Build a Full-Stack GenAI Conversation Analytics App with LLM, React ,MongoDB & Docker скачать в хорошем качестве

Build a Full-Stack GenAI Conversation Analytics App with LLM, React ,MongoDB & Docker

In this tutorial, we create a fullstack GenAI Conversation Analytics app. We will be using React for the front end, MongoDB for our database, and Docker for seamless deployment including Authentication and Authorisation using Json Web Token (JWT). Plus, we will leverage the free Gemini-Pro for enhanced functionality. Perfect for developers looking to expand their skills in full-stack development using GenAI. You can use this project repository as a sample and extend it to meet your needs. I will update the codebase to include separate analytics for each user and address other important topics. Example: Customer Feedback: I reached out for help with my account, and the support team was very responsive and helpful. I appreciate their quick assistance, but it would be helpful to have more self-service options available. Conversational Analytics: Key Topics: Account support Overall Sentiments: Mixed (Positive | Negative) Emerging Trends: Limited self-service options Stay tuned and don’t forget to like, subscribe, and hit the bell for more GenAI related coding & concept tutorials :) GitHub Link - https://github.com/genieincodebottle/... FastAPI - https://fastapi.tiangolo.com/ React - https://react.dev/ JWT - https://jwt.io/ How to setup Google's free Gemini Pro API Key -   • Video   Gemini API Key - https://console.cloud.google.com/apis... Docker Install - https://docs.docker.com/engine/install/ Postman Install - https://www.postman.com/downloads/ Instagram -   / genieincodebottle   00:00:00 Introduction 00:04:22 Backend 00:15:52 Frontend 00:19:41 Docker, Secret Key setuo, env, Running app 00:24:30 Understand Custom JWT Authentication & Authorization process Subscribe    / @genieincodebottle   #generativeai #langchain #geminipro #datascience #machinelearning #largelanguagemodels #vscode #artificialintelligence #reactjs #mongodb #docker