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Learn to build an intelligent AutoRAG system from scratch using PhiData in this comprehensive tutorial video. Discover how to enhance AI's decision-making capabilities for using memory, searching vector databases, or utilizing web search tools for relevant responses. Explore the basics of AutoRAG, set up an assistant with a large language model, add documents to a knowledge base, query the AI effectively, and create a user interface. Gain insights into memory storage with Postgres and PG Vector, utilize tools like DuckDuckGo Search, and integrate Groq LLM and Llama Hermes 2 Pro. Follow along with step-by-step instructions to develop a functional autonomous AI application, complete with a Streamlit-based user interface for improved interaction.
