Search Results for "multi-system" - Page 10
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Showing 2679 open source projects for "multi-system"
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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, enabling high audio fidelity with efficient processing of long sequences. ... -
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FastKoko
Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model
...The server also offers per-word timestamped captions, which makes it useful for creating subtitles or aligning audio with text. A built in web UI, API documentation, and debug endpoints for monitoring system status help users explore voices, test requests, and integrate the service into larger systems. -
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Basic Pitch
A lightweight audio-to-MIDI converter with pitch bend detection
...It's small, easy-to-use, pip install-able and npm install-able via its sibling repo. Basic Pitch may be simple, but it's is far from "basic"! basic-pitch is efficient and easy to use, and its multi pitch support, its ability to generalize across instruments, and its note accuracy compete with much larger and more resource-hungry AMT systems. Provide a compatible audio file and a basic-pitch will generate a MIDI file, complete with pitch bends. The basic pitch is instrument-agnostic and supports polyphonic instruments, so you can freely enjoy transcription of all your favorite music, no matter what instrument is used. ... -
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mistral.rs
Fast, flexible LLM inference
...It provides multiple entry points for developers, including a CLI for running models locally and an HTTP server that exposes an OpenAI-compatible API surface for easy integration with existing clients. The project includes hardware-aware tooling that can benchmark a system and choose sensible quantization and device-mapping strategies, helping users get strong performance without manual tuning. It also supports serving multiple models from the same server process, enabling routing or quick switching between models depending on workload needs. For user-facing testing, mistral.rs can provide a built-in web UI, and it also offers a dedicated lightweight web chat interface that supports richer interaction patterns. -
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AutoGen
An Open-Source Programming Framework for Agentic AI
...AutoGen aims to provide an easy-to-use and flexible framework for accelerating development and research on agentic AI, like PyTorch for Deep Learning. It offers features such as agents that can converse with other agents, LLM and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns. AutoGen provides multi-agent conversation framework as a high-level abstraction. With this framework, one can conveniently build LLM workflows. AutoGen offers a collection of working systems spanning a wide range of applications from various domains and complexities. AutoGen supports enhanced LLM inference APIs, which can be used to improve inference performance and reduce cost. -
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. ... -
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NVIDIA NeMo Framework
Scalable generative AI framework built for researchers and developers
NVIDIA NeMo is a scalable, cloud-native generative AI framework aimed at researchers and PyTorch developers working on large language models, multimodal models, and speech AI (ASR and TTS), with growing support for computer vision. It provides collections of domain-specific modules and reference implementations that make it easier to pre-train, fine-tune, and deploy very large models on multi-GPU and multi-node infrastructure. NeMo 2.0 introduces a Python-based configuration system, replacing YAML with more flexible, programmable configs that can be versioned and composed for different experiments. The framework builds on PyTorch Lightning–style modular abstractions, so training scripts are composed from reusable components for data loading, models, optimizers, and schedulers, which simplifies experimentation and adaptation. ... -
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Phidata
Build multi-modal Agents with memory, knowledge, tools and reasoning
Phidata is an open source platform for building, deploying, and monitoring AI agents. It enables users to create domain-specific agents with memory, knowledge, and external tools, enhancing AI capabilities for various tasks. The platform supports a range of large language models and integrates seamlessly with different databases, vector stores, and APIs. Phidata offers pre-configured templates to accelerate development and deployment, allowing users to quickly go from building agents to... -
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Telegram SMS
An SMS-forwarding Robot Running on Your Android Device
With the power of Telegram SMS, your multi-phone life is much easier than before. Receiving and sending SMS, relaying APP notifications, monitoring battery status. All stuff can be done with a single Telegram bot. You can use the bot in both private chat and group chat, in case you have more than 2 Android phones, or sharing the bot with other people. Telegram SMS connects with Telegram's bot API server directly, no 3rd-party services involved. -
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InfiniteYou
Flexible Photo Recrafting While Preserving Your Identity
...Using an architecture built around diffusion transformers (DiTs), InfiniteYou introduces a component called InfuseNet that injects identity features derived from reference images into the generation process — via residual connections — so that the output matches the person’s identity closely, without sacrificing visual quality or text-image alignment. The team uses a multi-stage training strategy with synthetic multi-sample data per identity to fine-tune for both identity consistency and aesthetic quality. Compared to prior methods, InfiniteYou significantly improves on identity similarity, text-prompt adherence, overall image quality, and avoids common problems such as face copy-pasting artifacts. -
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UForm
Multi-Modal Neural Networks for Semantic Search, based on Mid-Fusion
UForm is a Multi-Modal Modal Inference package, designed to encode Multi-Lingual Texts, Images, and, soon, Audio, Video, and Documents, into a shared vector space! It comes with a set of homonymous pre-trained networks available on HuggingFace portal and extends the transfromers package to support Mid-fusion Models. Late-fusion models encode each modality independently, but into one shared vector space. -
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infinite-canvas
Infinite Canvas Workbench for AI creation integrates AI generation
...It also includes a canvas assistant that can discuss selected nodes, use upstream context, generate new outputs, and place results back onto the canvas. The project is still in active development and is better suited for personal or local deployment than stable public multi-user production use. -
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Agent S
Agent S: an open agentic framework that uses computers like a human
...Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines powerful foundation models (such as GPT-5) with grounding models like UI-TARS to translate visual inputs into precise executable actions. It supports flexible deployment via CLI, SDK, or cloud, and integrates with multiple model providers including OpenAI, Anthropic, Gemini, Azure, and Hugging Face endpoints. ... -
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deepfakes_faceswap
Deepfakes Software For All
Faceswap is the leading free and open source multi-platform deepfakes software. When faceswapping was first developed and published, the technology was groundbreaking, it was a huge step in AI development. It was also completely ignored outside of academia because the code was confusing and fragmentary. It required a thorough understanding of complicated AI techniques and took a lot of effort to figure it out. -
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SuperPrompt
Experimental prompt framework exploring reasoning structures in AI
...Its main concept revolves around a highly structured prompt format that includes tagged sections for reasoning, analysis, conceptual expansion, and recursive thinking patterns. These sections act as a kind of meta-instruction system intended to influence how an AI model approaches problem solving and conceptual exploration. SuperPrompt also incorporates ideas from mathematics, recursion, abstract algebra, and theoretical reasoning to encourage models to perform multi-step conceptual synthesis rather than simple direct responses. -
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GLM-5.1
GLM-5: From Vibe Coding to Agentic Engineering
GLM-5.1 is a next-generation large language model developed by Z.ai for advanced coding, reasoning, and long-horizon agentic engineering tasks. Built as the successor to GLM-5, the model significantly improves performance in software engineering benchmarks, repository generation, and real-world terminal-based workflows. GLM-5.1 is designed to remain effective over extended problem-solving sessions, allowing it to iteratively refine strategies, analyze failures, and sustain productivity... -
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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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AgentRun
The easiest, and fastest way to run AI-generated Python code safely
AgentRun is a framework for building autonomous AI agents capable of executing complex tasks with minimal human intervention. It provides a structured environment for defining agent behaviors, managing workflows, and integrating AI models to achieve specific goals. -
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NoneBot
Asynchronous multi-platform robot framework written in Python
...NoneBot2 provides an easy-to-use, interactive command-line tool -- nb-cli, making it easier to get started with NoneBot2 for the first time. The plug-in system is the core of NoneBot2, through which the modularization and function expansion of the robot can be realized, which is convenient for maintenance and management. -
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Open Gauss
Project-scoped Lean workflow orchestrator from Math, Inc.
...One of its defining strengths is its optimization for multi-core and distributed environments, allowing it to efficiently process high volumes of concurrent transactions with minimal latency. OpenGauss also incorporates AI-based optimization techniques, such as intelligent query planning, performance prediction, and automated tuning, which help reduce operational complexity and improve efficiency. -
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Conversational Health Agents (CHA)
A Personalized LLM-powered Agent Frameworks
CHA, or Conversational Health Agents, is an open-source framework designed to build intelligent healthcare assistants powered by large language models and external data sources. The system enables developers to create personalized AI agents that can interact with users through natural language while performing multi-step reasoning and task execution. It integrates orchestration capabilities that allow the agent to gather information from APIs, knowledge bases, and external services in order to generate more accurate and context-aware responses. ... -
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MiroFlow
Agent framework that enables tool-use agent tasks
...This architecture allows agents to perform advanced reasoning tasks such as deep research, future event prediction, and multi-step knowledge analysis. The framework emphasizes reliability and scalability by incorporating robust workflow execution, concurrency management, and fault-tolerant design to handle unstable APIs or network conditions. -
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SearChat
Search + Chat = SearChat(AI Chat with Search)
SearChat is an open-source conversational search platform that combines traditional web search engines with large language model reasoning to create an interactive research environment. The project is designed to transform the process of web searching into a multi-turn conversational experience where users can refine queries and explore results through dialogue. Built using a modern monorepo architecture, the system includes a Node.js and Koa backend alongside a Vue 3 and TypeScript frontend that delivers a responsive chat interface. The platform supports multiple AI providers, allowing developers to connect models from providers such as OpenAI, Anthropic, or Google Gemini to generate contextual responses. ... -
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ReCall
Learning to Reason with Search for LLMs via Reinforcement Learning
ReCall is an open-source framework designed to train and evaluate language models that can reason through complex problems by interacting with external tools. The project builds on earlier work focused on teaching models how to search for information during reasoning tasks and extends that idea to a broader system where models can call a variety of external tools such as APIs, databases, or computation engines. Instead of relying purely on static knowledge stored inside the model, ReCall allows the language model to dynamically decide when it should retrieve information or invoke external capabilities during the reasoning process. The framework uses reinforcement learning to train models to perform these tool calls effectively while solving multi-step reasoning tasks. -
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DeepSearcher
Open Source Deep Research Alternative to Reason and Search
DeepSearcher is an open-source “deep research” style system that combines retrieval with evaluation and reasoning to answer complex questions using private or enterprise data. It is designed around the idea that high-quality answers require more than top-k retrieval, so it orchestrates multi-step search, evidence collection, and synthesis into a comprehensive response. The project integrates with vector databases (including Milvus and related options) so organizations can index internal documents and query them with semantic retrieval. ...
