gemini-embed

What problem does it solve?

This Skill provides a fast, scalable way to convert text into numeric embeddings using Google Gemini's embedding model, enabling efficient similarity search, classification, and retrieval across large text collections.

Core Features & Use Cases

• Single and Batch Embeddings: Generate embeddings for individual strings or batches to optimize throughput.
• RAG & Semantic Search: Use embeddings to power retrieval-augmented generation and content search across documents.
• Classification & Clustering: Leverage vector representations for document classification and topic clustering.
• Use Case: For a large knowledge base, embed all documents once, store vectors, and run user queries against the vector store to fetch relevant documents.

Quick Start

Use the gemini-embed skill to generate embeddings for a sample text such as "Hello world" or for a batch of documents by calling the Gemini API with your API key.