ml-rag
CommunityBuild 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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