ml-rag

Community

Build and query a RAG pipeline from documents

Authormilasaurus
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps you create a searchable knowledge base and answer questions about a document collection without needing ML expertise.

Core Features & Use Cases

  • Build a Searchable Index: Index a collection of documents into a searchable vector store.
  • Query and Answer: Ask questions and get answers with source citations from the index.
  • Use Case: Build a RAG pipeline from a directory of documents to answer questions about the content.

Quick Start

Use the ml-rag skill to build a RAG pipeline from the directory 'documents'.

Dependency Matrix

Required Modules

sentence-transformerschromadb

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: ml-rag
Download link: https://github.com/milasaurus/compound-ml/archive/main.zip#ml-rag

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