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š¤ Learn how to build a complete RAG (Retrieval-Augmented Generation) Agent from scratch using n8n! This comprehensive tutorial covers everything from data ingestion to AI-powered responses. š WHAT YOU'LL LEARN: ā Complete RAG architecture explained ā Data ingestion and vector indexing ā Setting up Pinecone vector database ā Implementing embeddings with Cohere ā Creating AI agent with Groq LLM ā Building query and response pipeline in n8n ā End-to-end workflow automation š ESSENTIAL RESOURCES: š n8n Platform: https://n8n.io/ š Pinecone (Vector Database): https://www.pinecone.io/ š Cohere (Embeddings): https://cohere.com/ š Groq (LLM API): https://console.groq.com/keys š RAG TUTORIAL SERIES: Watch the complete playlist: https://youtube.com/playlist?list=PL_YSOkuDdgvOp8s_MwfcU1QtYjW0oyKB9&si=Ot5v8hmta7y-g3NP š» MY PROFILES: š¹ GitHub: https://github.com/MahendraMedapati27 - More projects and code š¹ LinkedIn: https://www.linkedin.com/in/mahendra-medapati-429239289 - Professional connections š¹ X (Twitter): https://x.com/MahendraM27 - AI discussions and updates š§ Email: mahendramedapati.r469@gmail.com - Direct contact šÆ WHO IS THIS FOR? - Developers learning RAG systems - n8n automation enthusiasts - AI/ML practitioners - Anyone building intelligent chatbots - Data engineers working with vector databases š” If this tutorial helped you, please like, share, and subscribe for more AI and automation content! #n8n #rag #aiagents #machinelearning #automation #vectordatabases #llm #artificialintelligence #tutorial #pinecones #Cohere #groq #workflowautomation #datascience #aitutorial #retrievalaugmentedgeneration #chatbot #nlp #deeplearning #techtutorial