Showing 2679 open source projects for "multi-system"

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  • 1
    RAG-Survey

    RAG-Survey

    Collecting awesome papers of RAG for AIGC

    RAG-Survey is an open-source research repository that collects and organizes academic papers related to retrieval-augmented generation (RAG) systems used in modern AI applications. Retrieval-augmented generation combines large language models with external knowledge retrieval systems to improve factual accuracy and contextual understanding. The repository functions as a curated catalog of research papers categorized according to a taxonomy proposed in a related survey paper on RAG methods....
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  • 2
    Zero

    Zero

    Experience email the way you want with Mail0

    ...It combines a unified inbox experience with privacy-first architecture so your email data stays under your control without third-party tracking or data harvesting. The system enhances traditional email workflows by integrating AI assistance for tasks such as summarizing messages, suggesting replies, prioritizing conversations, and helping users manage their inbox more intelligently. With a clean, customizable web interface built on modern technologies, Zero makes it pleasant to navigate mail, search through messages, and organize threads without feeling cluttered or slow.
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  • 3
    Claude SEO

    Claude SEO

    Universal SEO skill for Claude Code

    ...It combines 25 sub-skills and 18 specialist agents across technical SEO, content quality, Schema.org markup, GEO and AEO, local SEO, e-commerce, international SEO, backlinks, semantic clustering, and Google API workflows. The system is designed to produce prioritized action plans instead of generic audit notes. Recommendations include first-principle observations, dependency relationships, falsifiability checks, and leading indicators. It can run full site audits, single-page reviews, schema validation, AI search readiness checks, sitemap workflows, local SEO analysis, and SEO reporting. ...
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  • 4
    OpenMonoAgent

    OpenMonoAgent

    Terminal-native coding agent powered by local LLMs

    ...The project emphasizes privacy, local control, and ownership of the model, compute, and project data. It includes a terminal-native workflow, built-in tools, Docker sandboxing, and code intelligence features. The system can run on CPU or GPU and is designed to auto-configure itself when possible. OpenMonoAgent.ai is best suited for developers who want a local AI development stack with no API keys, no cloud dependency, and no telemetry.
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  • 5
    Context Hub

    Context Hub

    Makes coding agents get smarter with every task

    Context Hub is a curated documentation system built to help coding agents write more accurate code. It gives agents versioned, language-specific reference material instead of forcing them to rely on noisy web searches or stale model memory. The project includes a CLI called chub that agents can use to search for available docs, fetch specific API guidance, and request only the files they need.
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  • 6
    Browser Harness

    Browser Harness

    Self-healing browser harness that enables LLMs to complete any task

    Browser Harness is a self-healing browser control system built to give language models direct and flexible access to a real Chrome browser through the Chrome DevTools Protocol. Its main philosophy is minimalism: instead of imposing a rigid framework, it exposes a very thin bridge so the agent can perform browser tasks with almost no abstraction in the way. A defining part of the project is that the agent can write or extend missing helper functions during a task, which is why the repository describes it as self-healing. ...
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  • 7
    Codebase to Course

    Codebase to Course

    A Claude Code skill that turns any codebase into an HTML course

    Codebase to Course is an AI-powered development tool that converts any software repository into a fully interactive educational experience presented as a self-contained HTML course. It is implemented as a skill for Claude Code and is designed to help users understand how a codebase works without requiring a formal computer science background. The tool analyzes the structure and behavior of a project and generates a visually rich, scroll-based course that includes diagrams, animations, and...
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  • 8
    Rust Port

    Rust Port

    The Rust workspace under rust/ is the current systems-language port

    ...It is often used as a sandbox for exploring how large-scale coding agents behave, including their decision-making processes, tool usage, and workflow orchestration. The system likely includes abstractions for handling file systems, executing commands, and maintaining context across sessions, allowing for more persistent and intelligent coding interactions.
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  • 9
    OpenSpace

    OpenSpace

    OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving

    OpenSpace is a self-evolving agent framework designed to improve the performance, efficiency, and collaboration of AI agents through continuous learning and shared knowledge. It introduces a system where agents develop reusable “skills” based on real task execution, allowing them to improve over time without retraining underlying models. The platform emphasizes collective intelligence, enabling multiple agents to share learned behaviors and benefit from each other’s experiences. It also focuses on cost efficiency by reducing redundant computations and reusing successful workflows, significantly lowering token usage in repeated tasks. ...
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  • 10
    Claude Subconscious

    Claude Subconscious

    Give Claude Code a subconscious

    ...It operates as a background agent that continuously observes user interactions, reads project files, and processes session transcripts to build long-term contextual memory. Unlike standard AI interactions that reset between sessions, this system accumulates knowledge over time, allowing it to recall user preferences, project structures, and recurring patterns across multiple sessions. The plugin injects relevant context and guidance back into Claude before each prompt, effectively “whispering” insights that improve continuity and decision-making. It also has access to tools such as file reading, code search, and web browsing, enabling it to perform background analysis and augment responses with deeper context.
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  • 11
    koishi-plugin-novelai

    koishi-plugin-novelai

    Koishi plugin for NovelAI image generation with advanced controls

    ...A customizable banned word list helps filter unwanted content, while timed message recall can automatically delete generated outputs after a set period. Built on Koishi’s modular system, koishi-plugin-novelai can be extended with additional integrations, making it adaptable for different bot environments and use cases.
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  • 12
    Amurex

    Amurex

    World's first AI meeting copilot

    ...It integrates directly into platforms such as Google Meet and Microsoft Teams, allowing it to operate in real time without disrupting the user’s existing environment. The system leverages advanced AI to generate live suggestions during meetings, helping participants respond more effectively and stay aligned with discussion goals. It also captures full transcripts and automatically produces structured summaries, key takeaways, and action items, reducing the need for manual note-taking. Amurex includes features such as late-join recaps and automated follow-up email generation, ensuring that users can stay informed and maintain continuity even when joining meetings late or managing multiple conversations.
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  • 13
    DeepProve

    DeepProve

    Framework to prove inference of ML models blazingly fast

    DeepProve is an advanced cryptographic framework designed to verify machine learning model inference using zero-knowledge proofs, enabling trustless validation of AI computations without exposing underlying data. The project focuses on zkML, a rapidly emerging field that combines machine learning with zero-knowledge cryptography to ensure both privacy and correctness. It supports neural network architectures such as multilayer perceptrons and convolutional neural networks, allowing...
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  • 14
    dots.ocr

    dots.ocr

    Multilingual Document Layout Parsing in a Single Vision-Language Model

    dots.ocr is a cutting-edge multilingual document parsing system built on a unified vision-language model that combines layout detection, text recognition, and structural understanding into a single architecture. Unlike traditional OCR pipelines that rely on multiple specialized components, dots.ocr integrates these processes end-to-end, reducing error propagation and improving consistency across tasks.
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  • 15
    SemTools

    SemTools

    Semantic search and document parsing tools for the command line

    ...The project focuses on enabling developers and AI agents to process large document collections and extract meaningful semantic representations that can be searched efficiently. Built with Rust for performance and reliability, the toolchain provides fast processing of text and structured documents while maintaining low system overhead. SemTools can parse documents, build semantic embeddings, and perform similarity searches across datasets, making it useful for research, knowledge management, and AI-assisted coding workflows. The toolkit is designed to work well with modern AI pipelines, particularly those involving large language models that require structured knowledge retrieval.
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  • 16
    TypeAgent Python

    TypeAgent Python

    Structured RAG: ingest, index, query

    ...Instead of relying solely on free-form prompts, the architecture emphasizes converting natural language interactions into structured representations that can be processed by deterministic software components. This design allows the system to combine the flexibility of language models with the reliability of traditional programming logic. The repository is intended primarily as a research prototype and sample code rather than a production-ready framework, allowing developers to experiment with building AI agents that maintain structured memory and perform tasks through defined actions.
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  • 17
    Humanoid-Gym

    Humanoid-Gym

    Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real

    Humanoid-Gym is a reinforcement learning framework designed to train locomotion and control policies for humanoid robots using high-performance simulation environments. The system is built on top of NVIDIA Isaac Gym, which allows large-scale parallel simulation of robotic environments directly on GPU hardware. Its primary goal is to enable efficient training of humanoid robots in simulation while enabling policies to transfer effectively to real-world hardware without additional training. The framework emphasizes the concept of zero-shot sim-to-real transfer, meaning that behaviors learned in simulation can be deployed directly on physical robots with minimal adjustment. ...
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  • 18
    VoxelMorph

    VoxelMorph

    Unsupervised Learning for Image Registration

    VoxelMorph is an open-source deep learning framework designed for medical image registration, a process that aligns multiple medical scans into a common spatial coordinate system. Traditional image registration techniques typically rely on optimization procedures that must be executed separately for each pair of images, which can be computationally expensive and slow. VoxelMorph approaches the problem using neural networks that learn to predict deformation fields that transform one image so that it aligns with another. ...
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  • 19
    AI Deadlines

    AI Deadlines

    AI conference deadline countdowns

    AI Deadlines is an open-source project that provides a centralized system for tracking important submission deadlines for major artificial intelligence and machine learning conferences. The repository powers a website that displays countdown timers and structured information for top research conferences across subfields such as computer vision, natural language processing, machine learning, and robotics.
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  • 20
    Jina-Serve

    Jina-Serve

    Build multimodal AI applications with cloud-native stack

    Jina Serve is an open-source framework designed for building, deploying, and scaling AI services and machine learning pipelines in production environments. The framework allows developers to create microservices that expose machine learning models through APIs that communicate using protocols such as HTTP, gRPC, and WebSockets. It is built with a cloud-native architecture that supports deployment on local machines, containerized environments, or large orchestration platforms such as...
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  • 21
    BrowserNode

    BrowserNode

    Make websites accessible for AI agents. Automate tasks online

    ...Built as an implementation compatible with the Browser-use ecosystem, Browsernode allows agents to perform actions such as navigating pages, extracting information, filling forms, or interacting with dynamic web interfaces. The system integrates with Playwright to control Chromium-based browsers and execute automation scripts in a reliable environment. Developers can configure the framework to connect to different language model providers so that AI agents can interpret instructions and decide which browser actions to perform.
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  • 22
    RecAI

    RecAI

    Bridging LLM and Recommender System

    RecAI is an open-source research platform developed by Microsoft to explore how large language models can be integrated into modern recommender systems. Traditional recommender systems rely on structured behavioral data such as user interactions and item embeddings, while large language models excel at understanding language and reasoning about user preferences. RecAI aims to bridge these two domains by creating architectures and training methods that allow LLMs to function as intelligent...
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  • 23
    Gollama

    Gollama

    Go manage your Ollama models

    ...Beyond standard model management, Gollama can display metadata such as size, quantization level, model family, and modification date, which helps users compare models quickly. One of its more distinctive capabilities is a VRAM estimation system that can calculate memory requirements, estimate context limits, and help users choose quantization settings that fit available hardware.
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  • 24
    Extractous

    Extractous

    Fast and efficient unstructured data extraction

    ...The project emphasizes performance and low memory usage, and its maintainers describe it as a local-first alternative to heavier extraction stacks. For broader format support, the system combines its Rust core with ahead-of-time compiled Apache Tika shared libraries, which allows it to extend parsing coverage while still avoiding traditional server-based overhead. It also supports OCR for images and scanned documents through Tesseract, making it useful for document ingestion pipelines that include image-based or scanned inputs.
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  • 25
    AI Engineering Academy

    AI Engineering Academy

    Mastering Applied AI, One Concept at a Time

    AI-Engineering.academy is a community-driven educational repository that organizes practical knowledge and learning paths for applied AI engineering. The project aims to make complex AI concepts accessible by structuring them into progressive learning modules covering topics such as prompt engineering, retrieval-augmented generation, LLM deployment, and AI agents. Rather than focusing purely on theoretical explanations, the repository emphasizes hands-on understanding of how modern AI...
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