CrabTalk emphasizes simplicity by avoiding unnecessary abstractions, allowing developers to maintain full control over how agents operate and interact with their environment. One of its key design goals is to address common issues in multi-agent systems, such as context fragmentation and coordination inefficiencies, by providing clearer structure and tighter control over execution. -
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td
Telegram client, in Go. (MTProto API)
Telegram MTProto API client in Go for users and bots. -
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SAG
SQL-Driven RAG Engine
...Documents are first decomposed into atomic semantic events, which are then represented using multidimensional natural language vectors. These vectors allow the system to identify relationships between concepts and construct a graph representation of knowledge at runtime. The architecture also includes a three-stage retrieval pipeline consisting of recall, expansion, and reranking steps to improve search accuracy. The engine integrates semantic vector similarity with traditional full-text search to improve both recall and precision. Because the knowledge graph is generated dynamically, the system can adapt to new information without requiring manual graph maintenance. -
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ExecuTorch
On-device AI across mobile, embedded and edge for PyTorch
ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices including wearables, embedded devices and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of PyTorch models to edge devices. -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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Coze Loop
Next-generation AI Agent Optimization Platform
Coze Loop is a developer-oriented platform that provides full lifecycle management for AI agents, covering everything from prompt engineering to production monitoring. The project aims to simplify the increasingly complex workflow of building reliable AI agents by offering integrated tools for debugging, evaluation, observability, and optimization. Through its visual playground, developers can test prompts interactively and compare outputs across different language models. -
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Latent Box
A collection of awesome-lists for AI, creativity and art. AI
Latent Box is an open-source platform focused on managing, deploying, and interacting with local or self-hosted AI models through a unified interface that simplifies experimentation and usage. It is designed to act as a control layer for running generative models, particularly those related to text and multimodal outputs, while maintaining full ownership of data and infrastructure. The platform emphasizes usability by providing a clean user interface that allows users to load models,... -
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Google Antigravity SDK
Python library for building agents that leverages Google Antigravity
Google Antigravity SDK for Python is a Python library for building AI agents powered by Antigravity and Gemini. It provides a secure, scalable, and stateful infrastructure layer so developers can focus on agent behavior instead of manually implementing the full agent loop. The SDK includes a high-level Agent class for quick setup, as well as lower-level conversation and connection abstractions for more controlled workflows. It supports streaming responses, stateful sessions, custom Python tools, MCP server integration, hooks, policies, and event-driven triggers. The package relies on a compiled runtime binary distributed through platform-specific PyPI wheels, so installation from PyPI is required for normal use. ... -
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Defang
Defang CLI and sample projects
Defang is a developer-centric platform that simplifies the process of developing, deploying, and debugging cloud applications. By leveraging AI-assisted tooling, Defang enables developers to swiftly transition from an idea to a deployed application on their preferred cloud provider. The platform supports multiple programming languages, including Go, JavaScript, and Python, allowing developers to start with sample projects or generate project outlines using natural language prompts. With a... -
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Agentic Coding Flywheel Setup
System tool for beginners wanting agentic engineering capabilities
Agentic Coding Flywheel Setup (ACFS) is a comprehensive environment bootstrap project that configures a full stack of tools for autonomous AI-assisted coding workflows. With a single shell installer, ACFS transforms a fresh compute environment into a ready-to-use development setup that includes modern shells, language runtimes, AI coding agents (like Claude Code, Codex CLI, and Gemini CLI), and a coordinated toolchain for orchestration and safety. The system is designed for developers who... -
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Solon
Java enterprise application development framework
Solon is a full-scenario Java enterprise application framework that positions itself as a lean, high-performance alternative to heavy stacks. It advertises large concurrency gains, lower memory use, much faster startup, and dramatically smaller packages while remaining compatible from Java 8 through Java 24. The framework focuses on restrained APIs and an open ecosystem, with modules that cover web, data, cloud, and microservice patterns. Its messaging emphasizes “replaceable Spring”... -
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
...Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. Retain full control of your models down to the activation functions. Support for hyperparameter optimization, explainability, and rich metric visualizations. ... -
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AutoAgent
AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework
AutoAgent is a fully automated, zero-code LLM agent framework that lets users create agents and workflows using natural language instead of manual coding and configuration. It is structured around modes that cover both “use” and “build” scenarios: a user mode for running a ready-made multi-agent research assistant, plus editors for creating individual agents or multi-agent workflows from conversational requirements. The framework emphasizes self-managing workflow generation, where it can... -
18
Matcha-TTS
A fast TTS architecture with conditional flow matching
Matcha-TTS is a non-autoregressive neural text-to-speech architecture that uses conditional flow matching to generate speech quickly while maintaining natural quality. It models speech as an ODE-based generative process, and conditional flow matching lets it reach high-quality audio in only a few synthesis steps, which greatly reduces latency compared to score-matching diffusion approaches. The model is fully probabilistic, so it can generate diverse realizations of the same text while still... -
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Supertonic
Lightning-fast, on-device TTS, running natively via ONNX
Supertonic is a lightning-fast, on-device text-to-speech system built around ONNX Runtime for maximum speed and portability. It focuses on running entirely locally, eliminating the need for cloud APIs and providing low latency and strong privacy guarantees, even on constrained devices like Raspberry Pi boards and e-readers. The core model is highly compact at around 66 million parameters, yet benchmarks show it can generate speech up to 167× faster than real time on modern consumer hardware... -
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Preswald
Python tool for browser-based interactive data apps in one file
Preswald is an open source Python-based framework and static-site generator designed for building interactive data applications that run entirely in the browser. It packages application logic, data processing, and user interface components into a single self-contained output, enabling easy sharing and deployment without requiring local dependencies. Preswald leverages a WebAssembly runtime along with technologies like Pyodide and DuckDB to execute Python code directly in the browser... -
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OpenClaw Opik Observability Plugin
Official plugin for OpenClaw that exports agent traces to Opik
OpenClaw Opik Observability Plugin is an open-source plugin designed to add observability and monitoring capabilities to OpenClaw autonomous AI agents by exporting operational traces to the Opik observability platform. The project integrates directly with OpenClaw’s plugin architecture so that developers can capture detailed runtime information about how their agents behave while executing tasks. Each time an AI agent performs an action—such as calling a large language model, invoking a tool, accessing memory, or delegating to a sub-agent—the plugin records the full interaction and sends it to Opik for analysis and visualization. This allows developers to inspect inputs, outputs, token usage, latency, and execution flow across complex multi-step agent workflows. ... -
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DragonianVoice
C++ inference library for multiple SVC/TTS
...It uses ONNX Runtime and other backends to accelerate inference, with notes on how different execution providers such as CUDA or DirectML affect operator support and numerical stability. Recent versions integrate with fish-speech via a dedicated fish-speech.cpp subproject using ggml. -
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TagForge
Cross-platform AI tagging and prompt engineering studio
TagForge is a professional, cross-platform desktop application for AI prompt engineering and image tagging. Built on .NET 9 and Avalonia UI, it provides a sleek, high-performance workspace for crafting perfect prompts for Stable Diffusion, FLUX, Midjourney, and other generative AI models. ## Key Capabilities - Multi-model tagging: Specialized generators for Stable Diffusion (tags), FLUX/Midjourney (prose), and custom LLM workflows - Multimodal vision: Extract metadata or generate... -
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TTS-Vue
Microsoft speech synthesis tool, built with Electron
TTS-Vue is a desktop text-to-speech application built with Electron, Vue, ElementPlus, and Vite, focused on using Microsoft’s official Speech API for high-quality neural synthesis. It wraps the Microsoft TTS WebSocket interface in a clean UI so users can paste or load text, choose voices, tweak parameters, and export audio without touching raw API calls. The app supports SSML (Speech Synthesis Markup Language), letting power users specify fine-grained control over pronunciation, pauses,... -
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Graph4NLP
Graph4nlp is the library for the easy use of Graph Neural Networks
Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP). It provides both full implementations of state-of-the-art models for data scientists and also flexible interfaces to build customized models for researchers and developers with whole-pipeline support. Built upon highly-optimized runtime libraries including DGL , Graph4NLP has both high running efficiency and great extensibility. The architecture of Graph4NLP is shown in the following figure, where boxes with dashed lines represent the features under development. ...
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