Search Results for "command prompt tutorial"
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Showing 8 open source projects for "command prompt tutorial"
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Code2Prompt
Convert codebases into structured prompts optimized for LLM analysis
code2prompt is an open source command line tool designed to convert an entire codebase into a structured prompt that can be easily used with large language models. It analyzes a project directory, gathers relevant source files, and formats them into a single prompt that includes the source tree and code content. This approach helps developers quickly provide full project context to AI models without manually copying files or assembling prompts. code2prompt is built in Rust and focuses on performance, enabling fast traversal of large repositories while maintaining low resource usage. ... -
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Gitingest
Create prompt-friendly codebase digests from any Git repository URL
...Developers can generate these digests from either a local directory or a remote repository by supplying a repository path or URL. The generated output is optimized for prompt usage, helping AI models understand codebases more effectively without requiring manual file aggregation. In addition to producing the code digest, Gitingest also calculates statistics about the extracted content such as repository structure, total size of the extract, and token count. Gitingest can be used as a command line utility or integrated directly into Python applications. -
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Fish Skin AI Knowledge Base
Programmer Fish Skin's AI Resource Guide
Fish Skin AI Knowledge Base is a comprehensive open knowledge base and tutorial collection that helps developers quickly learn, evaluate, and apply modern AI technologies, especially in the context of “vibe coding” and practical AI product development. The project curates structured learning paths covering model selection, AI coding tools, agent platforms, prompt engineering, and full-stack AI application workflows. -
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Easy-Vibe
Tutorial on Product Prototype, AI Capability Integration
Easy-Vibe is an open-source educational project designed to teach developers, product managers, and beginners how to build AI-powered applications using the emerging concept of “vibe coding,” a development approach that relies heavily on AI-assisted programming tools. The project provides a structured curriculum that guides learners from having no programming experience to building fully functional AI-integrated applications. Instead of focusing only on theoretical concepts, Easy-Vibe... -
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5
Easy Diffusion
An easy 1-click way to create beautiful artwork on your PC using AI
Easy Diffusion is a widely used community-driven repository offering a simple, one-click way to install and use Stable Diffusion-based generative AI on a personal computer without advanced technical skills or prior setup. It provides a browser-based user interface that runs locally, allowing users to type text prompts and immediately generate images directly within their web browser, democratizing access to powerful text-to-image models for artists and hobbyists alike. The project abstracts... -
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ai-renamer
A Node.js CLI that uses Ollama and LM Studio models
ai-renamer is a Node.js-based command-line tool that uses large language models to automatically rename files based on their content, enabling more meaningful and organized file management. Instead of relying on manual naming or metadata, the tool analyzes the actual content of files, including images, videos, and documents, to generate descriptive and context-aware filenames. -
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Loop Engineering
Practical patterns, starters & CLI tools for loop engineering with AI
Loop Engineering is a practical reference repository for designing loop-based workflows with AI coding agents. It focuses on replacing repeated manual prompting with systems that prompt, verify, schedule, and hand off work over time. The project is aimed at developers using tools such as Grok, Claude Code, Codex, Cursor, and other coding agents. It explains core building blocks such as scheduling, worktrees, skills, plugins, connectors, sub-agents, and persistent memory or state. The... -
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Qodo Cover
AI tool that generates tests to improve code coverage quickly
...Internally, Qodo Cover uses a modular architecture that includes components for prompt generation, AI interaction, coverage analysis, and test validation. It supports scanning entire repositories to automatically detect test files, gather relevant context, and extend test suites accordingly.
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