Overview

RAG & Vector Database guides for Clore.ai GPU cloud

Retrieval-Augmented Generation and vector database solutions for building intelligent search and AI applications.

RAG systems combine large language models with external knowledge bases to provide accurate, up-to-date responses. Vector databases enable semantic search and similarity matching by storing high-dimensional embeddings of text, images, and other data.

Deploy vector databases and RAG frameworks on CLORE.AI GPUs to power intelligent search applications, chatbots with external knowledge, and advanced AI systems that can reason over large document collections across the Clore.ai marketplace.

Available Guides

Guide	Use Case	Difficulty
ChromaDB	Simple vector database	Easy
LlamaIndex	RAG framework & orchestration	Medium
Milvus	Enterprise vector database	Advanced
Qdrant	Fast vector search engine	Medium
RAGFlow	Complete RAG platform	Medium
Weaviate	AI-native vector database	Advanced

Database Comparison

Database	Best For	Scalability	GPU Acceleration
ChromaDB	Prototyping	Small-Medium	Limited
Milvus	Enterprise	High	Excellent
Qdrant	Performance	High	Good
Weaviate	AI-native features	High	Excellent

Related Guides

• Language Models

• Computer Vision