How many data sources does LlamaIndex support?

Through LlamaHub, LlamaIndex supports over 300 data connectors, including PDF, GitHub, SQL, Slack, and various web scrapers.

Can I use LlamaIndex with different vector databases?

Yes, this skill provides implementation patterns for popular vector stores including Chroma, Pinecone, and FAISS.

Does this skill support multi-modal RAG?

Yes, it includes patterns for multi-modal indexing and querying, enabling Claude to process and reason across both text and images.

What is the primary use of the LlamaIndex skill?

The LlamaIndex skill is primarily used to build Retrieval-Augmented Generation (RAG) applications, allowing LLMs to access and query private or domain-specific data.

When should I use LlamaIndex over LangChain?

LlamaIndex is specialized for data-centric tasks and search-heavy RAG, whereas LangChain is a more general-purpose framework for complex agentic workflows.

LlamaIndex RAG Framework

Name: LlamaIndex RAG Framework
Author: davila7

bydavila7

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16,312

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データサイエンスとML

Simplifies the creation of data-centric LLM applications by providing patterns for RAG, document ingestion, and vector indexing.

This LlamaIndex skill equips Claude with the ability to architect sophisticated Retrieval-Augmented Generation (RAG) applications. It provides comprehensive implementation patterns for document ingestion from over 300 sources, efficient vector indexing, and advanced query engine configurations. Whether you are building internal knowledge bases, document Q&A systems, or multi-modal AI pipelines, this skill provides the necessary guidance and code structures to bridge the gap between private enterprise data and large language models.

主な機能

01Structured data extraction using Pydantic output parsing

02300+ pre-built data connectors for seamless document ingestion

03Autonomous RAG agents with advanced tool-calling capabilities

0416,312 GitHub stars

05Efficient vector store indexing and semantic search retrieval

06Advanced RAG patterns including multi-modal support and chat engines

ユースケース

01Creating automated knowledge retrieval agents for customer support

02Building private document Q&A systems over enterprise datasets

03Integrating diverse data sources like GitHub, PDFs, and SQL into LLM workflows

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add davila7/claude-code-templates ai-research

For use in Claude.ai and ChatGPT

Download Skill