Search Results for "multi-threaded" - Page 29

Showing 7596 open source projects for "multi-threaded"

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  • 1
    macai

    macai

    All-in-one native macOS AI chat application

    ...The application also emphasizes privacy by avoiding telemetry and offering optional iCloud synchronization for cross-device continuity. With its combination of native performance, multi-provider flexibility, and user-friendly design, macai serves as a comprehensive AI hub for macOS users.
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  • 2
    Artalk

    Artalk

    Your Self-hosted Comment System

    ...The system is framework-agnostic, allowing it to be integrated into virtually any frontend stack without dependency conflicts or heavy client-side overhead. Artalk emphasizes flexibility and control by offering features such as multi-site management, moderation tools, and plugin extensibility, making it suitable for both personal blogs and larger content platforms. It also includes user engagement features like voting, nested comments, and notifications, which enhance interaction while maintaining performance.
    Downloads: 0 This Week
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  • 3
    pi-autoresearch

    pi-autoresearch

    Autonomous experiment loop extension for pi

    ...The system likely integrates with external data sources or APIs to retrieve information and process it into structured insights. Its architecture suggests a focus on autonomy, allowing it to run multi-step research pipelines that mimic human investigative processes. This makes it particularly useful for exploratory analysis, trend discovery, or generating structured knowledge from large information spaces. Overall, pi-autoresearch represents a step toward self-directed research agents capable of producing increasingly refined outputs over time.
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  • 4
    Code-Graph-RAG

    Code-Graph-RAG

    The ultimate RAG for your monorepo

    Code-Graph-RAG is an advanced retrieval-augmented generation system designed specifically for understanding and interacting with large, multi-language codebases by transforming them into structured knowledge graphs. It uses Tree-sitter to parse source code into abstract syntax trees, extracting relationships between functions, classes, and modules to build a graph-based representation of the entire codebase. This structured approach enables more accurate and context-aware querying compared to traditional text-based search methods, allowing users to ask natural language questions about code structure and functionality. ...
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  • 5
    Datapizza AI

    Datapizza AI

    Build reliable Gen AI solutions without overhead

    Datapizza AI is a lightweight framework for building modular, multi-agent AI systems that collaborate to solve complex tasks through orchestration and tool usage. The project focuses on simplicity and transparency, enabling developers to construct agent-based workflows without the heavy abstractions and dependencies often found in larger AI frameworks. It provides a flexible architecture where individual agents can be assigned specialized roles, such as web search, reasoning, or domain-specific expertise, and can communicate with each other to complete tasks collaboratively. ...
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  • 6
    Deep Research Web UI

    Deep Research Web UI

    AI-powered research assistant that performs iterative, deep research

    Deep Research Web UI is an AI-powered research assistant interface designed to automate complex, multi-step information gathering workflows through a combination of search engines, web scraping, and large language models. It operates as a front-end system for deep research agents that iteratively refine queries, retrieve information from multiple sources, and synthesize structured outputs into coherent reports. The platform emphasizes long-horizon reasoning, allowing users to explore topics in depth rather than receiving shallow, single-response answers. ...
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  • 7
    MiroThinker

    MiroThinker

    MiroThinker is an open source deep research agent

    ...The system focuses on enabling long-horizon research workflows by allowing the agent to interact repeatedly with external tools, search systems, and data sources while refining its reasoning through iterative steps. Rather than simply generating responses from a single prompt, the agent performs structured multi-step reasoning processes that involve searching for information, analyzing evidence, and synthesizing conclusions. The platform is optimized for research tasks such as financial forecasting, knowledge discovery, and large-scale information synthesis. MiroThinker has been evaluated on several agent benchmarks and has demonstrated strong performance on tests designed to measure deep research capabilities.
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  • 8
    Autonomous Agents

    Autonomous Agents

    Autonomous Agents (LLMs) research papers. Updated Daily

    Autonomous-Agents is a research-focused repository that collects implementations, experiments, and academic resources related to autonomous multi-agent systems and intelligent robotics. The project explores how multiple agents can cooperate and interact with complex environments through machine learning, imitation learning, and multimodal sensing. It includes frameworks that integrate visual perception, tactile sensing, and spatial reasoning to guide the actions of robotic agents during manipulation or collaborative tasks. ...
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  • 9
    OM1

    OM1

    Modular AI runtime for robots

    OM1 is an open-source AI platform designed to build autonomous agents capable of interacting with digital environments and completing complex tasks. The project focuses on creating a modular architecture where language models can coordinate with external tools, APIs, and knowledge sources to accomplish multi-step objectives. Instead of operating as simple conversational systems, OM1 agents can plan actions, retrieve information, and execute tasks across different services. The framework integrates reasoning modules, planning strategies, and tool interfaces that allow agents to operate in dynamic environments. Developers can extend the system by connecting new tools, services, or data sources to the agent architecture. ...
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  • 10
    BettaFish

    BettaFish

    Public opinion analysis system

    BettaFish is an open-source, multi-agent public opinion analysis system built to automate the collection, deep analysis, and reporting of social media data at scale through conversational queries. It uses a modular architecture of specialized agents that collaborate to crawl mainstream platforms, extract multimodal content like text and short video, and synthesize insights through both statistical and large language model techniques.
    Downloads: 0 This Week
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  • 11
    Warracker

    Warracker

    Self-hostable warranty tracker to monitor expirations, store receipts

    ...It includes proactive notifications for upcoming expirations via various push or email services, robust search and filtering to quickly find warranties by product name or serial number, and the ability to handle multiple serial numbers per product. Designed for self-hosting with Docker and containerization support, the platform is mobile-friendly and supports multi-user environments with role-based access control and optional single sign-on through providers like Google or GitHub.
    Downloads: 0 This Week
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  • 12
    Loggifly

    Loggifly

    Get Alerts from your Docker Container Logs

    ...Instead of manually scanning logs for issues or relying solely on centralized monitoring stacks, LoggiFly proactively inspects streams of container output and notifies users through services like Ntfy, Slack, Discord, Telegram, or webhooks when significant events occur. It supports plain text, regex, and multi-line pattern matching, and its flexible alert templating lets operators tailor messages for clarity and context, including attaching relevant log excerpts. Beyond notifications, LoggiFly can take automated actions such as restarting or stopping containers when specific critical patterns are detected, which is especially useful for preventing damage from misbehaving services.
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  • 13
    OpenTinker

    OpenTinker

    OpenTinker is an RL-as-a-Service infrastructure for foundation models

    ...It introduces a centralized scheduler to manage distributed training jobs and shared compute resources, enabling workloads like reinforcement learning, supervised fine-tuning, and inference to run across multiple settings. The architecture supports a range of single-turn and multi-turn agentic tasks with a design that abstracts away infrastructure complexity while offering flexible Python APIs to define environments and workflows.
    Downloads: 0 This Week
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  • 14
    AutoMaker

    AutoMaker

    Start directing AI agents

    ...Instead of writing every line of code by hand, users add feature cards to a Kanban board with natural language descriptions, and AI agents powered by the Claude Agent SDK handle multi-step tasks such as planning, generating code, running tests, and committing to an isolated git worktree. The core idea is to shift developers’ focus from mechanical coding to high-level architectural and product decisions while retaining control through review and approval of generated changes. Built with tools like React, Vite, Electron, and Express, Automaker offers both web and desktop workflows with real-time streaming of agent activity and visibility into progress.
    Downloads: 0 This Week
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  • 15
    X For You Feed Algorithm

    X For You Feed Algorithm

    Algorithm powering the For You feed on X

    X For You Feed Algorithm is the open-sourced core recommendation system that powers the For You feed on X (the social network formerly known as Twitter), and it represents one of the first times a major social platform has published production-level ranking code for public review and experimentation. The repository contains the full pipeline that ingests user engagement and content candidate data, processes it through retrieval, hydration, filtering, scoring, and selection layers, and...
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  • 16
    agentgateway

    agentgateway

    Next Generation Agentic Proxy for AI Agents and MCP servers

    ...The project supports interoperable protocols designed for this ecosystem, including Agent2Agent (A2A) and Model Context Protocol (MCP), which helps standardize how tools and agents interoperate. It is designed for performance and scale, implemented in Rust and engineered to handle large throughput and multi-tenant deployments. Operationally, it emphasizes safety and control with an RBAC system tuned for MCP/A2A use cases, plus the ability to update configuration dynamically via xDS without downtime.
    Downloads: 0 This Week
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  • 17
    Docker Curriculum

    Docker Curriculum

    A comprehensive tutorial on getting started with Docker

    Docker Curriculum is a hands-on tutorial that teaches Docker from first principles to practical deployment through a sequence of guided exercises. It starts with images and containers, then layers on volumes, networks, and multi-container composition so learners grasp how pieces fit together. The material emphasizes doing over reading: you build images, run services, and push to registries as you go, reinforcing concepts with real commands. It also connects Docker to everyday developer workflows, covering topics like local development setups, environment variables, and debugging techniques. ...
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  • 18
    yamlfmt

    yamlfmt

    An extensible command line tool or library to format yaml files

    yamlfmt is an extensible formatter that makes YAML files consistent and easy to read across large repositories. It focuses on practical concerns unique to YAML—multi-document streams, anchors and aliases, comments, and block scalars—so a reformat doesn’t destroy semantics or helpful annotations. The tool ships as a single, distributable binary and can also be used as a library, making it simple to drop into CI and editor workflows. Configuration is file-based, allowing teams to pin indentation, line wrapping, and other house-style choices repo-wide. ...
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  • 19
    ML for Beginners

    ML for Beginners

    12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

    ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The repository includes quizzes, solutions, and instructor materials to make the content usable in classrooms or self-study. ...
    Downloads: 0 This Week
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  • 20
    HunyuanCustom

    HunyuanCustom

    Multimodal-Driven Architecture for Customized Video Generation

    ...The architecture builds on HunyuanVideo, with added modules for identity reinforcement and modality-specific condition injection. Text-image fusion module based on LLaVA for improved multimodal understanding. Applicable to single- and multi-subject scenarios, video editing/replacement, singing avatars etc.
    Downloads: 0 This Week
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  • 21
    Tesseral

    Tesseral

    Open source auth infrastructure for B2B SaaS

    Tesseral is an open-source authentication and identity management platform tailored for B2B SaaS applications, offering enterprise-grade features like SAML SSO, SCIM provisioning, RBAC, API key management, and audit logging through a unified API-first service. Tesseral is a multi-tenant, API-first service designed to run on the cloud. It is not an authentication library tied to a particular language or framework; Tesseral works with any tech stack. Tesseral is open source auth infrastructure for business software (i.e., B2B SaaS). Tesseral is built for B2B SaaS. Your customer's admins control how their users log in to their tenant, and can add or remove users at will.
    Downloads: 0 This Week
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  • 22
    DataFrame

    DataFrame

    C++ DataFrame for statistical, Financial, and ML analysis

    ...You can join, merge, and group-by the data. You can run various statistical, summarization, financial, and ML algorithms on the data. You can add your custom algorithms easily. You can multi-column sort, custom pick, and delete the data. DataFrame also includes a large collection of analytical algorithms in the form of visitors. These are from basic stats such as Mean, and Std Deviation and return, … to more involved analysis such as Affinity Propagation, Polynomial Fit, and Fast Fourier transform of arbitrary length … including a good collection of trading indicators. ...
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  • 23
    Roboquant

    Roboquant

    User-friendly and completely free algorithmic trading platform

    Roboquant is an open-source algorithmic trading platform written in Kotlin. It is flexible, user-friendly and completely free to use. It is designed for anyone serious about algo-trading. So whether you are a beginning retail trader or an established trading firm, Roboquant can help you to quickly develop robust and fully automated trading strategies. But perhaps most important of all, it is blazingly fast. Roboquant is orders of magnitude faster than most other algo-trading platforms. With...
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  • 24
    ImplicitGlobalGrid.jl

    ImplicitGlobalGrid.jl

    Distributed parallelization of stencil-based GPU and CPU applications

    ImplicitGlobalGrid is an outcome of a collaboration of the Swiss National Supercomputing Centre, ETH Zurich (Dr. Samuel Omlin) with Stanford University (Dr. Ludovic Räss) and the Swiss Geocomputing Centre (Prof. Yuri Podladchikov). It renders the distributed parallelization of stencil-based GPU and CPU applications on a regular staggered grid almost trivial and enables close to ideal weak scaling of real-world applications on thousands of GPUs [1, 2, 3]. ImplicitGlobalGrid relies on the...
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  • 25
    Ludwig AI

    Ludwig AI

    Low-code framework for building custom LLMs, neural networks

    ...Ludwig is a low-code framework for building custom AI models like LLMs and other deep 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. ...
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