This is a pnpm monorepo containing the Next.js framework and related packages. The main Next.js framework lives in packages/next/. This is what gets published as the next npm package. Source code is in packages/next/src/. Key entry points: Compiled output goes to packages/next/dist/ (mirrors src/ structure). Before editing or creating files in any subdirectory (e.g., packages/, crates/), read all README.md files in the directory path from the repo root up to and including the target file's directory. This helps identify any…
Set permissions: {} at the workflow level and grant the minimum needed per-job. Prefer GitHub-provided (actions/*) and Vercel-owned actions. For third-party actions: ${{ ... }} is interpolated into the script before bash runs, so untrusted values (PR title, branch name, issue body) can break out and execute. Route them through an env var and quote on use:
This version has breaking changes — APIs, conventions, and file structure may all differ from your training data. Read the relevant guide in dist/docs/ before writing any code. Heed deprecation notices.
Turbopack is a general-purpose bundler that is built and designed for Next.js, but is not necessarily Next.js-specific. Keep Next.js concepts out of it.
GitHub Spec Kit is a comprehensive toolkit for implementing Spec-Driven Development (SDD) - a methodology that emphasizes creating clear specifications before implementation. The toolkit includes templates, scripts, and workflows that guide development teams through a structured approach to building software. Specify CLI is the command-line interface that bootstraps projects with the Spec Kit framework. It sets up the necessary directory structures, templates, and AI agent integrations to support the Spec-Driven Development workflow. The toolkit supports multiple AI coding assistants, allowing…
gstack is a collection of SKILL.md files that give AI agents structured roles for software development. Each skill is a specialist: CEO reviewer, eng manager, designer, QA lead, release engineer, debugger, and more. Skills live in .agents/skills/ (or ~/.claude/skills/gstack/ on Claude Code). Invoke them by name (e.g., /office-hours).
In the codex-rs folder where the rust code lives: - Crate names are prefixed with codex-. For example, the core folder's crate is named codex-core - When using format! and you can inline variables into {}, always do that. - Install any commands the repo relies on (for example just, rg, or cargo-insta) if they aren't already available before running instructions here. - Never add or modify any code related to CODEXSANDBOXNETWORKDISABLEDENVVAR or CODEXSANDBOXENVVAR. - You operate in a sandbox…
When changing the paste-burst or chat-composer state machines in this folder, keep the docs in sync: - Update the relevant module docs (chatcomposer.rs and/or pasteburst.rs) so they remain a readable, top-down explanation of the current behavior. - Keep implementations/docstrings aligned unless a divergence is intentional and documented. Practical check: - After edits, sanity-check that docs mention only APIs/behavior that exist in code (especially the Enter/newline paths and disablepasteburst semantics).
This project has a graphify knowledge graph at graphify-out/. Rules: - When working on Graphify itself, use the repository's existing Graphify guidance. For codebase questions, prefer scoped graph queries where available; use the report for broad orientation. Do not use the graph as evidence when the task concerns the graph's correctness itself. - If graphify-out/wiki/index.md exists, navigate it instead of reading raw files - After modifying code files in this session, run graphify update . to keep the graph current…
This repository contains a comprehensive 21-lesson curriculum teaching Generative AI fundamentals and application development. The course is designed for beginners and covers everything from basic concepts to building production-ready applications. Key Technologies: - Python 3.9+ with libraries: openai, python-dotenv, tiktoken, azure-ai-inference, pandas, numpy, matplotlib - TypeScript/JavaScript with Node.js and libraries: openai (Azure OpenAI via the v1 endpoint + Responses API), @azure-rest/ai-inference (Microsoft Foundry Models) - Azure OpenAI Service, OpenAI API, and Microsoft Foundry Models (GitHub Models is retiring end of…
يحتوي هذا الريبو على منهج شامل مكون من 21 درسًا يشمل تعليم أساسيات الذكاء الاصطناعي التوليدي وتطوير التطبيقات. الدورة مُصممة للمبتدئين وتغطي كل شيء من المفاهيم الأساسية إلى بناء تطبيقات جاهزة للإنتاج. التقنيات الرئيسية: - بايثون 3.9+ مع المكتبات: openai، python-dotenv، tiktoken، azure-ai-inference، pandas، numpy، matplotlib - تايبسكريبت/جافا سكريبت مع Node.js والمكتبات: openai (Azure OpenAI عبر نقطة النهاية v1 وResponses API)، @azure-rest/ai-inference (نماذج Microsoft Foundry) - خدمة Azure OpenAI، OpenAI API، ونماذج Microsoft Foundry (نماذج GitHub ستتوقف نهاية يوليو 2026)…
Това хранилище съдържа обширна учебна програма от 21 урока, която преподава основите на Генеративния AI и разработката на приложения. Курсът е предназначен за начинаещи и обхваща всичко от базови концепции до изграждане на приложения готови за продукция. Ключови технологии: - Python 3.9+ с библиотеки: openai, python-dotenv, tiktoken, azure-ai-inference, pandas, numpy, matplotlib - TypeScript/JavaScript с Node.js и библиотеки: openai (Azure OpenAI чрез v1 endpoint + Responses API), @azure-rest/ai-inference (Microsoft Foundry модели) - Azure OpenAI Service, OpenAI API и Microsoft Foundry модели…
এই রেপোজিটরিতে রয়েছে ২১টি পাঠের বিস্তৃত পাঠ্যক্রম যা জেনারেটিভ AI-এর মূল বিষয়বস্তু এবং অ্যাপ্লিকেশন উন্নয়ন শেখায়। কোর্সটি নতুনদের জন্য ডিজাইন করা হয়েছে এবং বেসিক ধারণা থেকে শুরু করে প্রোডাকশন-রেডি অ্যাপ্লিকেশন তৈরি পর্যন্ত সবকিছু আচ্ছাদিত করে। মূল প্রযুক্তি: - Python 3.9+ লাইব্রেরিসহ: openai, python-dotenv, tiktoken, azure-ai-inference, pandas, numpy, matplotlib - TypeScript/JavaScript Node.js এবং লাইব্রেরিসহ: openai (Azure OpenAI v1 endpoint + Responses API), @azure-rest/ai-inference (Microsoft Foundry Models) - Azure OpenAI সার্ভিস, OpenAI API, এবং Microsoft Foundry Models (GitHub Models ২০২৬ সালের জুলাই…
Toto úložiště obsahuje rozsáhlý 21-lekcí učební plán učící základy generativní AI a vývoje aplikací. Kurz je navržen pro začátečníky a pokrývá vše od základních konceptů až po vytváření aplikací připravených pro produkci. Klíčové technologie: - Python 3.9+ s knihovnami: openai, python-dotenv, tiktoken, azure-ai-inference, pandas, numpy, matplotlib - TypeScript/JavaScript s Node.js a knihovnami: openai (Azure OpenAI přes v1 endpoint + Responses API), @azure-rest/ai-inference (Microsoft Foundry Models) - Azure OpenAI Service, OpenAI API a Microsoft Foundry Models (GitHub Models je na konci…
VercelAGENTS.md
