Search Results for "linux systems" - Page 9
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Showing 1064 open source projects for "linux systems"
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LandPPT
An LLM-based presentation generation platform
LandPPT is an open-source AI platform that automatically generates professional presentation slides using large language models. The system allows users to create complete PowerPoint presentations simply by entering a topic or uploading source documents such as PDFs, Word files, or Markdown notes. Using natural language processing and structured content generation, the platform produces presentation outlines and converts them into fully formatted slide decks. The application integrates... -
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OpenSandbox
OpenSandbox is a general-purpose sandbox platform for AI applications
OpenSandbox is a general purpose sandbox platform designed to securely run and isolate AI applications and untrusted workloads in controlled environments. The project focuses on providing a unified sandbox API that simplifies the process of executing code safely across different runtime backends. It supports multiple programming languages through SDKs, allowing developers to integrate sandbox capabilities into their systems without building custom isolation layers. The platform is built to... -
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Meetily
Privacy first, AI meeting assistant with 4x faster Parakeet/Whisper
This project is a privacy-first AI meeting assistant that captures meeting audio, produces real-time transcripts, and generates summaries while keeping processing entirely on your own machine or infrastructure. It’s built for organizations that want meeting intelligence without sending recordings or transcripts to third-party cloud services, which helps address compliance and data sovereignty requirements. The app supports live transcription with local model options (including Whisper- and... -
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LLMStack
No-code multi-agent framework to build LLM Agents, workflows
LLMStack is a no-code platform for building generative AI agents, workflows and chatbots, connecting them to your data and business processes. Build tailor-made generative AI agents, applications and chatbots that cater to your unique needs by chaining multiple LLMs. Seamlessly integrate your own data, internal tools and GPT-powered models without any coding experience using LLMStack's no-code builder. Trigger your AI chains from Slack or Discord. Deploy to the cloud or on-premise. -
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HY-World 1.5
A Systematic Framework for Interactive World Modeling
HY-WorldPlay is a Hunyuan AI project focusing on immersive multimodal content generation and interaction within virtual worlds or simulated environments. It aims to empower AI agents with the capability to both understand and generate multimedia content — including text, audio, image, and potentially 3D or game-world elements — enabling lifelike dialogue, environmental interpretations, and responsive world behavior. The platform targets use cases in digital entertainment, game worlds,... -
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VibeVoice
Open-source multi-speaker long-form text-to-speech model
VibeVoice-1.5B is Microsoft’s frontier open-source text-to-speech (TTS) model designed for generating expressive, long-form, multi-speaker conversational audio such as podcasts. Unlike traditional TTS systems, it excels in scalability, speaker consistency, and natural turn-taking for up to 90 minutes of continuous speech with as many as four distinct speakers. A key innovation is its use of continuous acoustic and semantic speech tokenizers operating at an ultra-low frame rate of 7.5 Hz,... -
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HunyuanImage-3.0
A Powerful Native Multimodal Model for Image Generation
HunyuanImage-3.0 is a powerful, native multimodal text-to-image generation model released by Tencent’s Hunyuan team. It unifies multimodal understanding and generation in a single autoregressive framework, combining text and image modalities seamlessly rather than relying on separate image-only diffusion components. It uses a Mixture-of-Experts (MoE) architecture with many expert subnetworks to scale efficiently, deploying only a subset of experts per token, which allows large parameter... -
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trench
Open-Source Analytics Infrastructure
Trench is an open-source analytics infrastructure designed for tracking events and performing real-time analysis of application data at scale. The system is built on top of high-performance data technologies including Apache Kafka and ClickHouse, which allows it to ingest and process very large volumes of events while maintaining fast query performance. It was originally developed to solve scaling challenges in product analytics systems where traditional relational databases become... -
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Opik
Debug, evaluate, and monitor your LLMapps, RAG systems, and agentic AI
Confidently evaluate, test, and monitor LLM applications. Opik is an open-source platform for evaluating, testing, and monitoring LLM applications. Built by Comet. Record, sort, search, and understand each step your LLM app takes to generate a response. Manually annotate, view, and compare LLM responses in a user-friendly table. Log traces during development and in production. Run experiments with different prompts and evaluate against a test set. Choose and run pre-configured evaluation... -
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Rhino
On-device Speech-to-Intent engine powered by deep learning
Rhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a given context of interest, in real-time. The end-to-end platform for embedding private voice AI into any software in a few lines of code. Design with no limits on top of a modular platform. Create use-case-specific voice AI models in seconds. Develop voice features with a few lines of code using intuitive and cross-platform SDKs. Deliver voice AI everywhere: on-device, mobile, web browsers,... -
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JSON_REPAIR
A python module to repair invalid JSON from LLMs
json_repair is an open-source Python library designed to automatically fix malformed JSON data and convert it into valid, parseable structures. The tool is particularly useful in scenarios where JSON output is generated by large language models or external services that may produce syntactically invalid responses. Instead of failing when encountering errors such as missing quotes, trailing commas, or incomplete objects, the library analyzes the malformed data and reconstructs it into valid... -
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Paperclip
Open-source orchestration for zero-human companies
Paperclip is an open-source tool designed to help AI systems and developer tools access academic research papers through a standardized interface. The project implements a server based on the Model Context Protocol (MCP), a framework that allows large language models and AI agents to connect to external data sources and tools in a consistent way. By acting as a middleware layer, Paperclip aggregates multiple academic databases and exposes them through a single interface, allowing AI... -
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Strix
Open-source AI hackers to find and fix your app’s vulnerabilities
Strix is an open source agent-driven security platform that uses autonomous AI agents to identify, investigate, and validate vulnerabilities in software applications. The system is designed to mimic the behavior of real attackers by executing dynamic testing and verifying findings through proof-of-concept exploitation. Unlike traditional vulnerability scanners that rely heavily on static analysis, Strix agents actively run code, probe systems, and attempt exploitation to confirm whether... -
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
AReaL is an open source, fully asynchronous reinforcement learning training system. AReal is designed for large reasoning and agentic models. It works with models that perform reasoning over multiple steps, agents interacting with environments. It is developed by the AReaL Team at Ant Group (inclusionAI) and builds upon the ReaLHF project. Release of training details, datasets, and models for reproducibility. It is intended to facilitate reproducible RL training on reasoning / agentic tasks,... -
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LiteMultiAgent
The Library for LLM-based multi-agent applications
LiteMultiAgent is a lightweight and extensible multi-agent reinforcement learning (MARL) platform designed for rapid experimentation. It allows researchers to design and test coordination, competition, and collaboration scenarios in simulated environments. -
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RWARE
MuA multi-agent reinforcement learning environment
robotic-warehouse is a simulation environment and framework for robotic warehouse automation, enabling research and development of AI and robotic agents to manage warehouse logistics, such as item picking and transport. -
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txtai
Build AI-powered semantic search applications
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid... -
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12-Factor Agents
What are the principles we can use to build LLM-powered software
12-Factor Agents is a conceptual engineering guide that defines a set of principles for building reliable, scalable, and maintainable LLM-powered applications. Inspired by the original Twelve-Factor App methodology, the project reframes best practices specifically for agentic systems and AI software. It outlines patterns such as treating prompts as first-class assets, owning the context window, and converting natural language into structured tool calls. The repository emphasizes operational... -
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Hello-Agents
Building an Intelligent Agent from Scratch
Hello Agents is an open educational project designed to teach developers how to understand, design, and build AI-native agents from the ground up through structured tutorials and practical examples. The project focuses on guiding learners beyond superficial framework usage toward deeper comprehension of agent architecture, reasoning loops, and real-world implementation patterns. It walks users through core concepts such as ReAct-style reasoning, tool usage, memory handling, and multi-step... -
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MemOS
AI memory OS for LLM and Agent systems
MemOS is an experimental operating system and runtime built around the concept of memory-centric computing, where memory objects are first-class citizens and program execution is organized around efficient, persistent memory access rather than traditional process and file system boundaries. The project explores rethinking system abstractions by tightly coupling computation with memory objects so that programs can operate on large datasets without expensive serialization or context switching.... -
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Monty
A minimal, secure Python interpreter written in Rust for use by AI
Monty is an experimental, security-focused Python interpreter implemented in Rust and intended for running AI-generated Python safely under strict constraints. 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... -
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Z80-μLM
Z80-μLM is a 2-bit quantized language model
Z80-μLM is a retro-computing AI project that demonstrates a tiny language model (Z80-μLM) engineered to run on an 8-bit Z80 CPU by aggressively quantizing weights down to 2-bit precision. The repository provides a complete workflow where you train or fine-tune conversational models in Python, then export them into a format that can be executed on classic Z80 systems. A key deliverable is producing CP/M-compatible .COM binaries, enabling a genuinely vintage “chat with your computer”... -
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E2B Cookbook
Examples of using E2B
...The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code execution, and application generation inside isolated sandbox environments. E2B itself provides secure Linux-based sandboxes that enable AI systems to safely run generated code and interact with real computing resources without compromising the host environment. The cookbook organizes examples across multiple frameworks and model providers, allowing developers to experiment with integrations involving models from OpenAI, Anthropic, and other ecosystems. -
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Lance
Modern columnar data format for ML and LLMs implemented in Rust
Lance is a columnar data format that is easy and fast to version, query and train on. It’s designed to be used with images, videos, 3D point clouds, audio and of course tabular data. It supports any POSIX file systems, and cloud storage like AWS S3 and Google Cloud Storage. -
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OmniBox
Collect, organize, use, and share, all in OmniBox
Omnibox (mirror) is a SourceForge mirror of the Omnibox open-source project, which provides a software interface designed to simplify interaction with multiple tools and services through a unified command or search interface. The project focuses on creating a centralized input field where users can enter commands, queries, or shortcuts that trigger actions across different applications or services. Inspired by the omnibox concept used in modern browsers, the system combines search...
