rag-patterns
CommunityBuild robust RAG pipelines with Azure AI Search.
Authorpascalvanderheiden
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill enables building Retrieval-Augmented Generation (RAG) pipelines using Azure AI Search to ground LLM responses with knowledge bases and structured data.
Core Features & Use Cases
- Agentic Retrieval: multi-query planning and synthesis across knowledge sources for complex, multi-step questions.
- Full-Text + Vector Hybrid: combine BM25 keyword search with semantic vector similarities for robust answer grounding.
- Semantic Ranking: leverage integrated semantic configurations to improve result relevance and citation quality.
- Use Case: design an enterprise chatbot that can search product docs, manuals, and policy PDFs, then provide cited answers to user queries.
Quick Start
- Install dependencies and run the example scripts to explore RAG patterns.
- Create and configure indexes with vector and semantic capabilities: python scripts/create_index.py
- Run vector-based search examples: python scripts/vector_search.py
- Explore full-text search examples: python scripts/full_text_search.py
- Experiment with agentic retrieval: python scripts/agentic_retrieval.py
Dependency Matrix
Required Modules
azure-search-documentsazure-identityopenai
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: rag-patterns Download link: https://github.com/pascalvanderheiden/my-agent-skills/archive/main.zip#rag-patterns Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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