Search Results for "multi-threaded" - Page 4
Sort By:
Showing 1086 open source projects for "multi-threaded"
View related business solutions-
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.
-
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.
-
1
llmfit
157 models, 30 providers, one command to find what runs on hardware
...It provides both an interactive terminal user interface and a traditional CLI mode, enabling flexible workflows for different user preferences. llmfit also supports advanced configurations including multi-GPU setups, mixture-of-experts architectures, and dynamic quantization recommendations. By presenting clear performance estimates and compatibility guidance, the project reduces the trial-and-error typically involved in local LLM experimentation. Overall, llmfit serves as a practical decision assistant for developers who want to run language models efficiently on their own machines. -
2
Feynman
The open source AI research agent
...It operates as a “Claude Code for research,” allowing users to input natural language queries and receive fully developed, source-grounded research briefs, literature reviews, or experimental analyses. The system is built around a multi-agent architecture that includes roles such as researcher, reviewer, writer, and verifier, each responsible for a specific stage of the research pipeline. It supports advanced workflows like deep research investigations, paper replication, peer review simulation, and autonomous experimentation, enabling users to go beyond simple question answering into full research automation. -
3
Swarms
Enterprise multi-agent orchestration framework for scalable AI apps
Swarms is an enterprise-grade multi-agent orchestration framework designed to help developers build, manage, and scale collaborative AI systems composed of multiple agents. It provides a structured infrastructure for coordinating agents in hierarchical, parallel, or sequential workflows, enabling complex task execution across distributed components. It emphasizes production readiness, offering modular architecture, high availability, and observability features suitable for large-scale deployments. ... -
4
ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
-
5
SALMONN family
A suite of advanced multi-modal LLMs
...SALMONN aims to push the frontier of multi-modal AI by allowing models to process and reason over diverse inputs, which can be useful for applications such as video understanding, speech analytics, cross-modal retrieval, and general AI capable of interpreting rich, multi-sensory data. By open-sourcing SALMONN, ByteDance enables researchers and developers to build on its architecture, experiment with new modalities or tasks, and contribute to the growing ecosystem of multi-modal LLMs. -
6
Appfl
Advanced Privacy-Preserving Federated Learning framework
APPFL (Advanced Privacy-Preserving Federated Learning) is a Python framework enabling researchers to easily build and benchmark privacy-aware federated learning solutions. It supports flexible algorithm development, differential privacy, secure communications, and runs efficiently on HPC and multi-GPU setups. -
7
Qwen3.5
Qwen3.5 is the large language model series developed by Qwen team
Qwen3.5 is part of Alibaba’s Qwen family of large language and multimodal foundation models, designed to power advanced AI applications such as chatbots, coding assistants, and autonomous agents. The project represents a significant step toward “agentic AI,” meaning models that can reason through multi-step tasks and interact with external tools or environments rather than only generating text. Qwen3.5 builds on earlier Qwen generations by improving multilingual understanding, reasoning ability, and efficiency, while also introducing native multimodal capabilities that allow the model to work with both language and visual inputs. ... -
8
ContextForge MCP Gateway
A Model Context Protocol (MCP) Gateway & Registry
...It exposes an MCP-compliant interface to clients while handling discovery, authentication, rate limiting, retries, and observability on the server side. The gateway scales horizontally, supports multi-cluster deployments on Kubernetes, and uses Redis for federation and caching across instances. Operators can define virtual servers, wire multiple transports, and optionally enable an admin UI for management and monitoring. Packaged for quick starts via PyPI and Docker, it targets production reliability with health checks, metrics, and structured logs. ... -
9
Image Fusion
Deep Learning-based Image Fusion: A Survey
...Survey style description of method taxonomy, architectures, loss types. Compilation of many state-of-the-art image fusion methods (infrared + visible, multi-focus, multi-exposure). Survey style description of method taxonomy, architectures, loss types. -
Atera - an All-in-one platform for IT managementYour IT essentials, integrated & elevated. Take your IT management from automated to autonomous, download Atera's agent to start your free trial!
-
10
ONNX Runtime
ONNX Runtime: cross-platform, high performance ML inferencing
...ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Support for a variety of frameworks, operating systems and hardware platforms. Built-in optimizations that deliver up to 17X faster inferencing and up to 1.4X faster training. -
11
Flock
Flock is a workflow-based low-code platform for building chatbots
...The platform supports multi-agent collaboration, allowing developers to design workflows where different agents handle specialized tasks within the same system. Flock also includes features such as intent recognition, code execution nodes, and human-in-the-loop approval processes that make it suitable for production AI applications. -
12
Claude Cognitive
Persistent context and multi-instance coordination
Claude Cognitive is an advanced memory and context-management extension designed to address the stateless limitations of Claude Code by giving the model a form of persistent “working memory” and multi-instance coordination. It introduces an attention-based context router that prioritizes files and content relevant to the current development discussion — tagging them as HOT, WARM, or COLD based on recency and keyword activation — so Claude Code doesn’t waste token budget rereading irrelevant code. This context routing dramatically reduces redundant token usage and accelerates large codebase interactions by focusing only on what truly matters to the current task. ... -
13
cuML
RAPIDS Machine Learning Library
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU... -
14
CowAgent
AI assistant based on large models that can actively think and plan
...The platform has evolved beyond a simple chatbot into a more autonomous agent capable of planning complex tasks, maintaining long-term memory, and invoking external tools to complete workflows. It supports multi-turn conversations with per-user context tracking, allowing more natural and persistent interactions across private and group chats. Developers can extend functionality through a plugin architecture and customizable rules, making it suitable for both personal assistants and enterprise automation scenarios. -
15
OpenAI Swarm
Educational framework exploring multi-agent orchestration
Swarm focuses on making agent coordination and execution lightweight, highly controllable, and easily testable. It accomplishes this through two primitive abstractions; Agents and handoffs. An Agent encompasses instructions and tools, and can at any point choose to hand off a conversation to another Agent. These primitives are powerful enough to express rich dynamics between tools and networks of agents, allowing you to build scalable, real-world solutions while avoiding a steep learning... -
16
Ralph Orchestrator
An improved implementation of the Ralph Wiggum technique
...The system emphasizes modularity and composability, allowing developers to design workflows as reusable building blocks that can be combined or extended as needed. It supports asynchronous execution and task coordination, enabling efficient handling of multi-step processes that involve decision-making and conditional branching. Ralph Orchestrator is particularly useful for building agent-based systems, automation pipelines, and AI-driven applications that require coordination across multiple services. It also includes logging and monitoring capabilities to track workflow execution and debug issues effectively. -
17
Build Your Own OpenClaw
A step-by-step guide to build your own AI agent
Build Your Own OpenClaw is a step-by-step educational framework that teaches developers how to construct a fully functional AI agent system from scratch, gradually evolving from a simple chat loop into a multi-agent, production-ready architecture. The project is structured into 18 progressive stages, each introducing a new concept such as tool usage, memory persistence, event-driven design, and multi-agent coordination, with each step including both explanatory documentation and runnable code. It begins with foundational concepts like conversational loops and tool integration, then expands into more advanced capabilities such as dynamic skill loading, web interaction, and context management. ... -
18
Spring AI Alibaba Examples
Spring AI Alibaba examples for building and testing AI apps
...Each module focuses on a specific use case such as chat, image processing, audio handling, graph workflows, and retrieval-augmented generation. The examples highlight how to integrate AI models, manage prompts, handle memory, and build multi-model or multi-agent workflows. Developers can explore individual project folders for detailed instructions and implementation guidance. Spring AI Alibaba Examples also supports experimentation through playground modules and encourages contributions to expand real-world AI use cases and improve development practices. -
19
StableSwarmUI
Multi-user UI for managing and running Stable Diffusion workflows tool
StableSwarmUI is a web-based interface designed to manage and coordinate Stable Diffusion image generation workflows in a multi-user environment. It focuses on enabling multiple users to interact with shared resources, making it suitable for collaborative or server-based deployments. It provides a centralized system where users can submit, monitor, and manage generation tasks through a browser interface. It abstracts much of the complexity involved in running diffusion models by offering a structured environment for handling prompts, outputs, and processing queues. ... -
20
super-agent-party
All-in-one AI companion! Desktop girlfriend + virtual streamer
...The platform is primarily intended as a research and demonstration environment for experimenting with agent collaboration strategies. Developers can use it to study coordination patterns, communication protocols, and task decomposition in multi-agent systems. -
21
Hermes Agent
The agent that grows with you
Hermes Agent is a fully open-source autonomous AI agent designed to run persistently on your own machine or server, becoming more capable the longer it operates by learning from experience and building reusable procedural skills. Rather than functioning as a stateless chatbot, it maintains long-term memory across sessions and can generate searchable “Skill Documents” that capture how it solved complex tasks so it doesn’t start from scratch each time. The agent interfaces with messaging... -
22
Inkeep
Create AI Agents in a No-Code Visual Builder or TypeScript SDK
Inkeep is an open-source framework for building and deploying AI agent workflows and interactive assistants that operate autonomously across applications, enterprise environments, and customer engagement use cases. It lets developers and non-technical users create, manage, and orchestrate multi-agent systems using both a no-code visual builder and a full TypeScript SDK, giving two ways to define agent behaviors that stay in sync with each other. Agents built with this framework can act as real-time conversational assistants — for example, handling help desk inquiries, providing internal support to teams, or driving in-app experiences — and they can be extended to automate multi-step tasks that interact with external systems like CRMs, knowledge bases, or ticketing systems. ... -
23
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 infer steps, refine them, and adapt plans even when users cannot fully specify implementation details up front. It also describes resource orchestration and iterative self-improvement behaviors, including controlled code generation for building tools and agent capabilities when needed. ... -
24
Constellation
Constellation is the first Confidential Kubernetes
...Built on top of Kubernetes and using technologies like Intel SGX and Gramine, Constellation guarantees that not even infrastructure operators can access data or code, making it ideal for privacy-sensitive workloads and multi-party computation scenarios. -
25
Accomplish
Accomplish is the open source Al coworker that lives on your desktop
...It supports integration with multiple AI providers or local models, giving users flexibility in how intelligence is powered. Accomplish emphasizes autonomy, allowing it to execute multi-step tasks without constant supervision. Its design focuses on replacing repetitive manual workflows with intelligent automation. Overall, it acts as a personal AI coworker embedded in the desktop environment.
