Rag Llm

Packt Publishing

Unlocking Data with Generative AI and RAG: Enhance generative AI systems by integrating internal data with large language models using RAG

Packt Publishing

RAG-Driven Generative AI: Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone

Packt Publishing

Building Neo4j-Powered Applications with LLMs: Create LLM-driven search and recommendations applications with Haystack, LangChain4j, and Spring AI

Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG (English Edition)

Independently published

Building Intelligent Systems with RAG 2.0: Develop Next-Gen LLM Applications with LangChain, OpenAI, Pinecone, FAISS, Vector Databases, and LLMOps Tools

Independently published

Ollama Crash Course: Build Local LLM powered Apps

Independently published

Building Scalable LLM Systems for Production: Deploy and Scale Transformer Models with LangChain, RAG, and Vector Databases

Independently published

Agentic AI Systems with LangChain + MCP + RAG + Ollama: Build Real-World Intelligent Agents with Modular Tools, Local LLMs, and Retrieval-Augmented Reasoning

Packt Publishing

Building Data-Driven Applications with LlamaIndex: A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Independently published

Graph RAG LLM: Hands-on Guide to graph-based approach to retrieval-augmented generation (RAG) For Developers