Creating an Autonomous AI App with AutoRAG and PhiData

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.

- Introduction to AutoRAG using PhiData
- Memory Storage with Postgres and PG Vector
- Utilising Tools like DuckDuckGo Search
- Adding Documents to the Knowledge Base
- Running Queries and Generating Responses
- Creating a User Interface with Streamlit
- Integrating Groq LLM and Llama Hermes 2 Pro