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Building Real-Time RAG Systems with Gemini & the Multimodal Live API

Chapters

1Foundations of Real-Time Retrieval-Augmented Generation

2Gemini Fundamentals: Architecture and Multimodal Capabilities

3Data Sources and Vector Stores for Real-Time RAG

4Real-Time Ingestion and Streaming Data Pipelines

5The Multimodal Live API: Authentication, Endpoints, and Workflows

6Prompt Engineering for RAG with Gemini

7Memory and Context Management in Real-Time RAG

8Latency, Throughput, and Quality of Service

9Security, Privacy, and Compliance in RAG Systems

10Evaluation, Metrics, and A/B Testing for RAG

11Deployment and Orchestration: Cloud and Edge

12Case Studies: Real-World RAG Scenarios

13Advanced Retrieval Techniques: Hybrid Search and Re-ranking

13.1 Hybrid Search Architectures 13.2 Dense + Sparse Vector Strategies 13.3 Reranking Techniques for Better Precision 13.4 Temporal Relevance and Freshness 13.5 Personalization in Retrieval 13.6 Cross-Modal Retrieval 13.7 Contextual Filtering and Safety 13.8 Retrieval Debugging and Diagnostics 13.9 Index Lifecycle Management 13.10 Semantic Drift and Drift Mitigation 13.11 Redundancy and Fault Tolerance in Retrieval 13.12 Probabilistic Data Structures for Scaling 13.13 Privacy-Preserving Retrieval 13.14 Efficiency in Embeddings Computation 13.15 Latency-Aware Retrieval Pipelines

14Observability: Monitoring, Logging, and Debugging

15Extending Gemini with Custom Tools and Plugins

Courses/Building Real-Time RAG Systems with Gemini & the Multimodal Live API/Advanced Retrieval Techniques: Hybrid Search and Re-ranking

Advanced Retrieval Techniques: Hybrid Search and Re-ranking

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Push retrieval quality further with advanced strategies for hybrid search, reranking, and temporal relevance.

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13.5 Personalization in Retrieval

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