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Skool RAG

Query Skool community content using RAG pipeline with vector search. Use when user asks to search Skool knowledge, find community answers, or query Skool content.

MHassan0000 Updated 1 repo stars
DevOps & Infra

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Skool RAG Pipeline

Goal

Query Skool community content using a RAG (Retrieval-Augmented Generation) pipeline with vector search and reranking.

Scripts

  • ./scripts/skool_rag_prepare.py - Prepare content for indexing
  • ./scripts/skool_rag_index.py - Index content in Pinecone
  • ./scripts/skool_rag_query.py - Query the knowledge base

Pipeline

1. Prepare Content

python3 ./scripts/skool_rag_prepare.py --community makerschool

Scrapes and chunks community content.

2. Index in Pinecone

python3 ./scripts/skool_rag_index.py --input .tmp/skool_chunks.json

Creates OpenAI embeddings and stores in Pinecone.

3. Query

python3 ./scripts/skool_rag_query.py --query "How do I get my first client?"

Pipeline:

  1. OpenAI embeddings for query
  2. Pinecone vector search
  3. Cohere reranking
  4. Claude response generation

Environment

PINECONE_API_KEY=your_key
OPENAI_API_KEY=your_key
COHERE_API_KEY=your_key
ANTHROPIC_API_KEY=your_key

MHassan0000/Skills/tree/main/Claude/maker zero claude skills premium/CLAUDE CODE WORKFLOWS AND SKILLS/Skills/skool-rag commit 727c5b5aba

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Frequently asked questions

npx skillmds@latest add mhassan0000/skool-rag