Join us for an immersive workshop — Optimizing RAG Workflow with LangChain, Gemini API, and Redis via Docker as a Cache Layer — designed for developers, data scientists, and AI enthusiasts eager to build faster and more efficient Retrieval-Augmented Generation (RAG) applications.

In this hands-on session, you’ll learn how to integrate LangChain, harness the power of Google Gemini API, and implement Redis as a high-performance cache layer deployed via Docker. Through practical exercises and real-world examples, participants will explore best practices for optimizing data retrieval, improving response times, and scaling AI-powered applications seamlessly.

Key takeaways include:

Understanding the fundamentals of RAG workflows and their real-world applications.

Integrating LangChain with Gemini API for advanced AI-driven data retrieval.

Deploying Redis with Docker to optimize caching strategies.

Building scalable and efficient AI applications with enhanced performance.

Whether you're new to RAG or looking to fine-tune your existing workflows, this workshop equips you with the tools and knowledge to take your AI solutions to the next level.