Search Results for "processing" - Page 12
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Showing 1085 open source projects for "processing"
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RuoYi AI
Enterprise AI platform for building, deploying, and managing apps
RuoYi AI is a full-stack enterprise-oriented AI development platform designed to help developers rapidly build, deploy, and manage intelligent applications using modern large language models and AI ecosystems. It provides a unified framework for integrating multiple AI models from different providers, allowing teams to switch or combine models through a consistent interface without vendor lock-in. RuoYi AI includes built-in support for retrieval-augmented generation, enabling organizations... -
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LiveKit Agents
Framework for building realtime multimodal voice AI agents apps
LiveKit Agents is an open source framework designed for building realtime AI agents that can participate as programmable entities within communication sessions. It enables developers to create conversational and multimodal agents capable of processing voice, audio, and other inputs in realtime environments. These agents can join LiveKit rooms as participants and interact with users or systems through speech, text, and other modalities. LiveKit Agents provides libraries and tooling that allow developers to combine speech-to-text, large language models, and text-to-speech services to build interactive AI experiences. ... -
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OpenClaw Medical Skills
The largest open-source medical AI skills library for OpenClaw
...This modular design allows developers and researchers to build AI systems that can access specialized medical reasoning processes, retrieve relevant biomedical information, and generate structured outputs suitable for analysis or downstream processing. -
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AudioMuse-AI
AudioMuse-AI is an Open Source Dockerized environment
AudioMuse-AI is an open-source system designed to automatically generate playlists and analyze music libraries using artificial intelligence and audio signal processing techniques. The platform runs locally in a Dockerized environment and performs detailed sonic analysis on audio files to understand characteristics such as tempo, mood, and acoustic similarity. By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal music libraries and generate curated playlists for different moods or listening contexts. ... -
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Replicate Flux MCP
MCP for Replicate Flux Model
The Replicate Flux MCP is an advanced Model Context Protocol server that empowers AI assistants to generate high-quality images and vector graphics. It leverages Black Forest Labs' Flux Schnell model for raster images and Recraft's V3 SVG model for vector graphics via the Replicate API. -
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MCP Image Compression
A high-performance image compression microservice based on MCP
The MCP Image Compression server is a high-performance microservice based on the Model Context Protocol architecture. It focuses on providing fast and high-quality image compression capabilities to help developers optimize image resources for websites and applications, improving loading speed and user experience. -
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Xiyan MCP Server
A Model Context Protocol (MCP) server
The XiYan MCP Server is a Model Context Protocol (MCP) server that enables natural language queries to databases, powered by XiYan-SQL, a state-of-the-art text-to-SQL model. It allows users to interact with databases using conversational language, simplifying data retrieval processes. -
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TextWorld
TextWorld is a sandbox learning environment for the training
...Developed by Microsoft Research, TextWorld focuses on language understanding, planning, and interaction in complex, narrative-driven environments. It generates games procedurally, enabling scalable testing of agents’ natural language processing and decision-making abilities. -
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AppWorld
World of apps for benchmarking interactive coding agent
AppWorld is a framework developed by Stony Brook University's NLP group to simulate environments for training and evaluating dialogue agents in task-oriented applications. -
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MLDatasets.jl
Utility package for accessing common Machine Learning datasets
...In contrast to other data-related Julia packages, the focus of MLDatasets.jl is specifically on downloading, unpacking, and accessing benchmark datasets. Functionality for the purpose of data processing or visualization is only provided to a degree that is special to some datasets. -
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Megatron
Ongoing research training transformer models at scale
...We developed efficient, model-parallel (tensor, sequence, and pipeline), and multi-node pre-training of transformer based models such as GPT, BERT, and T5 using mixed precision. Megatron is also used in NeMo Megatron, a framework to help enterprises overcome the challenges of building and training sophisticated natural language processing models with billions and trillions of parameters. Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. -
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Orpheus TTS
Towards Human-Sounding Speech
...It is designed to produce human-like speech with natural intonation, emotion, and rhythm, targeting quality comparable to or better than many closed-source systems. The project ships both pretrained and finetuned English models, as well as a family of multilingual models released as a research preview, and includes data-processing scripts so users can train or finetune their own variants. Inference is provided through a Python package that uses vLLM under the hood for high-throughput, low-latency generation, including streaming examples that show how to generate audio chunks in real time. The maintainers provide Colab notebooks, a standardized prompting format, and one-click deployment via Baseten for production-grade, FP8/FP16 optimized inference with ~200 ms streaming latency. -
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Kimi-Audio
Audio foundation model excelling in audio understanding
Kimi-Audio is an ambitious open-source audio foundation model designed to unify a wide array of audio processing tasks — from speech recognition and audio understanding to generative conversation and sound event classification — within a single cohesive architecture. Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one system, enabling developers to build rich, multimodal audio applications without stitching together disparate components. ... -
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MiniMax Skills
Development skills for AI coding agents
...These skills can be integrated into AI tools to improve the quality and consistency of generated code, particularly in areas such as frontend development, backend systems, mobile applications, and multimedia processing. The system supports a wide range of technologies and workflows, allowing developers to leverage AI assistance for both simple tasks and large-scale projects. It is designed to be extensible, enabling contributors to add new skills or enhance existing ones as development practices evolve. -
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Text Embeddings Inference
High-performance inference server for text embeddings models API layer
Text Embeddings Inference is a high-performance server designed to serve text embedding models efficiently in production environments. It focuses on delivering fast and scalable embedding generation by leveraging optimized inference techniques and modern hardware acceleration. It is built to support transformer-based embedding models, making it suitable for tasks such as semantic search, clustering, and retrieval-augmented systems. It provides an API interface that allows developers to... -
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LandPPT
An LLM-based presentation generation platform
...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 multiple AI models from providers such as OpenAI, Anthropic, Google, and locally hosted models to generate text, images, and structured presentation layouts. It also includes template systems and style options that allow presentations to be customized for different industries, visual themes, or storytelling formats. -
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Happy-LLM
Large Language Model Principles and Practice Tutorial from Scratch
Happy-LLM is an open-source educational project created by the Datawhale AI community that provides a structured and comprehensive tutorial for understanding and building large language models from scratch. The project guides learners through the entire conceptual and practical pipeline of modern LLM development, starting with foundational natural language processing concepts and gradually progressing to advanced architectures and training techniques. It explains the Transformer architecture, pre-training paradigms, and model scaling strategies while also providing hands-on coding examples so readers can implement and experiment with their own models. The tutorial emphasizes practical understanding by walking users through building and training small language models, including tokenizer construction, pre-training workflows, and fine-tuning methods. -
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Note67
A private, local meeting notes assistant
...Users can record meetings directly from their microphone, view live transcriptions, filter by speaker, and export structured summaries, making it useful for professionals who need searchable, organized records of discussions. It also features thoughtful signal processing such as voice activity detection and echo deduplication to improve transcription accuracy, and provides standard note-taking features. -
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NeMo Curator
Scalable data pre processing and curation toolkit for LLMs
NeMo Curator is a Python library specifically designed for fast and scalable dataset preparation and curation for large language model (LLM) use-cases such as foundation model pretraining, domain-adaptive pretraining (DAPT), supervised fine-tuning (SFT) and paramter-efficient fine-tuning (PEFT). It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings. The library provides a customizable and modular interface, simplifying pipeline... -
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Taipy
Turns Data and AI algorithms into production-ready web applications
...Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape. Struggle with sluggish performance and excessive memory usage, as every data point demands processing. Large datasets become cumbersome, complicating the user experience and data analysis. Scenarios are made easy with Taipy Studio. A powerful VS Code extension that unlocks a convenient graphical editor. Get your methods invoked at a certain time or intervals. Enjoy a variety of predefined themes or build your own. -
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Nimbalyst
Run multiple Codex and Claude Code AI sessions
...Crystal often leverages modern programming practices and clean architecture principles to ensure maintainability and scalability as projects grow. It can be used as a foundation for building internal tools, automation systems, or data processing pipelines, depending on how developers configure its components. The system is particularly useful for teams that want control over their infrastructure without relying on overly complex or opinionated platforms. -
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Automaton
The first AI that can earn its own existence, replicate, and evolve
...The project is particularly useful in educational contexts, where visualizing or testing automata behavior helps reinforce concepts such as deterministic and nondeterministic machines. Developers can also use it as a foundation for research prototypes involving parsing, pattern recognition, or language processing. Overall, Automaton bridges the gap between abstract theory and practical implementation by providing a structured and extensible codebase for automata experimentation. -
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Computer Vision in Action
A computer vision closed-loop learning platform
Computer Vision in Action is a practical, example-rich repository that demonstrates real-world applications of computer vision techniques and algorithms in Python, often using OpenCV, deep learning models, and related tooling. It serves as a hands-on companion for learners and engineers who want to understand not just the theory, but how computer vision is actually implemented for tasks like object detection, image classification, feature tracking, optical flow, and image segmentation. The... -
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npcpy
The AI toolkit for the AI developer
npcpy is a Python-based agent framework and command-line toolkit (the NPC Shell) for developers to build, test, and integrate AI agents into their workflows, including both command-line and GUI interfaces via NPC Studio. Welcome to npcpy, the core library of the NPC Toolkit that supercharges natural language processing pipelines and agent tooling. npcpy is a flexible framework for building state-of-the-art applications and conducting novel research with LLMs. The structure of npcpy also allows one to pass an npc to get_llm_response in addition to using the NPC's wrapped method, allowing you to be flexible in your implementation and testing. -
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LearnOpenCV
C++ and Python Examples
LearnOpenCV is a large educational repository that provides practical computer vision and deep learning examples in both Python and C++. The project accompanies the LearnOpenCV blog and contains hundreds of hands-on tutorials covering topics such as object detection, image processing, pose estimation, and neural networks. It is structured as a learning resource where each directory corresponds to a specific article or technical walkthrough. The repository supports beginners and advanced practitioners by offering reproducible code that demonstrates real-world computer vision techniques. Many examples integrate popular frameworks like PyTorch, OpenCV, and ONNX to reflect modern AI workflows. ...
