The Spring AI project aims to streamline the development of applications that incorporate artificial intelligence functionality without unnecessary complexity.

Spring AI 1.1.9-SNAPSHOT

|   | This version is still in development and is not considered stable yet. For the latest stable version, please use [Spring AI 2.0.1](https://docs.spring.io/spring-ai/reference/index.html)! |
|---|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|

# Google VertexAI API

[VertexAI API](https://cloud.google.com/vertex-ai/docs/reference) provides high-quality custom machine learning models with minimal machine learning expertise and effort.

Spring AI provides integration with VertexAI API through the following client(s):

- [VertexAI Gemini Chat](https://docs.spring.io/spring-ai/reference/1.1-SNAPSHOT/api/chat/vertexai-gemini-chat.html)

Google VertexAI

KnowForge 新版本 2026.0.3 正式发布！！！

AI Concepts

Getting Started

Introduction

Recursive Advisors

Advisors

Chat Client API

Prompts

Structured Output

Multimodality

Chat Models Comparison

Amazon Bedrock Converse

Anthropic

Azure OpenAI

DeepSeek

Docker Model Runner

Google

Groq

Hugging Face

Mistral AI

MiniMax

Moonshot AI

NVIDIA

Ollama

Perplexity AI

OCI Generative AI

OpenAI SDK (Official)

OpenAI

QianFan

ZhiPu AI

Chat Models

Amazon Bedrock

OCI GenAI

(ONNX) Transformers

PostgresML

VertexAI

Embedding Models

Stability

ZhiPuAI

Image Models

Transcription API

Text-To-Speech (TTS) API

Audio Models

Moderation Models

Models

Chat Memory

Tool Calling

MCP Client Boot Starters

STDIO and SSE MCP Servers

Streamable-HTTP MCP Servers

Stateless Streamable-HTTP MCP Servers

MCP Server Boot Starters

MCP Security (WIP)

Client Annotations

Server Annotations

Special Parameters

MCP Annotations Examples

MCP Annotations

Model Context Protocol (MCP)

ETL Pipeline

Retrieval Augmented Generation (RAG)

Model Evaluation

Azure AI Service

Azure Cosmos DB

Apache Cassandra Vector Store

Chroma

Couchbase

Elasticsearch

GemFire

MariaDB Vector Store

Milvus

MongoDB Atlas

Neo4j

OpenSearch

Oracle

PGvector

Pinecone

Qdrant

Redis

SAP Hana

Typesense

Weaviate

Vector Databases

Observability

Development-time Services

Testcontainers

Testing

Reference

Awesome Spring AI

Getting Started with MCP

Dynamic Tool Discovery

LLM-as-a-Judge Evaluation

Prompt Engineering Patterns

Building Effective Agents

Deploying to the Cloud

Guides

Migrating FunctionCallback to ToolCallback API

Upgrade Notes

Google VertexAI

Google VertexAI API

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