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Agentic AIintermediate

Flipkart Product Recommender Chatbot with GCP

Develop a Flipkart Product Recommender Chatbot using Retrieval-Augmented Generation (RAG) to provide accurate, context-aware product recommendations based on a specific dataset. The system leverages LangChain and LangGraph within a containerized microservices architecture for scalability and observability.

19 lectures

What You Will Learn

Hands on LangChain and LangGraph for orchestrating conversational AI workflows.
Implementing Retrieval-Augmented Generation (RAG) for product recommendation.
Building a Flask-based REST API for the chatbot backend.
Containerizing applications using Docker for consistent deployment.
Deploying and managing applications on Kubernetes using Minikube.
Monitoring application performance using Prometheus and Grafana.
Integrating with AstraDB for vector storage.

System Architecture

Flipkart Product Recommender Chatbot with GCP Architecture Diagram

High-level architecture overview of the Flipkart Product Recommender Chatbot with GCP .

What You'll Build

  • A Flipkart product recommendation chatbot using RAG.
  • A Flask-based REST API backend.
  • Dockerized microservices for scalability.
  • Kubernetes deployment configurations.
  • Prometheus and Grafana dashboards for monitoring.
Flipkart Product Recommender Chatbot with GCP
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