Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 24
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Showing 1781 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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We help you deliver Virtual and Hybrid Events using our Award Winning end-to-end Event Management PlatformEventsAIR have been anticipating and responding to the ever-changing event industry needs for over 30 years, providing innovative solutions that empower event organizers to create successful events around the globe.
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DataHub is the leading open-source data catalog helping teams discover, understand, and govern their data assets.Built on an open source foundation with a thriving community of 13,000+ members, DataHub gives you unmatched flexibility to customize and extend without vendor lock-in. DataHub Cloud is a modern metadata platform with REST and GraphQL APIs that optimize performance for complex queries, essential for AI-ready data management and ML lifecycle support.
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Gradio
Create UIs for your machine learning model in Python in 3 minutes
Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere! Gradio can be installed with pip. Creating a Gradio interface only requires adding a couple lines of code to your project. You can choose from a variety of interface types to interface your function. Gradio can be embedded in Python notebooks or presented as a webpage. A Gradio interface can automatically generate a public link you can share with colleagues that lets them interact with the model on your computer remotely from their own devices. ... -
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ex-skill
Distill your ex into an AI Skill
...The system works by ingesting various forms of personal data such as chat logs, social media content, photos, and user-provided descriptions, then structuring this information into a layered representation that combines memory and persona modeling. It is designed to run within Claude Code environments, where users can generate, manage, and interact with these personalized AI entities through command-based interfaces. The project emphasizes emotional realism by reconstructing conversational tone, habits, and contextual memories, enabling interactions that feel consistent with the original person. -
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MiniMax Skills
Development skills for AI coding agents
...It defines a set of reusable “skills” that encapsulate best practices, architectural patterns, and step-by-step processes for building applications across multiple platforms. These skills can be integrated into AI tools to improve the quality and consistency of generated code, particularly in areas such as frontend development, backend systems, mobile applications, and multimedia processing. The system supports a wide range of technologies and workflows, allowing developers to leverage AI assistance for both simple tasks and large-scale projects. It is designed to be extensible, enabling contributors to add new skills or enhance existing ones as development practices evolve. -
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Toad
Unified terminal AI tool for exploring and editing codebases
...Built in Python, it focuses on transparency and control by letting users load context intentionally and inspect how the AI processes files. Toad supports structured conversations, enabling navigation through code with clear references instead of opaque outputs. Inspired by notebook-style workflows, it allows reuse of previous interactions and exporting of results. Toad is vendor-agnostic, meaning it can work with different AI agents while maintaining a consistent user experience. It emphasizes developer intent over automation, keeping humans in control of decisions while using AI as a collaborative assistant for coding, refactoring, and analysis. -
Fully managed relational database service for MySQL, PostgreSQL, and SQL ServerCloud SQL manages your databases so you don't have to, so your business can run without disruption. It automates all your backups, replication, patches, encryption, and storage capacity increases to give your applications the reliability, scalability, and security they need.
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EventCatalog
Open source tool for documenting and exploring event-driven systems
EventCatalog is an open source documentation tool designed for event-driven architectures. It helps teams organize, document, and understand complex systems by mapping events, services, domains, and flows in one place. Instead of scattered knowledge, it creates a central, searchable catalog that improves visibility and collaboration. Documentation is generated and maintained automatically, making it easier to keep systems up to date as they evolve. With built-in discoverability features,... -
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AIBuildAI
An AI agent that automatically builds AI models
...The project explores recursive AI development, where models are used not only as tools but as builders capable of constructing other AI systems, workflows, or components. It provides a structured environment for orchestrating agents that can plan, execute, and refine tasks such as code generation, system design, and iterative improvement loops. The framework is designed to support experimentation with self-improving AI pipelines, allowing developers to test concepts like automated architecture search or adaptive system evolution. It integrates multiple components including prompt management, execution control, and feedback loops to ensure that generated outputs can be evaluated and improved over time. -
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machine-learning-refined
Master the fundamentals of machine learning, deep learning
...The project accompanies a series of textbooks and teaching materials that focus on making machine learning concepts accessible through visual demonstrations and simple code implementations. Instead of presenting algorithms purely through mathematical derivations, the repository emphasizes geometric intuition, visualization, and step-by-step experimentation. It includes Jupyter notebooks and scripts that illustrate core machine learning topics such as regression, classification, optimization methods, and neural networks. ... -
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Deepnote
Deepnote is a drop-in replacement for Jupyter
Deepnote is an open-source collaborative data science notebook platform designed as a modern alternative to traditional Jupyter notebooks. The project provides an AI-first computational environment where users can write, analyze, and share code, data, and visualizations in a single integrated workspace. Built on top of the Jupyter kernel ecosystem, it maintains compatibility with existing notebook workflows while introducing additional features focused on collaboration and automation. The system supports programming languages such as Python, R, and SQL and allows users to execute and analyze data directly within interactive notebooks. ... -
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Machine Learning Foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics
Machine Learning Foundations repository contains the code, notebooks, and teaching materials used in Jon Krohn’s Machine Learning Foundations curriculum. The project focuses on explaining the fundamental mathematical and computational concepts that underpin modern machine learning and artificial intelligence systems. The materials cover essential topics such as linear algebra, calculus, statistics, and probability, which form the theoretical basis of many machine learning algorithms. ... -
Windocks - Docker Oracle and SQL Server ContainersWindocks is a leader in cloud native database DevOps, recognized by Gartner as a Cool Vendor, and as an innovator by Bloor research in Test Data Management. Novartis, DriveTime, American Family Insurance, and other enterprises rely on Windocks for on-demand database environments for development, testing, and DevOps. Windocks software is easily downloaded for evaluation on standard Linux and Windows servers, for use on-premises or cloud, and for data delivery of SQL Server, Oracle, PostgreSQL, and MySQL to Docker containers or conventional database instances.
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python-small-examples
Focus on creating classic Python small examples and cases
python-small-examples is an open-source educational repository that contains hundreds of concise Python programming examples designed to illustrate practical coding techniques. The project focuses on teaching programming concepts through small, focused scripts that demonstrate common tasks in data processing, visualization, and general programming. Each example highlights a specific function or programming pattern so that learners can quickly understand how to apply Python features in... -
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LlamaDeploy
Deploy your agentic worfklows to production
...The project provides an asynchronous architecture that allows developers to deploy complex multi-agent workflows as scalable microservices. It enables teams to move from experimental prototypes to production systems with minimal changes to existing LlamaIndex code, making it easier to operationalize AI agents. The system supports orchestrating multiple services, handling communication between agents, and managing workflow execution in distributed environments. Developers can define workflows that involve multiple steps such as data retrieval, reasoning, tool invocation, and response generation, then deploy them using the framework’s infrastructure tools. ... -
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minbpe
Minimal, clean code for the Byte Pair Encoding (BPE) algorithm
minbpe is a minimal, clean implementation of byte-level Byte Pair Encoding (BPE), the tokenization approach widely used in modern language models. It operates on UTF-8 encoded bytes rather than Unicode characters, which makes it robust to arbitrary text inputs and avoids needing a language-specific character vocabulary. The repository is structured as a teaching-oriented implementation that shows how to train a tokenizer by learning merge rules, then apply those merges to encode text into... -
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Hello-Agents
Building an Intelligent Agent from Scratch
...It walks users through core concepts such as ReAct-style reasoning, tool usage, memory handling, and multi-step task execution, enabling hands-on experimentation with modern LLM-powered agent systems. The repository is structured as a progressive learning path, combining theory, exercises, and runnable code so users can incrementally build more capable agents. Its goal is to demystify agent engineering and help developers move from simple prompt scripts to robust autonomous systems. -
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Super comprehensive deep learning notes
Super Comprehensive Deep Learning Notes
...The repository contains hundreds of Jupyter notebooks that are richly annotated and organized by topic, progressing from basic Python and PyTorch fundamentals to advanced neural network designs like ResNet, transformers, and object detection algorithms. It’s not just a dry code repository; it includes theoretical explanations alongside hands-on examples, loss function explorations, optimization routines, and full end-to-end experiments on real datasets, making it highly suitable for both self-study and classroom use. -
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Big-AGI
AI suite powered by state-of-the-art models and providing advanced AI
...It unifies access to multiple large language models (LLMs) and AI services through a modern web UI that emphasizes efficient interaction, flexibility, and extensibility, enabling users to conduct multi-model chats, execute code, generate images, and perform voice or text-based tasks all in one place. The workspace includes advanced features like Beam, which enables multi-model consensus and comparative responses to improve reliability and reduce hallucination, and robust persona management to tailor responses to specific roles or workflows. Big-AGI can be self-hosted or deployed in cloud environments, giving users full control over data and model access limits and avoiding vendor lock-in. -
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SkillForge
Ultimate meta-skill for generating best-in-class Claude Code skills
SkillForge is a systematic methodology and tooling framework for creating high-quality AI “skills” specifically optimized for Claude Code integrations, treating skill creation as an engineering discipline rather than an ad-hoc art form. It introduces a multi-phase architecture where every input or request is triaged intelligently, analyzed deeply through structured lenses, specified formally, synthesized with automated generation, and finally subjected to multi-agent review before consideration complete. ... -
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agentation
The visual feedback tool for agents
...Instead of describing UI elements in text — like “the blue button in the sidebar” — users click directly on elements to automatically capture selectors, positions, and contextual metadata that can be consumed by AI agents to locate exact code references. This approach dramatically improves clarity and reduces ambiguity when working with AI tools that generate or modify UI code, making the handoff between human design intent and AI execution much clearer. The package installs into a React app and shows a floating toolbar that lets you activate element selection and add notes during a development session, helping you capture precise targets for improved AI output. -
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GitHub Copilot SDK
Multi-platform SDK for integrating GitHub Copilot Agent into apps
The GitHub Copilot SDK is a developer toolkit that enables creators to build custom AI-assisted experiences powered by Copilot models within their own applications, editors, and workflows. Instead of being limited to editors like VS Code, this SDK lets teams embed Copilot-style code suggestions, natural language assistance, and predictive completions anywhere they see fit—such as internal IDEs, browser extensions, documentation portals, or bespoke tools tailored to specific languages or frameworks. It provides a structured API surface for invoking the Copilot model in context with the surrounding user state, capturing document content, cursor position, and invocation triggers so suggestions are relevant and responsive. ... -
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MiniMind-V
"Big Model" trains a visual multimodal VLM with 26M parameters
MiniMind-V is an experimental open-source project that aims to train a very small multimodal vision–language model (VLM) from scratch with extremely low compute and cost, making research and experimentation accessible to more people. The repository showcases training workflows and code designed to produce a 26-million parameter model—including both image and text capabilities—using minimal resources in very little time, reflecting a trend toward democratizing AI research. MiniMind-V combines techniques from modern vision-language modeling but focuses on efficiency and simplicity so that individuals or small teams can explore multimodal learning without massive GPU clusters. ... -
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Sled
Teleport Claude Code, Codex or Gemini CLI to your phone
Sled under the layercodedev account appears to be a lightweight web and mobile UI aimed at interacting with local coding agents, likely including AI-assisted coding models or remote execution integrations; it’s designed in TypeScript/JavaScript and intended to let developers use or control coding agents from various devices. Although specific details in the repository are limited without direct project documentation, context and related online mentions indicate it functions as a local... -
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Step1X-3D
High-Fidelity and Controllable Generation of Textured 3D Assets
Step1X-3D is an open-source framework for generating high-fidelity textured 3D assets from scratch — both their geometry and surface textures — using modern generative AI techniques. It combines a hybrid architecture: a geometry generation stage using a VAE-DiT model to output a watertight 3D representation (e.g. TSDF surface), and a texture synthesis stage that conditions on geometry and optionally reference input (or prompts) to produce view-consistent textures using a diffusion-based... -
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HunyuanOCR
OCR expert VLM powered by Hunyuan's native multimodal architecture
...HunyuanOCR handles complex documents: multi-column layouts, tables, mathematical formulas, mixed languages, handwritten or stylized fonts, receipts, tickets, and even video-frame subtitles. The project provides code, pretrained weights, and inference instructions, making it feasible to deploy locally or on a server, and to integrate with applications. -
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handson-ml
Teaching you the fundamentals of Machine Learning in python
...The examples underscore fundamentals like bias-variance trade-offs, regularization, and proper validation, grounding learners before they move to deep nets. Even though the deep learning stack evolved, the classical ML sections remain highly relevant for production data problems. The code is crafted to be clear rather than clever, prioritizing readability for newcomers. As a historical snapshot and a still-useful primer, it pairs well with the second edition for understanding how the ecosystem matured. -
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CutLER
Code release for Cut and Learn for Unsupervised Object Detection
CutLER is an approach for unsupervised object detection and instance segmentation that trains detectors without human-annotated labels, and the repo also includes VideoCutLER for unsupervised video instance segmentation. The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. The codebase provides training and inference scripts, model configs, and references to... -
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Anthropic SDK TypeScript
Access to Anthropic's safety-first language model APIs
anthropic-sdk-typescript is the TypeScript / JavaScript client library for the Anthropic REST API, enabling backend or Node.js usage of models like Claude. It wraps API endpoints for creating messages, streaming responses, and managing parameters in a type-safe TS environment. The library is designed for server-side use, interfacing with REST, and is stable for integration in web services or backend agents. Example usage shows how to instantiate the Anthropic client, call...
