Retrieval-augmented-generation

This guide explains how the LangChain framework simplifies the process of building AI applications by chaining LLMs, external data sources, and conversation memory.

Retrieval-Augmented Generation connects AI models to private data to reduce hallucinations. This guide explains how RAG provides accurate and up-to-date answers.

LlamaIndex serves as a specialized data framework for connecting private information to AI models. This guide explains how to build RAG applications efficiently.

This guide explains how Pinecone functions as a cloud-native vector database, the role of embeddings in AI memory, and how to set up an index for data retrieval.