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gemini-embeddings

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Generate text embeddings & similarity

Data & Analytics#semantic search#embeddings#RAG#vector search#gemini#text similarity
Authorakrindev
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill automates the creation of numerical representations (embeddings) for text, enabling AI to understand and compare the semantic meaning of words and documents.

Core Features & Use Cases

  • Generate Embeddings: Create vector representations for any text input.
  • Calculate Similarity: Measure how semantically similar two or more pieces of text are.
  • Support for RAG: Prepare text data for Retrieval Augmented Generation systems.
  • Dimensionality Control: Adjust embedding vector size for performance or accuracy.
  • Use Case: You have a large collection of customer feedback. Use this Skill to generate embeddings for each piece of feedback, then find all feedback entries that are semantically similar to a new customer query, helping you quickly identify recurring issues.

Quick Start

Generate embeddings for the text "What is the meaning of life?".

Dependency Matrix

Required Modules

google-genainumpy

Components

scriptsreferences

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: gemini-embeddings
Download link: https://github.com/akrindev/google-studio-skills/archive/main.zip#gemini-embeddings

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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