Showing 5100 open source projects for "processing"

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  • 1
    clawhip

    clawhip

    claw + whip: Event-to-channel notification router

    Clawhip is an open-source daemon-first notification router designed to deliver structured events from development workflows directly to platforms like Discord and Slack. It acts as a central event-processing system that listens to sources such as Git, GitHub, tmux sessions, and custom CLI events, then routes them through a typed pipeline. Built with a clean separation between routing, rendering, and delivery, Clawhip ensures reliable and organized notifications without polluting AI agent contexts. It integrates seamlessly with tools like OpenClaw, OMX (oh-my-codex), and OMC (oh-my-claudecode) to monitor coding sessions and automate updates. ...
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  • 2
    BeeAI Framework

    BeeAI Framework

    Build production-ready AI agents in both Python and Typescript

    ...BeeAI also provides orchestration tools for designing dynamic workflows, enabling multiple agents to coordinate tasks through structured execution flows, retries, and parallel processing.
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  • 3
    Google Cloud Dataflow Template Pipelines

    Google Cloud Dataflow Template Pipelines

    Cloud Dataflow Google-provided templates for solving data tasks

    DataflowTemplates is the source repository for Google-provided Dataflow templates that are intended to solve large-scale in-cloud data processing tasks without requiring users to build everything from scratch in a full development environment. The repository is centered on templated pipelines powered by Google Cloud Dataflow and Apache Beam, making it easier to run common integration and movement jobs such as data import, export, backup, restore, and bulk API operations.
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  • 4
    Kuma UI

    Kuma UI

    A Headless, Utility-First, and Zero-Runtime UI Component Library

    ...It also offers an API designed to feel familiar to developers who already use popular styling solutions, which improves developer productivity and adoption. Because Kuma UI avoids heavy runtime processing, applications built with it can achieve faster rendering and reduced bundle sizes.
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    FISSURE

    FISSURE

    The RF and reverse engineering framework for everyone

    ...The platform supports workflows related to signal discovery, demodulation, packet inspection, fuzzing, and attack simulation, making it useful for both defensive research and controlled lab testing. Its architecture is oriented toward extensibility, so users can integrate additional hardware, signal-processing components, and protocol-specific modules depending on their needs.
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  • 6
    Text2Code for Jupyter notebook

    Text2Code for Jupyter notebook

    A proof-of-concept jupyter extension which converts english queries

    ...When a user enters a textual command, the extension interprets the request and generates a corresponding Python code snippet that can be inserted into the notebook and executed automatically. The system uses natural language processing techniques to identify the intent of the query, extract relevant variables, and map the request to predefined code templates. Technologies such as sentence embeddings and named entity recognition are used to interpret user instructions and construct appropriate code outputs.
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  • 7
    Memori

    Memori

    SQL-native memory layer enabling persistent context for AI agents

    Memori is an open source SQL-native memory engine designed to add persistent memory capabilities to AI applications, large language models, and multi-agent systems. It provides a memory layer that automatically captures conversations and interactions between users and AI models, allowing systems to retain knowledge across sessions instead of operating statelessly. It extracts structured information such as facts, preferences, rules, and summaries from interactions and stores them in standard...
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  • 8
    Open SaaS

    Open SaaS

    Open source SaaS boilerplate for React, NodeJS apps with Wasp stack

    ...Developers can use it as a boilerplate to avoid writing repetitive setup code and instead focus on building product features. It integrates several commonly used services and tools, including payment processing systems, email providers, analytics platforms, and AI integrations. It also includes an admin dashboard, testing setup, and deployment configuration to streamline development workflows. By bundling these components together, Open SaaS aims to reduce development time and make it easier to create scalable web applications.
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  • 9
    Python Code Tutorials

    Python Code Tutorials

    The Python Code Tutorials

    ...The repository is organized into thematic directories that group tutorials by topic, allowing learners to navigate easily between areas such as ethical hacking, multimedia processing, or machine learning.
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  • 10
    rust-bert

    rust-bert

    Rust native ready-to-use NLP pipelines and transformer-based models

    rust-bert is a Rust-based implementation of transformer-based natural language processing models that provides ready-to-use pipelines for tasks such as text classification, summarization, and question answering. The project ports many capabilities of the Hugging Face Transformers ecosystem into the Rust programming language. It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory efficiency. ...
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  • 11
    OpenVINO Notebooks

    OpenVINO Notebooks

    Jupyter notebook tutorials for OpenVINO

    openvino_notebooks is a collection of interactive Jupyter notebooks designed to demonstrate how to build, optimize, and deploy artificial intelligence applications using the OpenVINO toolkit. The repository provides practical tutorials that guide developers through various AI workflows including computer vision, natural language processing, and generative AI tasks. Each notebook demonstrates how to run pre-trained models, optimize inference performance, and deploy models across hardware such as CPUs, GPUs, and specialized accelerators. The tutorials also illustrate how OpenVINO integrates with models from frameworks like PyTorch, TensorFlow, and ONNX to accelerate inference workloads. ...
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  • 12
    AiLearning-Theory-Applying

    AiLearning-Theory-Applying

    Quickly get started with AI theory and practical applications

    ...The project also introduces important concepts such as probability theory, linear algebra, regression models, clustering methods, and neural network architectures. Advanced sections explore modern AI topics including transformers, BERT-based natural language processing systems, and practical competition-style machine learning workflows.
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  • 13
    ComfyUI-3D-Pack

    ComfyUI-3D-Pack

    An extensive node suite that enables ComfyUI to process 3D inputs

    ComfyUI-3D-Pack is an extension package for the ComfyUI visual AI workflow environment that enables users to generate and manipulate 3D assets using advanced machine learning techniques. ComfyUI itself is a node-based interface for designing and executing generative AI pipelines, and this extension expands its capabilities by introducing nodes specifically designed for working with three-dimensional data. The package allows the platform to process inputs such as meshes and UV textures and...
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  • 14
    Netflix Maestro

    Netflix Maestro

    Netflix’s Workflow Orchestrator

    Maestro is a large-scale workflow orchestration platform originally developed by Netflix to coordinate complex data processing and machine learning workflows across distributed systems. The system acts as a general-purpose workflow orchestrator that manages the execution, scheduling, monitoring, and recovery of large pipelines used for analytics and AI operations. It was designed to support the demanding internal infrastructure of Netflix, where thousands of workflows must process massive volumes of data reliably and efficiently every day. ...
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  • 15
    Advanced AI explainability for PyTorch

    Advanced AI explainability for PyTorch

    Advanced AI Explainability for computer vision

    pytorch-grad-cam is an open-source library that provides advanced explainable AI techniques for interpreting the predictions of deep learning models used in computer vision. The project implements Grad-CAM and several related visualization methods that highlight the regions of an image that most strongly influence a neural network’s decision. These visualization techniques allow developers and researchers to better understand how convolutional neural networks and transformer-based vision...
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  • 16
    QueryList

    QueryList

    Progressive PHP web crawler framework with jQuery-like DOM parsing

    QueryList is an extensible PHP web scraping and crawling framework designed to extract and process data from web pages. It provides a simple and expressive API that allows developers to collect structured information from HTML documents using familiar DOM traversal techniques. It is built on top of phpQuery and uses CSS3 selectors similar to those found in jQuery, making it easy for developers to query and manipulate page elements during scraping tasks. QueryList supports common data...
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  • 17
    Bedrock Chat

    Bedrock Chat

    AWS-native chatbot using Bedrock

    Bedrock Chat is a mirrored version of an open-source project that provides a conversational interface for interacting with large language models and AI services through a chat-style application. The project typically focuses on delivering a user interface that allows individuals or teams to communicate with AI models, manage conversations, and experiment with prompts and responses. Implementations like Bedrock Chat often integrate with model hosting platforms or APIs that provide access to...
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  • 18
    dataline

    dataline

    AI data analysis and visualization on CSV, Postgres, MySQL, Snowflake

    ...The platform is designed with a privacy-first architecture that stores data locally on the user’s device rather than sending it to external cloud services by default. It can also hide sensitive data from language models during processing, ensuring that only necessary metadata is used for query generation.
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  • 19
    ModernBERT

    ModernBERT

    Bringing BERT into modernity via both architecture changes and scaling

    ModernBERT is an open-source research project that modernizes the classic BERT encoder architecture by incorporating recent advances in transformer design, training techniques, and efficiency improvements. The goal of the project is to bring BERT-style models up to date with the capabilities of modern large language models while preserving the strengths of bidirectional encoder architectures used for tasks such as classification, retrieval, and semantic search. ModernBERT introduces...
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  • 20
    nndeploy

    nndeploy

    An Easy-to-Use and High-Performance AI Deployment Framework

    ...The framework focuses on making it easier to transform trained AI models into production-ready applications that can run efficiently on desktops, mobile devices, servers, and edge computing hardware. Developers can use visual workflows to design and configure AI processing pipelines by connecting modular nodes that represent different stages of the inference process. The system supports multiple inference engines and hardware accelerators, allowing the same AI workflow to run on different platforms without significant modifications. nndeploy also includes performance optimization techniques such as parallel execution, memory reuse, and hardware-accelerated operations to improve inference speed.
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  • 21
    xLSTM

    xLSTM

    Neural Network architecture based on ideas of the original LSTM

    xLSTM is an open-source machine learning architecture that reimagines the classic Long Short-Term Memory (LSTM) network for modern large-scale language modeling and sequence processing tasks. The project introduces a new recurrent neural network design that incorporates exponential gating mechanisms and enhanced memory structures to overcome limitations of traditional LSTM models. By introducing innovations such as matrix-based memory and improved normalization techniques, xLSTM improves the ability of recurrent networks to capture long-range dependencies in sequential data. ...
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  • 22
    HuixiangDou

    HuixiangDou

    Overcoming Group Chat Scenarios with LLM-based Technical Assistance

    HuixiangDou is an open-source large language model assistant designed specifically for technical question answering in group chat environments. The project addresses a common problem in developer communities where discussion channels become overwhelmed by repeated or irrelevant questions. To solve this issue, HuixiangDou implements a multi-stage pipeline that analyzes incoming messages, filters irrelevant conversations, and selectively generates responses when the assistant determines it can...
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  • 23
    llms-from-scratch-cn

    llms-from-scratch-cn

    Build a large language model from 0 only with Python foundation

    llms-from-scratch-cn is an educational open-source project designed to teach developers how to build large language models step by step using practical code and conceptual explanations. The repository provides a hands-on learning path that begins with the fundamentals of natural language processing and gradually progresses toward implementing full GPT-style architectures from the ground up. Rather than focusing on using pre-trained models through APIs, the project emphasizes understanding the internal mechanisms of modern language models, including tokenization, attention mechanisms, transformer architecture, and training workflows. ...
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  • 24
    LangChain for Java

    LangChain for Java

    LangChain4j is an open-source Java library

    ...The library provides a unified API that allows developers to connect Java applications to multiple AI providers and embedding databases without having to implement separate integrations for each service. Its architecture includes abstractions for prompts, chat interactions, document processing, embeddings, and vector storage, enabling developers to build complex AI workflows with minimal boilerplate code. LangChain4j also implements common design patterns used in generative AI systems, such as retrieval-augmented generation pipelines, tool calling, and intelligent agent frameworks. These abstractions allow developers to orchestrate interactions between language models, external tools, and knowledge bases in a structured and scalable way.
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  • 25
    Agent SOP

    Agent SOP

    Natural language workflows for AI agents

    ...It defines reusable SOP templates that agents can instantiate with context-specific parameters, allowing organizations to codify best practices for customer support, data processing, document workflows, or incident response. The framework supports monitoring and state tracking, so external systems can observe progress, intervene if necessary, and log outcomes for compliance or auditing. Integrations with common messaging and task orchestration systems enable SOP agents to interact with email, ticket queues, and databases as part of their workflows.
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