Showing 295 open source projects for "patterns"

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    Paessler - Monitor Your Whole Network in Minutes

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  • 1
    IVRE

    IVRE

    Open source framework for large scale network reconnaissance and analy

    ...IVRE stores the collected data in a database and offers multiple ways to explore and analyze it, including a web interface, command line tools, and a Python API. This allows security professionals to query scan results, inspect network flows, and identify patterns across large datasets. The project can be used to build self hosted alternatives to internet scanning services such as Shodan or Censys, giving organizations full control over their own reconnaissance infrastructure.
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  • 2
    AG-UI

    AG-UI

    The Agent-User Interaction Protocol

    AG-UI is an open, lightweight protocol for connecting AI agents to user-facing applications through a standardized event-based interface. It is designed to make agent behavior visible, interactive, and controllable inside real-time front-end experiences. Instead of treating an AI agent as a black-box chat endpoint, AG-UI defines structured events for messages, tool calls, state changes, lifecycle updates, and user interactions. This makes it easier for developers to build agent-powered apps...
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  • 3
    Scweet

    Scweet

    Scrape tweets, profiles, followers and following from Twitter/X

    ...Instead of depending on deprecated unauthenticated scraping methods, it works by using X’s web GraphQL API together with authenticated browser cookies, which gives it a more current and practical approach for data extraction. The project supports a broad set of collection patterns, including searches by keyword, hashtag, user, date range, engagement thresholds, language, and location, making it useful for research, monitoring, and data gathering workflows. It is built for both local use and higher-volume runs, with support for proxies, dedicated accounts, and multi-account cookie handling to improve reliability at scale. ...
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  • 4
    BeeAI Framework

    BeeAI Framework

    Build production-ready AI agents in both Python and Typescript

    BeeAI Framework is an open-source, production-grade toolkit designed for building intelligent AI agents and complex multi-agent systems that can reason, act, and collaborate to solve real-world problems at scale. It goes beyond simple prompt-based interactions by introducing rule-based governance and constraint enforcement, enabling developers to create agents with predictable and controllable behavior while still preserving advanced reasoning capabilities. The framework supports both Python...
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    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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  • 5
    Code2Prompt

    Code2Prompt

    Convert codebases into structured prompts optimized for LLM analysis

    code2prompt is an open source command line tool designed to convert an entire codebase into a structured prompt that can be easily used with large language models. It analyzes a project directory, gathers relevant source files, and formats them into a single prompt that includes the source tree and code content. This approach helps developers quickly provide full project context to AI models without manually copying files or assembling prompts. code2prompt is built in Rust and focuses on...
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  • 6
    KVCache-Factory

    KVCache-Factory

    Unified KV Cache Compression Methods for Auto-Regressive Models

    KVCache-Factory is an open-source research framework designed to explore and implement unified key-value cache compression techniques for autoregressive transformer models. In large language models, the key-value cache stores intermediate attention states that enable efficient token generation during inference, but these caches can consume large amounts of GPU memory when handling long contexts. KVCache-Factory provides a platform for implementing and evaluating multiple compression...
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  • 7
    Claude Code Skills & Plugins Hub

    Claude Code Skills & Plugins Hub

    270+ Claude Code plugins with 739 agent skills

    ...These plugins cover a wide range of domains including DevOps automation, security testing, API debugging, infrastructure management, and AI workflow orchestration. The project also includes orchestration patterns and best practices that guide how multiple AI agents or tools can collaborate effectively in software development workflows. Developers can install plugins through a package-style plugin system and integrate them with their Claude Code environment using standardized commands.
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  • 8
    Anomaly Detection Learning Resources

    Anomaly Detection Learning Resources

    Anomaly detection related books, papers, videos, and toolboxes

    ...The project serves as a centralized index for researchers and practitioners who want to explore algorithms, datasets, and publications associated with detecting unusual patterns in data. The repository organizes resources into structured categories such as books, tutorials, academic papers, datasets, benchmark frameworks, and open-source toolkits. It includes materials covering a wide range of anomaly detection domains, including time series data, graph data, tabular datasets, and real-time monitoring systems. ...
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  • 9
    Deep Search Agent

    Deep Search Agent

    Implement a concise and clear Deep Search Agent from 0

    ...The project is positioned primarily as a proof of concept for deep research agents rather than a production-ready system. Its architecture highlights agent loops, tool calling, and stepwise execution, which are increasingly important patterns in modern AI automation. Overall, the demo serves as a practical reference for developers exploring autonomous research agents and multi-tool LLM orchestration.
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  • 10
    NagaAgent

    NagaAgent

    A simple yet powerful agent framework for personal assistants

    NagaAgent is an experimental framework for building interactive virtual agents capable of autonomous reasoning, dialog, and task execution using components that mirror human cognitive patterns. It provides abstractions for representing goals, context, and state so that agents can plan sequences of actions, evaluate outcomes, and adjust behavior over time. The project includes mechanisms for semantic memory, reasoning pipelines, and integration points with external data sources and language models so that agents can interpret natural language instructions and produce coherent multi-step outputs. ...
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  • 11
    Agent Reinforcement Trainer

    Agent Reinforcement Trainer

    Train multi-step agents for real-world tasks using GRPO

    ...The framework is designed to integrate easily with Python applications, abstracting much of the RL infrastructure so developers can train agents without deep RL expertise or heavy infrastructure overhead. ART also supports scalable training patterns, observability tools, and integration with hosted platforms like Weights & Biases, and it provides notebooks that demonstrate training on standard benchmarks and tasks.
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  • 12
    zpdf

    zpdf

    Zero-copy PDF text extraction library written in Zig

    zpdf is a high-performance PDF text extraction library written in Zig that focuses on speed, low overhead, and modern parsing techniques. It leans heavily on memory-mapped file reading and zero-copy patterns where possible, so it can scan large PDFs without repeatedly copying data around in memory. The library supports streaming extraction using efficient arena allocation, making it well suited for workloads that need to process big documents quickly or in batches. It implements multiple PDF decompression filters and handles common font encoding pathways, which are essential for turning raw PDF content streams into readable text. ...
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  • 13
    AutoCoder

    AutoCoder

    A long-running autonomous coding agent powered by the Claude Agent

    Autocoder is an experimental auto-generation engine that transforms high-level prompts or structured descriptions into functioning source code, models, or systems with minimal manual intervention. Rather than hand-writing boilerplate or repetitive patterns, users supply a specification—such as a description of a feature, a function prototype, or a module outline—and Autocoder fills in complete implementations that compile and run. It is built to support iterative refinement: after generating an initial draft, you can provide feedback or corrections, and the system will adjust the output to match evolving intentions. ...
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  • 14
    Universal Commerce Protocol

    Universal Commerce Protocol

    Specification and documentation for the Universal Commerce Protocol

    UCP (Universal Commerce Protocol) is an open standard intended to make commerce integrations interoperable across platforms, agents, businesses, and payment providers without bespoke, one-off connector builds. It defines a shared “common language” and functional primitives so that different systems can express commerce actions and state transitions in a consistent way. The protocol is designed around the realities of existing retail infrastructure, aiming to fit into current operational...
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  • 15
    AI Agents Masterclass

    AI Agents Masterclass

    Follow along with my AI Agents Masterclass videos

    AI Agents Masterclass is an educational open-source repository designed to teach developers how to build, train, and deploy intelligent AI agents using modern tooling and workflow patterns. The project includes structured lessons, code examples, and practical exercises that cover foundational concepts like prompt engineering, chaining agents, tool usage, plan execution, evaluation, and safety considerations. It breaks down how autonomous agents interact with external systems, handle iterative reasoning, and integrate with third-party services or APIs to perform real tasks — for example, web search, browsing, scheduling, or coding assistance. ...
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  • 16
    Context Engineering Template

    Context Engineering Template

    Context engineering is the new vibe coding

    ...The repository provides templates such as CLAUDE.md for defining global project rules, INITIAL.md for feature requests, and folders for examples, PRPs, validation scripts, and settings to support systematic prompt generation and execution with tools like Claude Code. By using this template, teams can ensure consistency across AI outputs, reduce errors that stem from contextual misunderstandings, and build reusable patterns.
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  • 17
    Chinese-XLNet

    Chinese-XLNet

    Chinese XLNet pre-trained model

    ...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. Chinese-XLNet offers an alternative to models like BERT by emphasizing autoregressive and permutation-based learning, which can lead to performance improvements on certain benchmarks and tasks.
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  • 18
    Lingvo

    Lingvo

    Framework for building neural networks

    Lingvo is a TensorFlow based framework focused on building and training sequence models, especially for language and speech tasks. It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state...
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  • 19
    Advanced RAG Techniques

    Advanced RAG Techniques

    Advanced techniques for RAG systems

    Advanced RAG Techniques is a comprehensive collection of tutorials and implementations focused on advanced Retrieval-Augmented Generation (RAG) systems. It is designed to help practitioners move beyond basic RAG setups and explore techniques that improve retrieval quality, context construction, and answer robustness. The repository organizes techniques into categories such as foundational RAG, query enhancement, context enrichment, and advanced retrieval, making it easier to navigate...
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  • 20
    Granite TSFM

    Granite TSFM

    Foundation Models for Time Series

    ...Issues and examples in the tracker illustrate common tasks such as slicing inference windows or using pipeline helpers that return pandas DataFrames, grounding the library in day-to-day time-series operations. The ecosystem around TSFM also includes a community cookbook of “recipes” that showcase capabilities and patterns. Overall, the repo is designed as a hands-on companion for teams adopting time-series foundation models in production-leaning settings.
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  • 21
    Purple Llama

    Purple Llama

    Set of tools to assess and improve LLM security

    Purple Llama is an umbrella safety initiative that aggregates tools, benchmarks, and mitigations to help developers build responsibly with open generative AI. Its scope spans input and output safeguards, cybersecurity-focused evaluations, and reference shields that can be inserted at inference time. The project evolves as a hub for safety research artifacts like Llama Guard and Code Shield, along with dataset specs and how-to guides for integrating checks into applications. CyberSecEval, one...
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  • 22
    Boltons

    Boltons

    250+ constructs, recipes, and snippets which extend the Python library

    ...If you’ve found a natural “next-step” library worth mentioning, consider filing an issue! boltons has a minimalist architecture, remain as consistent, and self-contained as possible, with an eye toward maintaining its range of use cases and usage patterns as wide as possible. The boltons package depends on no packages, making it easy for inclusion into a project.
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  • 23
    Open Model Zoo

    Open Model Zoo

    Pre-trained Deep Learning models and demos

    ...It includes hundreds of models covering object detection, classification, segmentation, pose estimation, speech recognition, text-to-speech, and more, many of which are already converted into formats optimized for inference on CPUs, GPUs, VPUs, and other accelerators supported by OpenVINO. In addition to model files, Open Model Zoo provides demo applications that show realistic usage patterns and help developers quickly prototype and understand inference pipelines in C++, Python, or via the OpenCV Graph API. Tools in the repository also help automate model downloads and other tasks, making it easier to incorporate these models into production systems or custom solutions.
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  • 24
    Pal

    Pal

    A personal context-agent that learns how you work

    ...The agent can perform web research, summarize information, and store insights so that useful discoveries are not lost across conversations or sessions. Over time, the agent learns from interactions, remembers patterns that worked well, and applies those learnings to similar tasks in the future, allowing it to improve without requiring additional model training.
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  • 25
    Universal Commerce Protocol (UCP)

    Universal Commerce Protocol (UCP)

    The common language for platforms, agents and businesses.

    Universal Commerce Protocol (UCP) is an open standard designed to unify how platforms, businesses, and payment providers interact across the modern commerce ecosystem. It provides a common language that eliminates fragmented, custom integrations and enables seamless interoperability between diverse commerce systems. Built for an increasingly agentic web, UCP supports AI-driven platforms that can discover products, manage carts, and complete transactions securely on a user’s behalf. Its...
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