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Advanced RAG 101 - build agentic RAG with llama3 Get free HubSpot report of how AI is redefining startup GTM strategy: https://clickhubspot.com/4hx 🔗 Links - Follow me on twitter: https://twitter.com/jasonzhou1993 - Join my AI email list: https://www.ai-jason.com/ - My discord: https://discord.gg/eZXprSaCDE - Corrective RAG agent: https://github.com/langchain-ai/langgraph/blob/main/examples/rag/langgraph_crag_local.ipynbhttps://microsoft.github.io/autogen/blog/2023/10/26/TeachableAgent/ - LlamaParse: https://github.com/run-llama/llama_parse - Firecrawl: https://www.firecrawl.dev/ - Jerry Liu build production-ready RAG: https://www.youtube.com/watch?v=TRjq7t2Ms5I ⏱️ Timestamps 0:00 Intro 1:33 How to give LLM knowledge 3:05 Problem with simple RAG 5:55 Better Parser 9:01 Chunk size 11:40 Rerank 12:39 Hybrid search 13:10 Agentic RAG - Query translation 14:35 Agentic RAG - metadata filtering 15:52 Agentic RAG - Corrective RAG agent 17:33 Install LLama3 18:00 Code walkthrough 👋🏻 About Me My name is Jason Zhou, a product designer who shares interesting AI experiments & products. Email me if you need help building AI apps! ask@ai-jason.com #llama3 #rag #llamaparse #llamaindex #gpt5 #autogen #gpt4 #autogpt #ai #artificialintelligence #tutorial #stepbystep #openai #llm #chatgpt #largelanguagemodels #largelanguagemodel #bestaiagent #chatgpt #agentgpt #agent #babyagi