Search Results for "structure" - Page 5
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Showing 494 open source projects for "structure"
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Build Data Resilience - Take the Assessment TodayIs your recovery strategy as strong as you think? Take this quick self-assessment to check your recovery readiness and gain tailored insights. In only 2 minutes, you'll learn where you fall on the recovery readiness scale.
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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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screenshot-to-code
Drop in a screenshot and convert it to clean code
screenshot-to-code converts UI screenshots or design images into working front-end code, accelerating the path from concept to prototype. It uses modern vision-capable or code-generating models to infer layout structure, typography, and components, then outputs clean HTML/CSS (often Tailwind) or framework code. A web interface lets you upload images, tune options, and preview generated results, while a backend service orchestrates the model calls and post-processing. The tool focuses on practical developer outputs—semantic markup, reusable components, and readable classes—so the result is a starting point you can refine, not a throwaway demo. ... -
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aws-cli
Universal Command Line Interface for Amazon Web Services
The AWS CLI is the universal command-line interface for managing AWS services, automating tasks, and scripting cloud workflows. It exposes nearly every public API from EC2 and S3 to IAM, Lambda, and beyond, providing parity with the service SDKs in a tool you can run anywhere. Profiles, regions, single-sign-on, and credential helpers make it straightforward to switch contexts securely across accounts and environments. Its output controls and JMESPath querying let you slice, filter, and... -
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Instructor
Structured outputs for llms
Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. Its customizable nature permits the definition of... -
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Pacu
The AWS exploitation framework, designed for testing security
Pacu (named after a type of Piranha in the Amazon) is a comprehensive AWS security-testing toolkit designed for offensive security practitioners. While several AWS security scanners currently serve as the proverbial “Nessus” of the cloud, Pacu is designed to be the Metasploit equivalent. Written in Python 3 with a modular architecture, Pacu has tools for every step of the pen testing process, covering the full cyber kill chain. Pacu is the aggregation of all of the exploitation experience... -
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Former.skill
AI skill generator designed to reconstruct conversational personality
Ex Skill is an AI skill generator designed to reconstruct the conversational personality and shared memories of a former partner from personal data. It can analyze exported chats, photos, social media records, PDFs, images, and manually entered descriptions. The system builds separate memory and persona layers covering relationship history, habits, emotional patterns, communication style, and behavior. Generated personas can respond in a style modeled after the source material. New... -
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SmartNode
Visual simulation platform for space-based data backhaul scenarios
smartNode is a visual simulation platform for space-based intelligent relay and satellite data-return scenarios. It models the relationship between satellites, ground stations, relay links, and content-driven task scheduling. The project includes a Python backend and a browser-based frontend, making it suitable for local simulation, teaching, and secondary development. Users can view a three-dimensional space situation, submit data return tasks, and monitor resource states in real time. The... -
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Gpt-Agreement-Payment
End-to-end protocol replay toolkit for ChatGPT Plus/Team/Pro sub
...It documents and implements controlled workflows around account setup, payment routing, runtime state storage, and operational monitoring. The project includes both command-line and web UI modes, with Docker and manual deployment options. It stores runtime output and logs in a local SQLite-backed structure for review and debugging. Because it touches payment systems, account workflows, and fraud controls, it should be treated strictly as a research and compliance-sensitive project, not as a general-purpose automation product. Its main value is documenting complex payment-flow behavior in a reproducible technical environment for authorized analysis. -
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Polymarket Data
Polymarket Data Retriever that fetches, processes, and structures data
Polymarket Data is a comprehensive data engineering pipeline designed to collect, process, and structure trading activity from the Polymarket prediction market ecosystem into analyzable datasets. The system operates as a multi-stage pipeline that integrates data from both off-chain APIs and on-chain event sources, enabling users to reconstruct full trading activity including markets, order events, and executed trades. It begins by fetching market metadata such as questions, outcomes, and trading volumes, then proceeds to scrape order-filled events from a GraphQL-based subgraph, and finally transforms these raw events into structured trade-level records with calculated prices and directions. ... -
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Map-Anything
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Map-Anything is a universal, feed-forward transformer for metric 3D reconstruction that predicts a scene’s geometry and camera parameters directly from visual inputs. Instead of stitching together many task-specific models, it uses a single architecture that supports a wide range of 3D tasks—multi-image structure-from-motion, multi-view stereo, monocular metric depth, registration, depth completion, and more. The model flexibly accepts different input combinations (images, intrinsics, poses, sparse or dense depth) and produces a rich set of outputs including per-pixel 3D points, camera intrinsics, camera poses, ray directions, confidence maps, and validity masks. ... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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AI Hedge Fund
An AI Hedge Fund Team
...The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than a ready-to-use financial product, giving learners insight into the mechanics of quantitative finance automation. The project underlines AI’s potential in investment strategies but also carries disclaimers that it is for research and not financial advice. The implementation is designed so developers can study the pipeline end-to-end: from data ingestion through modeling to simulated portfolio management. -
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apk-reverse
Suitable for Android APK reverse engineering analysis
apk-reverse is an Agent Skill for structured Android application reverse-engineering work in authorized research environments. It is designed for Claude Code, Codex, and other systems that support the Agent Skills format rather than as a conventional end-user application. Its scope includes APK analysis, debloating, controlled Dex modifications, repacking, runtime investigation, and client-versus-server diagnosis. A gated workflow forces agents to verify assumptions, environment state, and... -
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Book1_Python-For-Beginners
The Iris Book: Addition, Subtraction, Multiplication, and Division
Book1_Python-For-Beginners is the introductory volume of the Visualize-ML series, designed to teach Python programming to newcomers with no prior coding experience. The repository emphasizes clarity and gradual skill building, starting from fundamental syntax and moving toward practical programming patterns. It integrates visual aids and annotated code examples to help learners understand not just how Python works but why certain patterns are used. The material is structured to support... -
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Book3_Elements-of-Mathematics
From Addition, Subtraction, Multiplication, and Division to ML
Book3_Elements-of-Mathematics is an open learning resource in the Visualize-ML collection that introduces core mathematical foundations required for modern data science and AI. The repository presents topics such as algebra, calculus fundamentals, and mathematical reasoning using a highly visual and beginner-friendly approach. Its goal is to reduce the intimidation barrier often associated with formal mathematics by combining diagrams, structured explanations, and applied examples. The... -
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Data Science Notes
Curated collection of data science learning materials
Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. Because it aggregates... -
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Oh My Zsh (ohmyzsh)
A framework for managing your zsh configuration
Oh My Zsh is a widely used, open-source, community-driven framework for managing Zsh shell configurations, providing hundreds of plugins, themes, and an auto-update system—designed to enhance developer productivity and shell aesthetics. Once installed, your terminal shell will become the talk of the town or your money back! With each keystroke in your command prompt, you'll take advantage of the hundreds of powerful plugins and beautiful themes. It's a good idea to inspect the install script... -
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Agent Skills
Specification and documentation for Agent Skills
agentskills is the specification and documentation repository for the Agent Skills open format, which defines a standardized way to package capabilities that AI agents can discover and use. A “skill” is treated as a foldered bundle containing instructions, optional scripts, and supporting resources, so agents can reliably apply a workflow or expertise area when it becomes relevant. The central goal is portability: you can write a skill once and reuse it across different agent runtimes and... -
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redis-py
Redis Python client
redis-py is the official Python client for interacting with Redis, the in-memory data structure store. It supports all Redis commands and data types, making it easy to build caching, messaging, or real-time analytics features in Python applications. With both synchronous and asyncio support, redis-py is suited for modern Python projects and integrates smoothly into web frameworks, task queues, and backend services. -
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Qwen-Image-Layered
Qwen-Image-Layered: Layered Decomposition for Inherent Editablity
Qwen-Image-Layered is an extension of the Qwen series of multimodal models that introduces layered image understanding, enabling the model to reason about hierarchical visual structures — such as separating foreground, background, objects, and contextual layers within an image. This architecture allows richer semantic interpretation, enabling use cases such as scene decomposition, object-level editing, layered captioning, and more fine-grained multimodal reasoning than with flat image... -
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Ideogram 4
Open image model at the forefront of design
...Ideogram 4 is especially useful for design-heavy outputs such as posters, ads, mockups, branded graphics, and images that include readable text. Its main value is combining open model access with professional-level control over image structure and visual direction. -
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How to Train Your GPT
Build a modern LLM from scratch. Every line commented
How to Train Your GPT is an interactive textbook that teaches users how to build, train, and run a modern language model from scratch. It is written for learners with minimal machine-learning background, using simple explanations, commented code, and practical examples. The project covers the same broad family of architecture behind systems such as GPT-style models, LLaMA-style models, Claude-style systems, and Mistral-style models. It includes chapters and topic explainers on tokenizers,... -
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RecursiveMAS
Offical Implementation for "Recursive Multi-Agent Systems"
...Instead of treating agents as independent units exchanging text outputs, it connects them through a shared latent computation loop, allowing internal “thought states” to be passed and refined iteratively. This recursive structure enables agents to build on each other’s intermediate reasoning, leading to deeper and more coherent solutions. The system uses a lightweight module called RecursiveLink to transfer and transform latent representations between agents, enabling seamless interaction even across heterogeneous models. It also incorporates an inner–outer loop training approach that optimizes the entire system collectively rather than tuning each agent separately. ... -
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Index
The SOTA Open-Source Browser Agent
...The system enables developers to instruct an AI agent to interact with web pages using natural language rather than traditional automation scripts. Instead of writing detailed browser automation code, users can describe the desired task and allow the agent to interpret the page structure, interact with elements, and complete multi-step workflows automatically. The project is built to integrate easily with applications through a simple programming interface, allowing developers to embed browser automation capabilities directly into their software systems. Index can perform tasks such as navigating pages, filling forms, collecting data, and analyzing web content without requiring manual scripting for each website. -
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Antigravity Awesome Skills
The Ultimate Collection of 700+ Agentic Skills for Claude Code
...The project includes skill definitions, example prompts, and usage patterns that highlight how modular abilities can be assembled into functioning assistants. Because it aims to reduce cognitive overhead, many skills show how to structure intents, handle context, and orchestrate multi-step reasoning without deep technical complexity. It also serves as inspiration for users looking to prototype new use cases — from conversational helpers that answer questions to workflow automators that trigger actions. -
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Backtrack Sampler
An easy-to-understand framework for LLM samplers
Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs. -
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EasyR1
An Efficient, Scalable, Multi-Modality RL Training Framework
EasyR1 is a streamlined training framework for building “R1-style” reasoning models from open-source LLMs with minimal boilerplate. It focuses on the full reasoning stack—data preparation, supervised fine-tuning, preference or outcome-based optimization, and lightweight evaluation—so you can iterate quickly on chain-of-thought–heavy tasks. The project’s philosophy is practicality: sensible defaults, one-command recipes, and compatibility with popular base models let you stand up experiments...
