How to Build a Full-Stack RAG Powered Smart Web Searching AI Tool using Tavily, Langchain & Mistral

In this video, we craft a full-stack application from the ground up, utilizing the Tavily Search API for fast, accurate, and RAG-optimized AI-enhanced search results. We also briefly discuss the integration of the Retrieval-Augmented Generation (RAG) technique and harness the power of the #mistral model as our Large Language Model (LLM) #llm , which runs on the #Groq LPU for unmatched processing speed and efficiency. The AI stacks are seamlessly orchestrated using the langchain Python package. #langchain

Additionally, we will also develop a dynamic app featuring a Python #FastAPI backend and a #Reactjs frontend, all facilitated by the databutton online platform. The frontend is designed with the potential for further enhancements and expansion. This tutorial is presented as a demo app, with minimal video edits for clarity.

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[PaddyBrennan-mxhi]

Love this - thank you ! Groq is insane ! Can you query your own docs using this ?

[ritaverissimo]

Hi, does Data Button only work with Python in backend or can it be set to use Javascript for example? Thanks :)