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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

6.1 Principles of Prompt Engineering for RAG 6.2 System vs. User vs. Tool Prompts 6.3 Context Window Sizing for Multimodal Inputs 6.4 Tool Invocation Patterns and Guardrails 6.5 Retrieval-Augmented Prompts 6.6 Structured vs. Unstructured Data in Prompts 6.7 Chain-of-Thought vs Direct Answers 6.8 Prompt Debugging Techniques 6.9 Prompt Versioning and A/B Testing 6.10 Personalization in Prompts 6.11 Safety and Content Guardrails 6.12 Handling Hallucinations 6.13 Prompt Templating and Libraries 6.14 Multimodal Prompt Strategies 6.15 Tool Feedback and Result Validation

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

14Observability: Monitoring, Logging, and Debugging

15Extending Gemini with Custom Tools and Plugins

Courses/Building Real-Time RAG Systems with Gemini & the Multimodal Live API/Prompt Engineering for RAG with Gemini

Prompt Engineering for RAG with Gemini

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Design effective prompts that leverage Gemini across modalities, control flow, and tool invocations to maximize accuracy and reliability.

Content

5 of 15

6.5 Retrieval-Augmented Prompts

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