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Agentic AIintermediate

Ai-Powered Anime Recommendation System

AI-powered anime recommendation system that provides personalized suggestions based on natural language queries. By leveraging Retrieval-Augmented Generation (RAG) and LLM as JUDGE evaluation, it understands user preferences and retrieves relevant anime from a semantic knowledge base to offer a conversational and discovery-rich experience everything traced on Langsmith , deployed via kubernetes on GCP cloud.

25 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

Ai-Powered Anime Recommendation System Architecture Diagram

High-level architecture overview of the 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.

Project Instructor

Divesh Jadhwani

Divesh Jadhwani

3+ years exp
LinkedIn
Ai-Powered Anime Recommendation System
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