Easily Create Autonomous AI App from Scratch

Hey everyone! 🌟 In this video, we're diving deep into the world of AutoRAG using PhiData. You'll learn how to build an intelligent AutoRAG system from scratch, enhancing your AI's ability to decide whether to use memory, search a vector database, or utilise web search tools for the most relevant responses. 💡🤖 Easily Create Autonomous AI App from Scratch What You'll Learn: Introduction to AutoRAG: Understand the basics and how it works. 📘 Setting Up the Assistant: Step-by-step guide to configure the large language model and its components. 🛠️ Adding Documents to Knowledge Base: Learn how to upload files and URLs efficiently. 🗂️ Querying the Assistant: Techniques to ask questions and get precise answers from your AI. 💬 Creating a User Interface: Build a functional interface for better interaction. 🖥️ 🔗 Resources: Sponsor a Video: https://mer.vin/contact/ Do a Demo of Your Product: https://mer.vin/contact/ Patreon: https://patreon.com/MervinPraison Ko-fi: https://ko-fi.com/mervinpraison Discord: https://discord.gg/nNZu5gGT59 Twitter / X : https://twitter.com/mervinpraison Code: https://mer.vin/2024/05/phidata-auto-rag/ https://git.new/auto-rag https://git.new/groq-autorag https://git.new/ollama-autorag Key Highlights: 0:00 - Introduction to AutoRAG using PhiData 1:03 - Memory Storage with Postgres and PG Vector 2:01 - Utilising Tools like DuckDuckGo Search 4:00 - Adding Documents to the Knowledge Base 7:00 - Running Queries and Generating Responses 9:03 - Creating a User Interface with Streamlit 11:30 - Integrating Groq LLM and Llama Hermes 2 Pro Stay tuned for more in-depth tutorials on AI and machine learning! Don't forget to like, share, and subscribe. 👍🔔 #autorag #phidata #groq #ollama #gpt4o