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Showing 259 open source projects for "include"
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1
Vibe
Transcribe on your own
Vibe is an open-source project by thewh1teagle designed to deliver a collaborative and interactive social application experience, though its specifics depend on its evolving community scope; its development often focuses on connecting users through dynamic features that can include chat, shared spaces, and immersive interactions. The repository typically includes backend logic, frontend integration, and real-time communication stacks to support live user engagement, performance optimizations, and modular features that adapt to social workflows. Because open-source social platforms benefit from transparency and community contribution, Vibe’s codebase allows developers to experiment with new social features, customize existing components, and build integrations with popular services for authentication, media sharing, and notifications. ... -
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Claude Skills
Public repository for Agent Skills
...Rather than relying on handcrafted prompts every time, Skills teach an AI agent procedural knowledge and task-specific workflows so it can apply that expertise reliably, whether the task involves document creation, data analysis, design generation, or technical automation. Each Skill lives in its own directory with a SKILL.md file containing metadata and instructions, and can include supplemental scripts or assets that the agent uses to perform complex operations when relevant. -
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Wurst Client
Minecraft Wurst Hacked Client v7
...The project provides a custom client environment where players can enable various automated tools, overlays, and gameplay enhancements that alter how the game behaves. These features may include movement enhancements, automation utilities, and visualization tools that provide additional information about the game world. Wurst7 is typically installed as a Fabric mod and runs alongside the standard Minecraft Java Edition client. The client includes a graphical interface that allows users to toggle different modules and configure their behavior during gameplay. ... -
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OpenClaude
Claude Code opened to any LLM
...It likely includes support for executing tasks, managing context, and interacting with external tools, allowing agents to perform real-world actions beyond simple text generation. The architecture emphasizes flexibility, enabling developers to adapt the system to different use cases and integrate it with various models or APIs. It may also include modular components for extending functionality, such as plugins or skills. The project reflects a broader trend toward open and decentralized AI systems that prioritize transparency and control. -
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free-code
The free build of Claude Code
...The project is designed to encourage collaboration and knowledge sharing within the developer community, making it easier for beginners and experienced developers alike to access useful code snippets and frameworks. It may include a collection of curated resources that span multiple programming languages and use cases. Free-code emphasizes openness and accessibility, ensuring that users can freely explore, modify, and distribute the code. Its structure often supports modular usage, allowing developers to pick and choose what they need for their projects. -
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Open WebUI
User-friendly AI Interface
...It supports various LLM runners like Ollama and OpenAI-compatible APIs, with a built-in inference engine for Retrieval Augmented Generation (RAG), making it a powerful AI deployment solution. Key features include effortless setup via Docker or Kubernetes, seamless integration with OpenAI-compatible APIs, granular permissions and user groups for enhanced security, responsive design across devices, and full Markdown and LaTeX support for enriched interactions. Additionally, Open WebUI offers a Progressive Web App (PWA) for mobile devices, providing offline access and a native app-like experience. ... -
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IVY
The Unified Machine Learning Framework
Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. -
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caveman
Why use many token when few token do trick
...The project often serves as a foundation for developers who want to build applications quickly without being constrained by heavy conventions or extensive configuration. It may include utilities for routing, state handling, or simple server logic, depending on its implementation scope. Caveman embraces a philosophy of “less is more,” encouraging developers to focus on core functionality rather than framework overhead. Its design makes it particularly useful for experimentation, small tools, or proof-of-concept applications. -
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DeepSeek V2
Strong, Economical, and Efficient Mixture-of-Experts Language Model
...Because DeepSeek is pushing open-weight competition, this V2 iteration is meant to solidify its position in benchmark rankings and in developer adoption. The code in the repository may include description files, support for tool use or plug-in architectures, and artifacts showing fine-tuning or prompt templates. -
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Graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
...It is particularly useful in domains such as network analysis, knowledge graphs, and system architecture visualization. The architecture emphasizes flexibility, enabling users to customize how data is mapped and displayed. It may also include analytical features to explore patterns, clusters, or anomalies within the graph. Overall, Graphify serves as a bridge between raw data and visual insight. -
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Machine Learning Study
This repository is for helping those interested in machine learning
...Many examples include dataset preparation, visualization of results, and experimentation with different modeling approaches. -
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SDGym
Benchmarking synthetic data generation methods
...The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. ... -
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TorchIO
Medical imaging toolkit for deep learning
...Transforms include typical computer vision operations such as random affine transformations and also domain-specific ones such as simulation of intensity artifacts due to MRI magnetic field inhomogeneity. -
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System Design Academy
If you want to become good at AI & system design, join this newsletter
...It organizes a large collection of articles and case studies into searchable alphabetical sections. Real-world examples examine how major services scale storage, messaging, streaming, payments, collaboration, and other workloads. Fundamental topics include APIs, caching, consistency, databases, DNS, Docker, Kafka, Kubernetes, load balancing, microservices, and service discovery. Separate guides cover interview frameworks and design exercises for products such as ChatGPT, Spotify, WhatsApp, and YouTube. The repository also collects AI agent concepts and selected software architecture white papers. -
15
YuE
Open source AI model for generating full songs from lyrics prompts
YuE is an open source project that provides a foundation model designed for full-song music generation using artificial intelligence. It focuses on transforming text inputs such as lyrics and genre prompts into complete musical compositions that include both vocal and instrumental tracks. Unlike many shorter audio generators, the model is capable of producing songs that last several minutes while maintaining coherent musical structure and alignment with the provided lyrics. YuE introduces a family of models built on large language model architectures that process music generation as a sequence prediction task. ... -
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Qwen
The official repo of Qwen chat & pretrained large language model
...These models, which range from smaller to larger configurations, are designed for a wide range of natural language processing tasks. They are openly available for research and commercial use, with Qwen's code and model weights shared on GitHub. Qwen's capabilities include text generation, comprehension, and conversation, making it a versatile tool for developers looking to integrate advanced AI functionalities into their applications. -
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Claude Autoresearch
Claude Autoresearch Skill, autonomous goal-directed iteration
...Its iterative loop enables deeper exploration of topics over time, making it particularly useful for complex or open-ended research questions. The architecture emphasizes autonomy, reducing the need for constant user input while still producing meaningful insights. It may also include summarization and reporting capabilities to present findings in a digestible format. Overall, autoresearch represents a step toward self-directed knowledge discovery systems that continuously improve their outputs through iteration. -
18
img2obj
Codex plugin that turns attached object images into code-only
...Reconstruction proceeds through blockout, form, look development, and interaction phases so details are added in a controlled order. The plugin supports hard-surface objects, organic forms, vegetation, fabrics, glass, hair, emissive surfaces, and decals. Generated models can include animation-ready parent-child relationships and detachable or articulated parts. Visual review compares browser renders with the source and requires important differences to be corrected before promotion. Outputs include a TypeScript Three.js factory, structured specifications, comparison evidence, optional procedural PBR maps, and review checkpoints. -
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PenEcho
Think with AI beyond the chat box
...Users can draw with pressure-sensitive ink, erase, pan, zoom, type formatted text, and arrange ideas across a large virtual workspace. The application sends focused visual regions to an API, Codex CLI, or Claude CLI and converts model responses into editable canvas commands. AI output can include text, formulas, plots, mixed drawings, erasures, and declarative animations. Sparse tile rendering keeps the 20,000-by-20,000 logical canvas efficient without allocating one enormous bitmap. Local snapshots, undo and redo, lasso selection, PNG export, and manual or automatic AI modes support iterative work. PenEcho is available as a desktop application or Node.js package and supports configurable models, reasoning levels, request retention, and plugins. -
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Agent Skills
Skills for AI coding agents
...In this repository, each skill adheres to the Agent Skills specification, meaning they’re defined as folders with a SKILL.md file (containing task descriptions and step-by-step guidance) and can include helper scripts and reference material that the agent can execute or consult when invoked. The goal of the project is to make it easy for AI assistants like Claude Code, OpenCode, Cursor, Codex, and others that support this open ecosystem to automatically apply best practices or perform concrete actions when a relevant user intent is detected. ... -
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Repomix
Repomix is a powerful tool that packs your entire repository
Repomix is a developer utility that packages an entire code repository into a single AI-friendly file for analysis by large language models. Its core purpose is to simplify the process of feeding complex codebases into AI tools by consolidating files, metadata, and structure into a unified representation. The tool is particularly valuable for code review, refactoring assistance, and automated documentation workflows where context size matters. Repomix intelligently respects ignore rules and... -
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Lingua-Py
The most accurate natural language detection library for Python
...This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine learning frameworks or natural language processing applications. In cases where you don't need the full-fledged functionality of those systems or don't want to learn the ropes of those, a small flexible library comes in handy. -
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Deepchecks
Test Suites for validating ML models & data
Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate... -
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PicoClaw
Ultra-Efficient AI Assistant in Go
...PicoClaw can run on hardware costing as little as $10 and on resource-constrained environments like RISC-V or ARM boards, with cross-architecture portability achieved through a single self-contained binary. The project’s goals include broad platform support (including Linux, macOS, and multiple CPU architectures), rapid startup times that make the assistant feel responsive, and integration with popular messaging platforms via gateways or bots. -
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img2threejs
Rebuild the object in a reference image as a code-only, procedural
...It generates a TypeScript THREE.Group factory from primitives, procedural shaders, and generated geometry rather than extracting or downloading a mesh. The resulting hierarchy can include pivots, sockets, colliders, and destruction groups so the model is ready for interaction and animation. A staged pipeline evaluates suitability, defines a detailed specification, builds successive passes, renders browser previews, and compares them with the source image. Quality gates require structural detail, material realism, correct attachments, and passing visual-review scores. ...
