Retrieval-augmented-generation

This guide explains how to build an AI-powered application with LangChain by connecting large language models to external data sources using Python and Claude.

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.