This session focuses on the functionalities of Firebase Genkit for effectively managing AI models, particularly in the context of Retrieval-Augmented Generation (RAG) utilizing HNSW (Hierarchical Navigable Small World) for efficient retrieval.

Key areas covered:
- Model Management: Learn how Genkit streamlines the process of deploying, monitoring, and updating your AI models, ensuring smooth integration with your applications.
- Debugging Techniques: Uncover debugging tools within Genkit that help identify and troubleshoot issues within your AI models, accelerating development cycles.
- Deployment Strategies: Explore Genkit's capabilities for seamless deployment of your AI models, including serverless options for scalability and efficient resource management.
- RAG with HNSW Implementation: Gain insights into how Genkit facilitates the implementation of RAG, a powerful technique for enhancing generative models. We'll delve into the integration of HNSW for efficient retrieval within the RAG framework.

This session explores advanced functionalities of Firebase Genkit for developers.

Focus: Effective management of AI models, particularly for Retrieval-Augmented Generation (RAG) utilizing Hierarchical Navigable Small World (HNSW) for efficient retrieval.

Key Areas:
- Model Management & Deployment
- Debugging Techniques
- RAG with HNSW Implementation