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Agentic AIintermediate

AniBaba: AI-Powered Anime Recommendation System

AniBaba is an AI-powered anime recommendation system that provides personalized suggestions based on natural language queries. Leveraging Retrieval-Augmented Generation (RAG), it understands user preferences and retrieves relevant anime from a semantic knowledge base to offer a conversational and discovery-rich experience.

22 lectures

What You Will Learn

Mastering the implementation of Retrieval-Augmented Generation (RAG) for anime recommendations.
Implementing LangChain for orchestrating LLM workflows in a recommendation system.
Building a semantic knowledge base using Vector Databases like ChromaDB.
Utilizing Hugging Face embeddings for effective anime similarity calculations.
Developing a user-friendly interface using Streamlit for conversational anime discovery.
Deploying the AniBaba application using Docker and Kubernetes on GCP.
Implementing monitoring solutions with Grafana Cloud for the deployed application.

System Architecture

AniBaba: AI-Powered Anime Recommendation System Architecture Diagram

High-level architecture overview of the AniBaba: AI-Powered Anime Recommendation System .

What You'll Build

  • An AI-powered anime recommendation system capable of understanding natural language queries.
  • A conversational interface that allows users to interact with an AI 'otaku' assistant.
  • A Dockerized application ready for deployment on Kubernetes.
  • A monitoring dashboard for tracking the performance and usage of the AniBaba system.
AniBaba: AI-Powered Anime Recommendation System
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