Name		Name	Last commit message	Last commit date
parent directory ..
agents/research-multi-agents		agents/research-multi-agents
batch-prediction		batch-prediction
chat-completions		chat-completions
code-execution		code-execution
context-caching		context-caching
controlled-generation		controlled-generation
evaluation		evaluation
function-calling		function-calling
getting-started		getting-started
grounding		grounding
long-context		long-context
multimodal-live-api		multimodal-live-api
orchestration		orchestration
prompts		prompts
qa-ops		qa-ops
rag-engine		rag-engine
reasoning-engine		reasoning-engine
responsible-ai		responsible-ai
sample-apps		sample-apps
tuning		tuning
use-cases		use-cases
README.md		README.md

README.md

Generative AI

YouTube Video: Introduction to Gemini on Vertex AI

Gemini is a family of generative AI models developed by Google DeepMind that is designed for multimodal use cases.

On Google Cloud, the Gemini API in Vertex AI provides a unified interface for interacting with multimodal Gemini models, such as:

	Description
`getting-started/`	Get started with the Gemini API in Vertex AI
`sample-apps/`	Discover sample apps using Gemini
`use-cases/`	Explore industry use-cases enabled by Gemini (e.g. retail, education)
`evaluation/`	Learn how to evaluate Gemini with Vertex AI Model Evaluation for Generative AI
`function-calling/`	Learn how to use the function calling feature of Gemini
`grounding/`	Learn how to use the grounding feature of Gemini
`rag-engine/`	Discover how to utilize the RAG Engine feature of Vertex AI
`prompts/`	Learn how to create and use effective prompts with Gemini.
`qa-ops/`	Learn about the question-answer operations available in Gemini
`reasoning-engine/`	Discover how to utilize the Reasoning Engine feature of Vertex AI
`responsible-ai/`	Learn best practices for responsible AI and security with the Gemini API in Vertex AI.
`tuning/`	Learn how to tune and customize the Gemini models for specific use-cases.