# spring_ai_alibaba_project

**Repository Path**: li9699/spring_ai_alibaba_project

## Basic Information

- **Project Name**: spring_ai_alibaba_project
- **Description**: SAA项目实战
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 2
- **Created**: 2025-10-09
- **Last Updated**: 2025-10-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: Spring, AI, 阿里云百炼平台

## README

# Spring AI Alibaba Project Examples

This is a collection of example projects using Spring AI and the Alibaba DashScope API, demonstrating how to integrate large language models into Spring Boot applications.

## Project Overview

This project contains multiple modules demonstrating the following capabilities:

- Basic Hello World example
- Using Ollama local models
- Using ChatModel and ChatClient
- Streaming output handling
- Prompt Engineering
- Using prompt templates
- Generating structured output
- Chat persistence
- Text-to-image generation
- Text-to-speech conversion
- Text embedding vector generation
- AI operations application based on Retrieval-Augmented Generation (RAG)
- Tool calling capabilities
- MCP protocol server and client implementation
- Bailing Platform RAG application
- Intelligent ordering assistant

## Quick Start

### Prerequisites

- Java 17 or higher
- Spring Boot 3.x
- Maven build tool
- DashScope API key

### Installation and Configuration

1. Clone the project repository
2. Configure the DashScope API key in `application.yml`
3. Build the project using Maven
4. Run the required modules

### Running Examples

Each module is an independent Spring Boot application that can be run individually. For example, to run the basic Hello World example:

```bash
cd SAA-01HelloWorld
mvn spring-boot:run
```

## Usage Instructions

Access different endpoints to experience various features:

- `/hello/chat` - Basic chat functionality
- `/hello/stream` - Streaming chat output
- `/ollama/chat` - Using Ollama local models
- `/chatclient/dochat` - ChatClient usage example
- `/stream/chatflux*` - Streaming output demonstration
- `/prompt/chat*` - Prompt engineering example
- `/prompttemplate/chat*` - Prompt template usage
- `/structuredoutput/chat` - Structured output generation
- `/chatmemory/chat` - Chat persistence
- `/t2i/image` - Text-to-image generation
- `/t2v/voice` - Text-to-speech conversion
- `/text2embed` - Text embedding vector generation
- `/ragaiops` - RAG AI operations application
- `/toolcall/chat*` - Tool calling capabilities
- `/mcpclient/chat*` - MCP protocol client
- `/bailian/rag/chat` - Bailing Platform RAG application
- `/eatAgent` - Intelligent ordering assistant

## Contribution Guidelines

Code contributions and improvements are welcome. Please follow these steps:

1. Fork the project
2. Create a new branch
3. Submit your changes
4. Create a Pull Request

## License

This project uses the Apache 2.0 license. For details, please refer to the LICENSE file.