Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 18
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Showing 1619 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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Next-generation security awareness training. Built for AI email phishing, vishing, smishing, and deepfakes.Assess how your company's digital footprint can be leveraged by cybercriminals. Identify the most at-risk individuals using thousands of public data points and take steps to proactively defend them.
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Smart IT MonitoringNetCrunch is a smart, agentless network monitoring and management software system capable of monitoring every device in a network. Developed by AdRem Software, NetCrunch helps businesses of all sizes remotely monitor network services, switches, routers, bandwidth utilization, and traffic flow and visualize their system performance.
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MedgeClaw
Open-source AI research assistant for biomedicine
...It includes a real-time dashboard that displays progress, generated code, and outputs, providing transparency throughout the research process. MedgeClaw also supports reproducibility by generating structured reports and maintaining consistent environments through containerization. Its architecture combines conversational AI, automated pipelines, and scientific tooling into a unified workflow. -
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AI-Crawler
Crawl a website starting from a URL, find relevant pages
...The tool supports output formats such as JSON and Markdown, and it can generate or accept schemas to ensure that extracted data is structured according to application needs. It is designed as a low-code solution, reducing the complexity of building and maintaining custom scraping pipelines. -
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DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
...DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and unstructured text, enabling flexible and comprehensive analysis workflows. It integrates execution-based reasoning by generating and running code as part of its analysis process, allowing it to iteratively refine results and produce more accurate outputs. DeepAnalyze provides multiple interaction interfaces, including a web-based UI, a command-line interface, and a Jupyter-style notebook environment for interactive workflows. -
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n-skills
Curated plugin marketplace for AI agents
...The repository includes a universal AGENTS.md discovery file and a shared SKILL.md format so that once a skill is published, it can be recognized and used by Claude Code, GitHub Copilot, Codex, Cursor, and other AI coding assistants with minimal friction. Installation of skills is supported through native installers or via universal installers like openskills, enabling seamless adoption in diverse development environments. -
Peer to Peer Recognition Brings Teams TogetherCreate a positive and energetic workplace environment with Motivosity, an innovative employee recognition and engagement platform. With Motivosity, employees can give each other small monetary bonuses for doing great things, promoting trust, collaboration, and appreciation in the workplace. The software solution comes with features such as an open-currency open-reward system, insights and analytics, dynamic organization chart, award programs, milestones, and more.
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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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Generative AI Docs
Documentation for Google's Gen AI site - including Gemini API & Gemma
...It contains guides, API references, and examples for developers building applications using Google’s large language models, text-to-image models, embeddings, and multimodal capabilities. The repository includes markdown source files that power the Google AI developer documentation site, as well as sample code snippets in Python, JavaScript, and other languages that demonstrate how to use Google’s Generative AI SDKs and REST APIs effectively. -
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MCPB
One-click local MCP server installation in desktop apps
...An .mcpb file is a zip archive containing your server and a manifest.json that declares capabilities, entry points, permissions, and configuration inputs, much like how .crx packages Chrome extensions or .vsix packages VS Code extensions. The goal is to make local tool servers easy for end users to install, update, and configure, while giving app developers a consistent way to discover and load them safely. The repository includes the bundle spec, a CLI to scaffold and pack bundles, and the loading/verification code used by Claude’s desktop apps, including support for auto-updates and a curated directory. ... -
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OpenAI Cookbook
Examples and guides for using the OpenAI API
openai-cookbook is a repository containing example code, tutorials, and guidance for how to build real applications on top of the OpenAI API. It covers a wide range of use cases: prompt engineering, embeddings and semantic search, fine-tuning, agent architectures, function calling, working with images, chat workflows, and more. The content is primarily in Python (notebooks, scripts), but the conceptual guidance is applicable across languages. -
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Fairlearn
A Python package to assess and improve fairness of ML models
Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system's fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. An AI system can behave unfairly for a variety of reasons. In Fairlearn, we define whether an AI system is behaving unfairly in terms of its impact on people – i.e., in terms of harm. Fairness of AI systems is about more than simply running lines of code. ... -
Deliver trusted data with dbtData teams use dbt to codify business logic and make it accessible to the entire organization—for use in reporting, ML modeling, and operational workflows.
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CTranslate2
Fast inference engine for Transformer models
CTranslate2 is a C++ and Python library for efficient inference with Transformer models. The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU. The execution is significantly faster and requires less resources than general-purpose deep learning frameworks on supported models and tasks thanks to many... -
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Marvin
A batteries-included library for building AI-powered software
...Marvin's job is to integrate AI directly into your codebase by making it look and feel like any other function. Marvin introduces a new concept called AI Functions. These functions differ from conventional ones in that they don’t rely on source code, but instead generate their outputs on-demand through AI. With AI functions, you don't have to write complex code for tasks like extracting entities from web pages, scoring sentiment, or categorizing items in your database. Just describe your needs, call the function, and you're done. AI functions work with native data types, so you can seamlessly integrate them into any codebase and chain them into sophisticated pipelines. ... -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major... -
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FLAML
A fast library for AutoML and tuning
...Users can find their desired customizability from a smooth range: minimal customization (computational resource budget), medium customization (e.g., scikit-style learner, search space, and metric), or full customization (arbitrary training and evaluation code). It supports fast automatic tuning, capable of handling complex constraints/guidance/early stopping. FLAML is powered by a new, cost-effective hyperparameter optimization and learner selection method invented by Microsoft Research. -
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. ... -
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Depth Anything 3
Recovering the Visual Space from Any Views
Depth Anything 3 is a research-driven project that brings accurate and dense depth estimation to any input image or video, enabling foundational understanding of 3D structure from 2D visual content. Designed to work across diverse scenes, lighting conditions, and image types, it uses advanced neural networks trained on large, heterogeneous datasets, producing depth maps that reveal scene depth relationships and object surfaces with strong fidelity. The model can be applied to photography,... -
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BrowserOS
Agentic browser; privacy-first alternative to ChatGPT Atlas
BrowserOS is an open-source, agentic web browser built on a Chromium base that integrates AI agents directly into the browsing experience. Rather than just doing standard browsing, it places AI intelligence at the core: you can connect your own API keys (for e.g., OpenAI, Anthropic, Google Gemini) or run local models (via e.g., Ollama) so that your browsing data and automation stay on your machine — privacy and control are emphasized throughout. The interface remains familiar to users of... -
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n8n-MCP
A MCP for Claude Desktop / Claude Code / Windsurf / Cursor
n8n-mcp is a Model Context Protocol (MCP) server that turns the n8n workflow platform into a set of first-class, typed tools an AI assistant can understand and operate. It exposes structured knowledge of n8n nodes and operations so an agent can reason about workflows, parameters, and executions without scraping docs or guessing API shapes. The server focuses on making Claude Desktop (and other MCP-capable clients) “n8n-literate,” enabling tasks such as inspecting existing workflows,... -
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MCP JetBrains
A model context protocol server to work with JetBrains IDEs
The JetBrains MCP Server is a Model Context Protocol (MCP) server designed to integrate seamlessly with JetBrains IDEs such as IntelliJ, PyCharm, WebStorm, and Android Studio. It facilitates enhanced communication between Large Language Models (LLMs) and the development environment, enabling AI-driven code assistance and automation. -
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freenom
Freenom domain name renews automatically
Freenom domain name automatic renewal. -
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Rawon
A simple powerful Discord music bot built to fulfill your production
A simple powerful Discord music bot built to fulfill your production desires. Easy to use, with no coding required. -
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Sandbox Agent
Run Coding Agents in Sandboxes
Sandbox Agent by Rivet is an experimental framework for running AI agents in controlled, isolated environments where they can safely execute code, interact with tools, and perform autonomous tasks without risking system integrity. It is designed to provide a secure sandbox that allows agents to test actions, manipulate files, and run commands while enforcing strict boundaries and monitoring capabilities. The project focuses on enabling more reliable and auditable agent behavior by separating execution from the host environment, which is especially important for applications involving automation, code generation, or system-level operations. ... -
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Qodo Cover
AI tool that generates tests to improve code coverage quickly
Qodo Cover is an open source developer tool designed to automate the creation of unit tests using generative AI, helping teams improve code coverage with minimal manual effort. It operates as a command-line interface and can also be integrated into continuous integration workflows, making it adaptable to different development environments. It analyzes an existing codebase, identifies gaps in test coverage, and generates new tests that target uncovered or weakly tested areas. -
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MLE-bench
AI multi-agent framework for automating data-driven R&D workflows
...RD-Agent can analyze data, generate experimental code, run evaluations, and learn from outcomes to improve future iterations. -
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draw-a-ui
Draw wireframe sketches and generate HTML with AI vision models
...The result is an automated design-to-code workflow where rough interface ideas can quickly become functional web layouts. It is implemented as a modern web application built with Next.js and TypeScript and requires a compatible Node.js runtime to run locally. It is designed primarily as a demonstration of AI-assisted UI generation rather than a production-ready platform. -
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Machine learning algorithms
Minimal and clean examples of machine learning algorithms
...The repository includes implementations of both supervised and unsupervised learning techniques, along with dimensionality reduction and clustering methods. Many of the algorithms are written in a simplified style that prioritizes clarity and educational value over production-level optimization. Because the code is compact and easy to follow, it is often used as a learning resource by developers who want to understand how machine learning algorithms are constructed.
