Chat With Your PDFs Like a Pro: Build an AI Agent in скачать в хорошем качестве

Chat With Your PDFs Like a Pro: Build an AI Agent in

Welcome to video #7 in the 🧠 n8n AI Workflow Series – and things are starting to get spicy! 🌶️ Ever stared at an 870-page PDF bill and asked yourself, “Do I really need this kind of pain in my life?” 🥹 Worry no more – because we’re about to chat with that doc like it’s our new AI bestie! 📄💬 In this episode, I'm showing you how to build a real-world AI Agent powered by RAG (Retrieval-Augmented Generation). Long story short: it fetches relevant info from your PDFs and serves answers like a research-savvy genie. 🧞‍♂️ What’s in the menu today? 🍽️ ✅ Setting up Google Drive access in n8n ✅ Creating your own Vector DB using Pinecone (not the Christmas tree kind 🌲) ✅ Ingesting and chunking up documents like AI sushi chefs 🍣 ✅ Building a smart chat workflow that talks to your docs ✅ And of course, chatting live with a PDF stored in Google Drive 🚀 🔥 By the end, you'll be chatting with the law, news articles, books, research papers, or even your own shopping lists. And yes, AI won’t judge you for having “Buy more snacks” repeated 7 times 🍩🍕. 🧠 RAG is the real MVP here – and if you’re scratching your head thinking “Wait, wut is RAG?” No worries! I’ve explained RAG in plain English on Medium. Link in the description (because I like helpful and humblebragging) 😎 So dust off that old document archive and let’s make them talk! If you like AI, automation, and cool bots doing boring work, this one’s for you. Let’s RAG and roll! 🤘💻 Resources used in this video: https://app.pinecone.io https://console.cloud.google.com My Medium ARticles related to the topic:   / rag-in-the-ai-world-like-giving-your-ai-a-...     / pinecone-vector-database-for-no-coders-giv...     / understanding-vector-databases-used-by-ai-...     / understanding-vector-databases-a-beginner-...   👇 Copy this prompt to use as your Agent instructions: --------------------------------------------------------------------------------------------------- You are an AI assistant trained to answer only based on the contents of the document titled “Historical Evolution of Artificial Intelligence”, a JRC technical report by the European Commission. Only provide answers grounded in this document. If the question cannot be answered based on the document, respond with: “The information is not available in the provided document.” Use concise, informative language. If dates, key figures, or structured information are present in the document, prefer those. If summarizing, maintain factual accuracy and clearly distinguish between different historical AI periods, definitions, and paradigm shifts as detailed in the report. The document includes topics such as: Definitions and classifications of AI (ANI, AGI, ASI) Three paradigm shifts in AI history: Symbolic AI, Machine Learning, Deep Learning Key breakthroughs and failures (AI winters) Investments and predictions made by notable AI figures Ethical and regulatory concerns including adversarial attacks and deepfakes Future projections and comparisons across decades DO NOT hallucinate or invent information. Cite sections when relevant information. ------------------------------------------------------------------------------------------------------------- 💥 Don’t forget to LIKE 👍, SHARE 🔁, and SUBSCRIBE 🔔 or your documents might start spilling your secrets! 👀 #n8n #openai #rag #chatwithpdf #pinecone #documentai #workflowautomation #vectorstore #nocodeautomation #gpt4 #chatgpt #automationtools #techytools #aiworkflow #startuptech #openaiteam #embeddingmodels #pdfautomation #datalovers #dataisbeautiful #technerds #aiproject #ragagent #PinPixels #aiagents #n8nautomation