Search Results for "processing" - Page 5
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Showing 445 open source projects for "processing"
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RouteGenie NEMT softwareRouteGenie NEMT software is a modern system built to automate all non-emergency medical transportation processes including routing, scheduling, dispatching, and billing. It helps manage everyday challenges like vehicle breakdowns, traffic problems, cancelations, driver call-offs, will calls, no shows, add-on trips, on-demand trips, and more.
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The Receptionist for iPad | the Original Visitor Management SystemThe Receptionist for iPad is visitor management software that allows users to calm the chaos of the front office. Our digital check-in solution is customizable to your needs; from your company branding, to configurable buttons and drag-and-drop-design badge printing. Effectively manage and track everyone who comes to your workspace and store the information securely in the cloud: no more paper visitor log!
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DeepBI
LLM based data scientist, AI native data application
DeepBI is an AI-native data analysis platform. DeepBI leverages the power of large language models to explore, query, visualize, and share data from any data source. Users can use DeepBI to gain data insight and make data-driven decisions. -
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E2M
E2M converts various file types (doc, docx, epub, html, htm, url
...The mirrored repository allows users to access the project’s codebase independently from its original hosting platform while preserving the development history and release artifacts. Systems like e2m often serve as middleware components that connect different software systems or facilitate data processing pipelines. By acting as a transformation layer, the software can support workflows such as converting data formats, integrating services, or bridging incompatible systems. The mirror hosted on SourceForge ensures that developers can continue accessing the project even if the primary repository becomes unavailable. -
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LLM-Aided OCR Project
Enhances Tesseract OCR output using LLMs (local or API)
...The project is particularly useful for digitizing historical documents, research papers, and scanned materials where traditional OCR often struggles. It also includes tools for processing batches of images or documents, enabling automated document digitization workflows. -
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Chinese-XLNet
Chinese XLNet pre-trained model
Chinese-XLNet is a Chinese language pre-trained model based on the XLNet architecture, providing an advanced foundation for natural language processing tasks in Mandarin and other Chinese dialects. Unlike traditional masked language modeling, XLNet uses a permutation language modeling objective that captures bidirectional context more effectively by training over all possible token orderings, yielding richer contextual representations. This model is trained on large-scale Chinese text datasets to learn linguistic patterns, long-range dependencies, and semantic nuance typical of Chinese writing, making it useful for tasks like text classification, question answering, named entity recognition, and language generation. ... -
Top Corporate LMS for Training | Best Learning Management SoftwareAxis LMS enables you to deliver online and virtual learning and training through a scalable, easy-to-use LMS that is designed to enhance your training, automate your workflows, engage your learners and keep you compliant.
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Umi-OCR
OCR software, free and offline
...It includes a highly efficient offline OCR engine with built-in multilingual recognition libraries, so users can extract text across multiple languages with high accuracy directly on their machines. The software supports flexible usage patterns including screenshot capture OCR, batch processing of large sets of images or documents, PDF parsing, QR code detection, and layout-aware paragraph output. Users can interact with Umi-OCR through a graphical interface, command-line options, or HTTP interfaces, making it adaptable to both casual desktop usage and programmatic automation. Because the project is open source, developers can inspect, modify, and extend its capabilities, and plugins allow for different recognition engines or enhanced features. -
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Frigate
NVR with realtime local object detection for IP cameras
Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. -
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Colossal-AI
Making large AI models cheaper, faster and more accessible
The Transformer architecture has improved the performance of deep learning models in domains such as Computer Vision and Natural Language Processing. Together with better performance come larger model sizes. This imposes challenges to the memory wall of the current accelerator hardware such as GPU. It is never ideal to train large models such as Vision Transformer, BERT, and GPT on a single GPU or a single machine. There is an urgent demand to train models in a distributed environment. ... -
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Medeo Video Generator
AI-powered video generation skill for OpenClaw
Medeo Video Generator is an AI-driven project designed to enable advanced video processing and generation capabilities within agent-based or automation systems. It provides a “skill” module that can be integrated into AI agents, allowing them to create, edit, and manipulate video content programmatically. The project focuses on bridging the gap between language-based AI systems and multimedia outputs by enabling models to produce structured video content as part of their workflows. ... -
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LitServe
Minimal Python framework for scalable AI inference servers fast
...Unlike traditional serving tools that enforce rigid abstractions, LitServe focuses on flexibility by letting users control request handling, batching strategies, and output processing directly in Python. LitServe is built on top of FastAPI and extends it with AI-specific optimizations such as efficient multi-worker execution, which can significantly improve throughput. It includes built-in capabilities for batching, streaming responses, and automatic scaling across CPUs and GPUs, enabling high-performance deployments. -
No-code email and landing page creationBuilt for speed and collaboration, Knak streamlines campaign production with modular templates, real-time editing, simple collaboration, and seamless integrations with leading MAPs like Adobe Marketo Engage, Salesforce Marketing Cloud, Oracle Eloqua, and more. Whether you're supporting global teams or launching fast-turn campaigns, Knak helps you go from brief to build in minutes—not weeks. Say goodbye to bottlenecks and hello to marketing agility.
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Hugging Face - Speech To Speech
Open speech-to-speech models and pipelines by Hugging Face toolkit AI
This project from Hugging Face focuses on enabling direct speech-to-speech processing using modern machine learning models. It provides tools and reference implementations that allow audio input to be transformed into audio output without requiring an intermediate text representation. Hugging Face - Speech To Speech builds on recent advances in speech modeling, combining components such as speech recognition, translation, and synthesis into unified pipelines. -
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Paperless-AI
AI-powered document analysis and tagging for Paperless-ngx
Paperless-AI is an AI-powered extension designed to enhance document management within Paperless-ngx by automating analysis, classification, and organization tasks. It continuously monitors incoming documents and processes them using various AI backends, enabling automatic assignment of titles, tags, document types, and correspondents. It integrates with multiple OpenAI-compatible services as well as local models, giving users flexibility in how document intelligence is handled. A key... -
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docext
An on-premises, OCR-free unstructured data extraction
...The system is designed to operate entirely on-premises, allowing organizations to process sensitive documents without relying on external cloud services. Unlike traditional document processing pipelines that rely heavily on optical character recognition, docext leverages multimodal AI models capable of understanding both visual and textual information directly from document images. This allows the system to detect and extract structured elements such as tables, signatures, key fields, and layout information while maintaining semantic understanding of the document content. ... -
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Youtu-Agent
A simple yet powerful agent framework that delivers with models
...The system focuses on reducing the complexity traditionally involved in configuring large language model agents by providing a modular architecture that separates execution environments, tools, and context management. This structure allows developers to rapidly assemble agent systems capable of performing tasks such as research, file processing, and data analysis. The framework supports automated generation of agent components, enabling the system to synthesize prompts, tool interfaces, and workflow configurations automatically. Youtu-Agent also incorporates hybrid learning strategies that combine experience accumulation with reinforcement learning to improve agent performance over time. ... -
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Memobase
Fast backend for long-term AI user memory via structured profiles
...Instead of relying purely on traditional embedding-based retrieval or RAG systems, Memobase uses profile and timeline structures to deliver memory that reflects user context efficiently and meaningfully. The system focuses on three principal performance metrics: high search performance, reduced large language model (LLM) costs through batch processing techniques, and low latency with minimal SQL operations. Memobase supports integration with existing LLM workflows via APIs and SDKs (including Python, Node, and Go), making it easy to adopt within diverse application stacks. -
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NeMo Retriever Library
Document content and metadata extraction microservice
...It processes various document types by splitting them into components such as text, tables, charts, and images, and then applies OCR and contextual analysis to convert them into structured data formats. The system is built on NVIDIA NIM microservices, enabling high-performance parallel processing and efficient handling of large datasets. It supports multiple extraction strategies for different document formats, balancing accuracy and throughput depending on the use case. Additionally, it can generate embeddings for extracted content and integrate with vector databases like Milvus, making it well-suited for retrieval-augmented generation pipelines. -
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Llama Stack
Composable building blocks to build Llama Apps
Llama-Stack is an open-source framework designed to facilitate the deployment and fine-tuning of large language models (LLMs) for various natural language processing tasks. -
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Browser Use
Make websites accessible for AI agents
Browser-Use is a framework that makes websites accessible for AI agents, enabling automated interactions and data extraction from web pages. -
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Open Gauss
Project-scoped Lean workflow orchestrator from Math, Inc.
Open Gauss is an enterprise-grade open-source relational database management system designed to handle large-scale data processing with high performance, reliability, and security. It is based on the PostgreSQL ecosystem but significantly extends its capabilities through architectural optimizations, AI-driven features, and enterprise-level enhancements. The database organizes data using the relational model, storing structured information in tables composed of rows and columns while supporting standard SQL for querying and management. ... -
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Cactus
Low-latency AI inference engine optimized for mobile devices
...Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing large models to run within the constraints of mobile hardware. It supports a wide range of AI tasks including text generation, speech-to-text, vision processing, and retrieval-augmented workflows through a unified API interface. A notable feature of Cactus is its hybrid execution model, which can dynamically route tasks between on-device processing and cloud services when additional compute is required. -
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GPTme
Your agent in your terminal, equipped with local tools
GPTMe is a personal AI chatbot designed for self-reflection, journaling, and productivity, using GPT models to generate personalized insights and responses. -
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Quantitative Trading System
A comprehensive quantitative trading system with AI-powered analysis
...The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. It includes tools for collecting and processing market data from multiple sources, performing statistical and machine learning analysis, and generating trading signals based on quantitative models. The system supports real-time data streaming, allowing strategies to respond to market conditions as they evolve. QuantMuse also incorporates advanced risk management features, including portfolio monitoring, risk limits, and dynamic position sizing to control exposure. -
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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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Faster Whisper
Faster Whisper transcription with CTranslate2
...The architecture is designed to run efficiently on both CPUs and GPUs, making it accessible across different environments. It also includes support for streaming and batch processing, enabling flexible deployment scenarios. Overall, faster-whisper makes state-of-the-art speech recognition more practical for production use cases by improving speed and efficiency without sacrificing quality. -
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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...
