Back to Projects
Agentic AIadvanced

Production grade advance RAG with LangGraph Guardrails LLM Gateway Evals GCP

Develop a production-grade, Enterprise level , Scalable Retrieval-Augmented Generation (RAG) system leveraging LangGraph, Google Cloud Platform (GCP) . This system intelligently distinguishes between technical 'True Data' and random 'Noisy Data' through semantic re-ranking and history-aware planning, ensuring accurate and contextually relevant responses. This system is designed to be highly reliable and robust and secured with the integration LLM Gateways , Guardrails and Evaluations. This project is all you need to master entire LLM ecosystem , all you need is excitement , patience and eagerness to learn .

63 lectures

What You Will Learn

Mastering LangGraph for building Advanced RAG pipelines.
Implementing semantic re-ranking techniques to filter noisy data.
Designing a scalable, three-tier enterprise cloud architecture on GCP.
Building event-driven data ingestion pipelines using GCS and Eventarc.
Implementing persistent memory using Postgres.
Orchestrating multi-container builds with Cloud Build
Automating infrastructure provisioning with Terraform.
Understanding LLM gateways , LLM security , LLM Evaluation
Tokens and cost optimization

System Architecture

Production grade advance RAG with LangGraph Guardrails LLM Gateway Evals GCP Architecture Diagram

High-level architecture overview of the Production grade advance RAG with LangGraph Guardrails LLM Gateway Evals GCP .

What You'll Build

  • A production-grade advange RAG system.
  • An automated data ingestion pipeline.
  • A scalable microservices architecture on GCP.
  • Infrastructure-as-Code using Terraform.
  • LLM Gateways , Guardrails and Evaluation Pipeline

Project Instructor

Divesh Jadhwani

Divesh Jadhwani

3+ years exp
LinkedIn
Production grade advance RAG with LangGraph Guardrails LLM Gateway Evals GCP
Premium
One Subscription. 40+ Projects. Unlimited Access.
AccessMobile & Web