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wiki-embed-qdrant

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Make wiki chunks searchable with Qdrant.

Data & Analytics#gemini#wiki#qdrant#semantic-search#vector-embedding#rag-backend
Authorcdeistopened
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill enables you to index wiki content into a Qdrant Cloud vector store so your RAG backend can perform fast semantic search over wiki chunks.

Core Features & Use Cases

  • Embed semantic chunks using Gemini to generate 768-dim vectors.
  • Upsert embeddings into a Qdrant Cloud collection for production search and Q&A.
  • Automatically resume from the last processed chunk to handle interruptions in long-running jobs.

Quick Start

Run the embed_chunks.py script for your wiki to upsert all chunks into the Qdrant Cloud collection.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 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: wiki-embed-qdrant
Download link: https://github.com/cdeistopened/skill-stack-skills/archive/main.zip#wiki-embed-qdrant

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