Search Results for "project-open" - Page 48
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Showing 17751 open source projects for "project-open"
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Diffusion for World Modeling
Learning agent trained in a diffusion world model
Diffusion for World Modeling is an experimental reinforcement learning system that trains intelligent agents inside a simulated environment generated by a diffusion-based world model. The project introduces the idea of using diffusion models, commonly used for image generation, to simulate the dynamics of an environment and predict future states based on previous observations and actions. Instead of interacting directly with a real environment, the reinforcement learning agent learns within a generative model that produces frames representing the environment. ... -
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Python Code Tutorials
The Python Code Tutorials
Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and... -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis. The repository integrates numerous popular machine learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, XGBoost, and Hugging Face. ... -
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AiLearning-Theory-Applying
Quickly get started with AI theory and practical applications
...It includes well-commented notebooks, datasets, and implementation examples that allow learners to reproduce experiments and understand the inner workings of various algorithms. 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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face.evoLVe
High-Performance Face Recognition Library on PaddlePaddle & PyTorch
face.evoLVe is a high-performance face recognition library designed for research and real-world applications in computer vision. The project provides a comprehensive framework for building and training modern face recognition models using deep learning architectures. It includes components for face alignment, landmark localization, data preprocessing, and model training pipelines that allow developers to construct end-to-end facial recognition systems. The repository supports multiple neural network backbones such as ResNet, DenseNet, MobileNet, and ShuffleNet, enabling experimentation with different architectures depending on performance requirements. ... -
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newspaper4k
Python library for scraping and analyzing online news articles easily
...Newspaper4k supports both single-article extraction and full news site processing, allowing users to build sources representing entire publications and iterate through their articles. It maintains compatibility with the original project so that existing code written for newspaper3k can continue working with minimal changes. -
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Toapi
Convert websites into structured APIs automatically with Python tool
...It also includes mechanisms for caching both page content and API requests, helping reduce repeated network calls and improving performance. Because the generated service is built on top of a Flask application, it can be deployed like any other Flask-based project and integrated into existing Python workflows. -
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Claude Code Tools
Practical productivity tools for Claude Code, Codex-CLI
Claude Code Tools is an open-source collection of command-line utilities and productivity plugins designed to enhance developer workflows when using AI coding agents such as Claude Code and Codex-CLI. The project focuses on solving common problems encountered in AI-assisted development environments, including managing session history, automating terminal interactions, and maintaining context across multiple coding sessions. -
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hCaptcha Challenger
Gracefully face hCaptcha challenge with multimodal llms
hCaptcha Challenger is an open-source automation framework designed to solve hCaptcha verification challenges using computer vision models and multimodal reasoning techniques. The project integrates machine learning models capable of analyzing visual captcha tasks and identifying the correct responses required to pass the verification process. Instead of relying on third-party captcha-solving services or browser scripts, the system operates independently by using pretrained neural networks that can classify images, detect objects, and interpret spatial relationships. ... -
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MatMul-Free LM
Implementation for MatMul-free LM
MatMul-Free LM is an experimental implementation of a large language model architecture designed to eliminate traditional matrix multiplication operations used in transformer networks. Since matrix multiplication is one of the most computationally expensive components of modern language models, the project explores alternative computational strategies that reduce hardware requirements while maintaining comparable performance. The architecture relies on quantization-aware training and lightweight operations to replace conventional dense matrix multiplications with more efficient alternatives. These optimizations can significantly reduce memory consumption and potentially improve computational efficiency during both training and inference. ... -
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Nano-vLLM
A lightweight vLLM implementation built from scratch
Nano-vLLM is a lightweight implementation of the vLLM inference engine designed to run large language models efficiently while maintaining a minimal and readable codebase. The project recreates the core functionality of vLLM in a simplified architecture written in approximately a thousand lines of Python, making it easier for developers and researchers to understand how modern LLM inference systems work. Despite its compact design, nano-vllm incorporates advanced optimization techniques such as prefix caching, tensor parallelism, and CUDA graph execution to achieve high performance during model inference. ... -
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AWS Agent Skills
AWS Skills for Agents
AWS Agent Skills is a repository that curates AWS-focused agent skills — capability modules that give AI assistants like Claude Code and Codex deep, practical knowledge across key Amazon Web Services domains. Instead of streaming giant documentation sets or relying on episodic web search, this project compresses AWS best practices, usage patterns, edge cases, and real-world engineering guides into pre-structured skill definitions that are token-efficient and tailored for reasoning. The skills cover critical AWS services such as IAM, Lambda, DynamoDB, S3, API Gateway, EKS, and many more, letting agents offer actionable advice on infrastructure as code, debugging, security configurations, and architectural workflows. ... -
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NagaAgent
A simple yet powerful agent framework for personal assistants
...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. Rather than being a simple chatbot, NagaAgent emphasizes persistent thought cycles, context retention, and the ability to decompose complex tasks into smaller executable units, earning it a place in research explorations of agent design. ... -
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Agent SOP
Natural language workflows for AI agents
Agent SOP is a framework that implements structured operational procedures (SOPs) for autonomous agents so that they can carry out complex multi-step tasks reliably and in a defined order. Instead of relying solely on broad language model reasoning, this project enforces explicit step sequences with checkpoints, conditional transitions, and rollback logic, making agent workflows more predictable and auditable. 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. ... -
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claude-code-transcripts
Tools for publishing transcripts for Claude Code sessions
claude-code-transcripts is a command-line utility that takes session files exported from Claude Code (in JSON or JSONL format) and turns them into clean, navigable HTML transcripts that can be viewed in any modern web browser. It is designed to make the often dense and verbose outputs from AI coding sessions easier to read, share, and archive by breaking conversations into paginated, annotated pages with navigable timelines of prompts and responses. Users can run this tool locally or fetch... -
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Unsloth-MLX
Bringing the Unsloth experience to Mac users via Apple's MLX framework
Unsloth-MLX offers developers the power of Unsloth’s efficient large language model fine-tuning experience on Apple Silicon Macs by wrapping Apple’s native MLX framework with an API fully compatible with Unsloth workflows. This project removes traditional barriers that prevent Mac users from prototyping and experimenting with LLM training locally by allowing the same code used in cloud GPU environments to run on M-series hardware, improving workflow continuity and reducing iteration costs. It supports loading and training Hugging Face models with fine-tuning strategies like SFT, DPO, ORPO, and GRPO and even handles exporting models to formats like GGUF for downstream use, although some limitations apply with quantized models. ... -
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MAI-UI
Real-World Centric Foundation GUI Agents
MAI-UI is a cutting-edge open-source project that implements a family of foundation GUI (Graphical User Interface) agent models capable of interpreting natural language and performing real-world GUI navigation and control tasks across mobile and desktop environments. Developed by Tongyi-MAI (Alibaba’s research initiative), the MAI-UI models are multimodal agents trained to understand user instructions and corresponding screenshots, grounding those instructions to on-screen elements and generating sequences of GUI actions such as taps, swipes, text input, and system commands. ... -
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StreamSpeech
StreamSpeech is a seamless model for offline speech recognition
StreamSpeech is an “all-in-one” speech model designed to perform offline and simultaneous speech recognition, speech translation, and speech synthesis within a single unified architecture. Developed as part of an ACL 2024 paper, it targets streaming and low-latency scenarios where intermediate results and final translations or synthetic speech must be produced continuously as audio is being received. The model supports eight tasks: offline ASR, speech-to-text translation, speech-to-speech... -
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Meta-World
Collections of robotics environments
Meta-World is an open-source benchmark suite of robotic manipulation environments focused on multi-task and meta reinforcement learning. It provides a large collection of continuous-control tasks, such as reaching, pushing, opening doors, and manipulating objects with a simulated robot arm. The library defines standardized benchmarks like MT1, MT10, and MT50 for multi-task learning, where a single policy is trained across different numbers of tasks. -
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Agently 4
Build GenAI application quick and easy
...With Agently, one can define agents that call different models, chain tasks, trigger workflows based on events, and switch models with minimal code changes. It abstracts away boilerplate around model API calls, tool usage, prompt management, and workflow state. The project aims at production-grade GenAI application development rather than just one-off scripts — you’ll find examples of news gathering, agentic workflows, control systems, etc. It is licensed under Apache-2.0, allowing commercial use and modification. Because it's built in Python, it integrates easily with existing data pipelines, databases, and agent architectures. -
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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... -
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HunyuanWorld-Mirror
Fast and Universal 3D reconstruction model for versatile tasks
...The pipeline emphasizes both speed and flexibility so creators can go from casual captures to assets without elaborate capture rigs. Outputs can include point clouds, estimated camera parameters, and other 3D representations that plug into typical graphics workflows. The project sits within a broader family of Hunyuan models that explore world generation and 3D-consistent understanding, and this mirror variant makes the reconstruction stack easier to test. It’s attractive for rapid prototyping of scenes, environment scans, or reference assets when you need repeatable 3D results from ordinary media. -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
...Because it stays close to vanilla PyTorch, you can integrate custom datasets and training loops without framework lock-in. It’s widely used as an educational reference for people learning transformers in vision and as a lightweight baseline for research prototypes. The project encourages experimentation—swap optimizers, change augmentations, or plug the transformer backbone into downstream tasks. -
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LitterBox
A secure sandbox environment for malware developers and red teamers
...Repo metadata and author pages highlight an active security-tools ecosystem around the maintainer, with CI and pull-request activity suggesting ongoing development. The project positions itself as a safe proving ground to reduce surprises in the field while minimizing operational risk. For teams exploring MCP integrations, notes mention pairing with LLM agents for assisted analysis. -
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ContextForge MCP Gateway
A Model Context Protocol (MCP) Gateway & Registry
...Operators can define virtual servers, wire multiple transports, and optionally enable an admin UI for management and monitoring. Packaged for quick starts via PyPI and Docker, it targets production reliability with health checks, metrics, and structured logs. The project positions itself as an integration hub so agentic apps can “connect once, use many” backends with consistent policy and lifecycle control.
