How do I handle large documents effectively?

This skill includes several chunking strategies, such as recursive character splitting, token-based splitting, and semantic chunking to optimize context window usage.

What is RAG and why is it used?

Retrieval-Augmented Generation (RAG) grounds LLM responses in external, factual data to reduce hallucinations and provide accurate information from proprietary or domain-specific sources.

Does this include advanced retrieval techniques?

Yes, it covers hybrid search (combining dense and sparse retrieval), multi-query retrieval, contextual compression, and reranking with Cross-Encoders.

Which vector databases are supported by this skill?

The skill provides implementation patterns for major providers including Pinecone, Weaviate, Chroma, Qdrant, Milvus, and FAISS.

RAG System Implementation

Name: RAG System Implementation
Author: carlopezzuto

bycarlopezzuto

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데이터 과학 및 ML

Builds robust Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search to ground LLM responses in proprietary data.

This skill provides a comprehensive framework for developing high-quality RAG applications, enabling LLMs to access and reason over external knowledge bases. It covers the entire pipeline from document loading and sophisticated chunking strategies to advanced retrieval patterns like hybrid search and reranking. By implementing these patterns, developers can significantly reduce hallucinations and build accurate, source-cited Q&A systems, research tools, and documentation assistants that leverage domain-specific information.

주요 기능

01Integration with major vector databases including Pinecone, Chroma, and Weaviate

02Standardized evaluation metrics for measuring groundedness and retrieval quality

03Advanced document chunking and semantic splitting strategies

04Hybrid and multi-query retrieval patterns for improved search accuracy

05Contextual compression and reranking using Cross-Encoders

060 GitHub stars

사용 사례

01Building a Q&A chatbot over internal company documentation

02Creating a semantic search engine for large, unstructured datasets

03Developing a research assistant that cites specific sources for every claim

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add carlopezzuto/agents rag-implementation

For use in Claude.ai and ChatGPT

Download Skill