Advanced RAG with Llama 3 in Langchain | Chat with PDF using Free Embeddings, Reranker & LlamaParse Published 2024-05-12 Download video MP4 360p Recommendations 21:33 Python RAG Tutorial (with Local LLMs): AI For Your PDFs 00:50 What is LangChain? 14:58 This Llama 3 is powerful and uncensored, let’s run it 15:40 GraphRAG: LLM-Derived Knowledge Graphs for RAG 24:07 Transformers, explained: Understand the model behind ChatGPT 15:47 Getting Started with LangChain and Llama 2 in 15 Minutes | Beginner's Guide to LangChain 16:48 Meta x Ray-Ban AI Glasses Are Fantastic...But Not Why You Think 53:15 Building a RAG application using open-source models (Asking questions from a PDF using Llama2) 24:02 "I want Llama3 to perform 10x with my private knowledge" - Local Agentic RAG w/ llama3 17:32 Talk to Your Documents, Powered by Llama-Index 47:43 Agency Swarm: Why It’s Better Than CrewAI & AutoGen 23:00 How to chat with your PDFs using local Large Language Models [Ollama RAG] 15:21 Unlimited AI Agents running locally with Ollama & AnythingLLM 24:20 "okay, but I want Llama 3 for my specific use case" - Here's how 14:02 Chunking Strategies in RAG: Optimising Data for Advanced AI Responses 11:37 What is RAG? (Retrieval Augmented Generation) 1:07:30 Chat with Multiple PDFs | LangChain App Tutorial in Python (Free LLMs and Embeddings) 10:00 Open Source RAG running LLMs locally with Ollama 20:22 How to scrape the web for LLM in 2024: Jina AI (Reader API), Mendable (firecrawl) and Scrapegraph-ai 19:21 How I Made AI Assistants Do My Work For Me: CrewAI Similar videos 59:37 High-performance RAG with LlamaIndex 27:15 RAG with LlamaParse, Qdrant and Groq | Step By Step 08:48 Discover LlamaIndex: Ask Complex Queries over Multiple Documents 22:40 Jerry Liu–LlamaIndex – Practical Data Considerations for building Production-Ready LLM Applications More results