MemeMeow-Studio/MemeMeow

智能管理表情包

What it solves

It eliminates the need to remember specific filenames or tags when searching for memes. Instead of keyword matching, it allows users to find the perfect meme for a specific scene or emotion using natural language descriptions.

How it works

The system uses embedding models to enable Q&A-style retrieval, matching user queries to the most relevant images. To build and expand its library, it integrates Vision Language Models (VLMs) to automatically generate descriptive labels and filenames for uploaded images, removing the manual tagging effort.

Who it’s for

  • Users who want a fast, intuitive way to find memes via natural language.
  • Meme collectors who want to automatically label and organize their image libraries.
  • Developers looking to integrate meme retrieval into other apps via an API.

Highlights

  • AI-Powered Search: Uses embeddings for semantic retrieval rather than simple keyword search.
  • Automated Labeling: Leverages VLMs to automatically describe images and generate tags.
  • Flexible Deployment: Available as a web interface, API, iOS shortcuts, and an input method (MMIME).
  • Community-Driven: Supports importing and exporting "resource packs" (meme libraries) via community manifests and online URLs.

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