$ show f/prompts.chat
This repository is a full-stack Next.js application that serves as the world's largest open-source prompt library for AI. It provides a platform for users to create, share, discover, and manage prompts for various AI models (ChatGPT, Claude, Gemini, etc.). The core functionality includes CRUD operations for prompts with types (text, image, video, audio, skill, taste), voting, commenting, versioning, change requests, collections, and moderation tools. It features AI-powered capabilities such as semantic search via OpenAI embeddings, prompt improvement, translation, quality checking, and media generation through plugin-based providers (Fal.ai, Wiro.ai). The application supports multi-tenancy for self-hosting with configurable branding, authentication plugins (OAuth, OIDC, GitHub, Apple, Google), and storage backends (S3, DO Spaces). Beyond the web app, it includes a CLI tool (packages/prompts.chat) for browsing and running prompts locally, a Raycast extension for quick access, and an MCP server for integration with AI coding assistants. Additionally, it bundles an interactive educational book on prompt engineering (28+ chapters) and a gamified kids learning section, both fully localized into 17 languages. The codebase is well-structured with a plugin registry pattern, configuration-driven design, and extensive use of modern Next.js patterns (App Router, server components, streaming).
The LLM identified 5 files worth highlighting for reuse:
Implements a generic plugin registry for auth, storage, media generators, and widgets. Plugins are registered with a name, config, and handler, enabling hot-swappable backends without modifying core code. This pattern is reusable for any application requiring pluggable components, such as multi-provider authentication or storage backends.
Provides a standalone text similarity function using weighted Jaccard with n-grams (character trigrams). Includes normalization for punctuation, markdown, variables, and code blocks. The function is pure and has no external dependencies, making it easily extractable for any project requiring duplicate detection or content similarity matching.
A custom parser for prompt files in YAML, JSON, Markdown, and plain text formats. It extracts structured metadata (title, description, variables, model parameters) and content. Although the documentation suggests replacing it with js-yaml for robustness, the pattern of a unified parser for multi-format configuration files is reusable for any domain-specific file format.
A fluent TypeScript builder pattern for constructing prompts for text, image, video, and audio. Provides chainable methods (e.g., `.addMessage()`, `.setModel()`, `.addMedia()`) and generates multiple output formats (JSON, YAML, Markdown). The builder is isolated in a separate npm package and demonstrates a clean DSL pattern that could be adapted for any structured content generation.
Detects variable placeholders in strings using seven common patterns (e.g., `{{var}}`, `[VAR]`, `${var}`) with a curated list of false positives (HTML tags, programming keywords). This utility is pure and zero-dependency, reusable for any system that needs to identify templated variables in user input.