Search Results for "engineering" - Page 8
Sort By:
Showing 1331 open source projects for "engineering"
View related business solutions-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
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. The system includes tooling that routes natural language inputs to existing skills, augments them, or generates new ones using autonomous phases, enforcing quality, extensibility, security, and timelessness. ... -
2
Agentic Coding Flywheel Setup
System tool for beginners wanting agentic engineering capabilities
Agentic Coding Flywheel Setup (ACFS) is a comprehensive environment bootstrap project that configures a full stack of tools for autonomous AI-assisted coding workflows. With a single shell installer, ACFS transforms a fresh compute environment into a ready-to-use development setup that includes modern shells, language runtimes, AI coding agents (like Claude Code, Codex CLI, and Gemini CLI), and a coordinated toolchain for orchestration and safety. The system is designed for developers who... -
3
UltraRAG
Less Code, Lower Barrier, Faster Deployment
...It encourages pipeline composition via configuration, enabling researchers to swap retrievers, rerankers, and generators without heavy refactoring. Community posts highlight its focus on reducing engineering overhead so more effort goes to experimental design. Backed by the OpenBMB org, it is actively maintained with tutorials and updates. -
4
PandasAI
PandasAI is a Python library that integrates generative AI
PandasAI is a Python library that adds Generative AI capabilities to pandas, the popular data analysis and manipulation tool. It is designed to be used in conjunction with pandas, and is not a replacement for it. PandasAI makes pandas (and all the most used data analyst libraries) conversational, allowing you to ask questions to your data in natural language. For example, you can ask PandasAI to find all the rows in a DataFrame where the value of a column is greater than 5, and it will... -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
-
5
OpenSage
An agent framework that enables AI to create their own agent
OpenSage is an emerging open-source AI agent development framework designed to automate the creation, orchestration, and evolution of intelligent agents through a self-programming paradigm. Unlike traditional agent frameworks that require developers to manually define workflows, tools, and structures, OpenSage introduces a system where large language models can dynamically generate their own agent architectures, including sub-agents, toolchains, and execution strategies. The framework is... -
6
ADK Go
Code-first Go toolkit for building, evaluating, and deploying AI agent
...It is part of the Agent Development Kit ecosystem and follows a code-first approach that allows developers to define agent behavior, tools, and orchestration logic directly in Go code. ADK-Go applies traditional software engineering principles to agent development, making it easier to structure, test, and maintain complex agent-based systems. It supports building both simple task-oriented agents and more advanced multi-agent architectures that collaborate to perform workflows. It is designed to be modular and flexible, allowing developers to integrate custom tools, external services, or existing functionality into agent workflows. ... -
7
C3
The goal of CLAIMED is to enable low-code/no-code rapid prototyping
...The system emphasizes reproducibility and scalability, allowing researchers and engineers to reuse existing components and integrate them into larger scientific or data engineering workflows. It also aims to support trusted and explainable AI systems by integrating tools for fairness analysis, explainability, and adversarial robustness. -
8
AutoTrain Advanced
Faster and easier training and deployments
...The project provides a no-code and low-code interface that allows users to train models using custom datasets without needing extensive expertise in machine learning engineering. It supports a wide range of tasks including text classification, sequence-to-sequence modeling, token classification, sentence embedding training, and large language model fine-tuning. The system integrates closely with the Hugging Face ecosystem and allows developers to train models using datasets hosted on the Hugging Face Hub. ... -
9
Machine Learning for Software Engineers
A complete daily plan for studying to become a machine learning engine
...It aggregates a wide range of resources including books, online courses, Kaggle competitions, podcasts, conferences, and community learning opportunities. The repository is structured to help learners gradually build the skills required for machine learning engineering positions while maintaining a focus on real-world application development. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
10
Prompt Poet
Streamlines and simplifies prompt design for both developers
Prompt Poet is an open-source framework designed to simplify the creation, organization, and maintenance of prompts for large language model applications. The project focuses on transforming prompt engineering into a structured design process rather than ad-hoc string manipulation within application code. It allows developers and non-technical users to build prompts using templated configurations based on YAML and Jinja2, which makes prompts easier to compose, reuse, and modify across different environments. By separating prompt structure from program logic, Prompt Poet encourages iterative prompt design and experimentation without requiring constant changes to application code. ... -
11
csghub-server
csghub-server is the backend server for CSGHub
...The server acts as a centralized management layer that allows teams to store, organize, and operate AI assets such as models, datasets, and machine learning applications in a manner similar to artifact repositories used in software engineering. Built primarily in the Go programming language, the system enables organizations to run model inference, training, and fine-tuning tasks within a unified platform. It integrates capabilities similar to model repositories like Hugging Face while allowing enterprises to host and manage their AI assets internally for security and compliance purposes. -
12
Fulling
Full-stack Engineer Agent. Built with Next.js, Claude, shadcn/ui
Fulling is an open-source AI-powered development environment designed to function as an autonomous full-stack engineering assistant. The platform provides a sandboxed workspace where developers can build complete applications with the help of an integrated AI coding agent. Instead of manually configuring development environments, the system automatically provisions the required infrastructure including a Linux environment, database services, and development tools. -
13
Daily Interview
Datawhale members have compiled a book covering machine learning
daily-interview is an open-source educational repository designed to help software engineers prepare for technical interviews through daily practice questions and curated learning materials. The project collects a wide range of interview questions related to algorithms, data structures, system design, and core computer science topics commonly tested by technology companies. The repository is organized in a structured format that encourages developers to practice solving problems regularly... -
14
PyTorch-Tutorial-2nd
CV, NLP, LLM project applications, and advanced engineering deployment
PyTorch-Tutorial-2nd is an open-source educational repository that provides structured tutorials for learning deep learning with the PyTorch framework. The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization... -
15
LearnLLM.AI
Sharing knowledge about big models that everyone can understand
LLMForEverybody is an open-source educational repository designed to make large language model concepts accessible to a broad audience, including beginners, developers, and job candidates preparing for AI-related interviews. The project organizes knowledge about LLMs into a structured learning path that begins with foundational research papers and progresses through the evolution of modern model architectures. It covers a wide range of topics including attention mechanisms, tokenization... -
16
Web Quality Skills
Agent Skills for optimizing web quality based on Lighthouse
This repository is a curated set of AI agent skills that encapsulate best practices for improving web quality, performance, accessibility, search engine optimization, and general best practices for web projects. It encodes knowledge drawn from Google Lighthouse audits, Core Web Vitals heuristics, WCAG accessibility guidelines, and real-world engineering experience, allowing coding agents to automatically assess and suggest improvements. These skills are framework-agnostic, meaning they apply to React, Vue, Svelte, Angular, Astro, or even plain HTML projects. For example, an agent can use these skills to audit a page’s performance, identify bottlenecks in loading speed, fix layout shift issues, suggest accessibility enhancements, or recommend SEO improvements. ... -
17
VibeTensor
Our first fully AI generated deep learning system
VibeTensor is a groundbreaking open-source research system software stack for deep learning that was uniquely generated almost entirely by AI coding agents under guided human supervision, demonstrating a new frontier in AI-assisted software engineering. It implements a PyTorch-style eager tensor library with a modern C++20 core that supports both CPU and CUDA backends, giving it the ability to manage tensors, automatic differentiation (autograd), and complex computation flows similar to mainstream frameworks. What makes VibeTensor remarkable is that every major component, from core libraries and dispatch systems to CUDA runtime support, caching allocators, and language bindings, was created and validated by coding agents using automated builds and tests rather than manual line-by-line human coding. ... -
18
Dev Janitor
Your Vibe Coding Toolkit A cross-platform desktop application
Dev Janitor is an open-source developer productivity tool designed to automatically clean up stale, unused, or poorly maintained code patterns in a codebase, helping teams keep their repositories tidy without consuming engineering time manually pruning technical debt. The tool analyzes project files and identifies opportunities to perform cleanup tasks such as removing dead imports, fixing outdated syntax, simplifying redundant expressions, and consolidating duplicated logic, all while observing established conventions for the languages it supports. Through a pluggable rule system, it allows teams to enforce their own style guides or cleanup policies, enabling tailored automation that fits each codebase’s unique needs. ... -
19
AI Agents Masterclass
Follow along with my AI Agents Masterclass videos
AI Agents Masterclass is an educational open-source repository designed to teach developers how to build, train, and deploy intelligent AI agents using modern tooling and workflow patterns. The project includes structured lessons, code examples, and practical exercises that cover foundational concepts like prompt engineering, chaining agents, tool usage, plan execution, evaluation, and safety considerations. It breaks down how autonomous agents interact with external systems, handle iterative reasoning, and integrate with third-party services or APIs to perform real tasks — for example, web search, browsing, scheduling, or coding assistance. Students of the masterclass can follow written modules or Jupyter notebooks that illustrate concepts step by step and progressively build more capable agents. ... -
20
Serena
Agent toolkit providing semantic retrieval and editing capabilities
Serena is a coding-focused agent toolkit that turns an LLM into a practical software-engineering agent with semantic retrieval and editing over real repositories. It operates as an MCP server (and other integrations), exposing IDE-like tools so agents can locate symbols, reason about code structure, make targeted edits, and validate changes. The toolkit is LLM-agnostic and framework-agnostic, positioning itself as a drop-in capability for different chat UIs, orchestrators, or custom agent stacks. ... -
21
TraceRoot
Find the Root Cause in Your Code's Trace
TraceRoot.AI is an open source, AI-native observability and debugging platform designed to help engineering teams resolve production issues faster. It consolidates telemetry into a single correlated execution tree that provides causal context for failures. AI agents operate over this structured view to summarize issues, pinpoint likely root causes, and even suggest actionable fixes or draft GitHub issues and pull requests. It offers interactive trace exploration with zoomable log clusters, span and latency views, and code-linked insights. ... -
22
Easy-Vibe
Tutorial on Product Prototype, AI Capability Integration
...The learning path is divided into progressive stages that cover beginner concepts, full-stack development, and advanced multi-platform application development. Throughout the curriculum, learners explore topics such as prompt engineering, AI tool integration, product prototyping, and deployment strategies for AI-enabled applications. -
23
IQuest-Coder-V1 Model Family
New family of code large language models (LLMs)
IQuest-Coder-V1 is a cutting-edge family of open-source large language models specifically engineered for code generation, deep code understanding, and autonomous software engineering tasks. These models range from tens of billions to smaller footprints and are trained on a novel code-flow multi-stage paradigm that captures how real software evolves over time — not just static code snapshots — giving them a deeper semantic understanding of programming logic. They support native long contexts up to 128K tokens, enabling them to reason across large codebases and multi-file interactions without context fragmentation, and include “Thinking” variants optimized for complex reasoning and “Loop” variants with recurrent mechanisms to improve inference efficiency. ... -
24
Acontext
Context data platform for building observable, self-learning AI agents
Acontext is a cloud-native context data platform designed to support the development and operation of advanced AI agents. It provides a unified system to store and manage contexts, multimodal messages, artifacts, and task workflows, enabling developers to engineer context effectively for their agent products. The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. Acontext also... -
25
Koog
Koog is the official Kotlin framework for building AI agents
...It features pure Kotlin implementation, seamless Model Control Protocol (MCP) integration for enhanced model management, vector embeddings for semantic search, and a flexible system for creating and extending tools that access external systems and APIs. Ready‑to‑use components address common AI engineering challenges, while intelligent history compression optimizes token usage and preserves context. A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring.
