Integrating Mistral AI with Spring Boot Using Spring AI

Here’s an example of integrating Mistral AI with a Spring Boot application using Spring AI support for generative AI services. This hypothetical example demonstrates how you can set up a simple service that interacts with Mistral AI models for text generation.

Step 1: Setup Spring Boot Project

  1. Create a Spring Boot project:

    • Use Spring Initializr to generate a Spring Boot project with the required dependencies:
      • Spring Web
      • Mistral AI
      • Any additional libraries as per your project needs.

  2. Complete pom.xml:

    <?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
	xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
	<modelVersion>4.0.0</modelVersion>
	<parent>
		<groupId>org.springframework.boot</groupId>
		<artifactId>spring-boot-starter-parent</artifactId>
		<version>3.4.1</version>
		<relativePath/> <!-- lookup parent from repository -->
	</parent>
	<groupId>com.example</groupId>
	<artifactId>demo</artifactId>
	<version>0.0.1-SNAPSHOT</version>
	<name>demo</name>
	<description>Demo project for Spring Boot</description>

	<properties>
		<java.version>17</java.version>
		<spring-ai.version>1.0.0-M4</spring-ai.version>
	</properties>
	<dependencies>
		<dependency>
			<groupId>org.springframework.boot</groupId>
			<artifactId>spring-boot-starter-web</artifactId>
		</dependency>
		<dependency>
			<groupId>org.springframework.ai</groupId>
			<artifactId>spring-ai-mistral-ai-spring-boot-starter</artifactId>
		</dependency>

		<dependency>
			<groupId>org.springframework.boot</groupId>
			<artifactId>spring-boot-starter-test</artifactId>
			<scope>test</scope>
		</dependency>
	</dependencies>
	<dependencyManagement>
		<dependencies>
			<dependency>
				<groupId>org.springframework.ai</groupId>
				<artifactId>spring-ai-bom</artifactId>
				<version>${spring-ai.version}</version>
				<type>pom</type>
				<scope>import</scope>
			</dependency>
		</dependencies>
	</dependencyManagement>

	<build>
		<plugins>
			<plugin>
				<groupId>org.springframework.boot</groupId>
				<artifactId>spring-boot-maven-plugin</artifactId>
			</plugin>
		</plugins>
	</build>
	<repositories>
		<repository>
			<id>spring-milestones</id>
			<name>Spring Milestones</name>
			<url>https://repo.spring.io/milestone</url>
			<snapshots>
				<enabled>false</enabled>
			</snapshots>
		</repository>
	</repositories>

</project>

Step 2: Configure Mistral AI Settings

Add the necessary configuration properties in the application.properties or application.yml file.

Using application.properties

mistral.api-key=your-mistral-api-key
mistral.base-url=https://api.mistral.ai

Using application.yml

mistral:
  api-key: your-mistral-api-key
  base-url: https://api.mistral.ai

Replace your-mistral-api-key with the API key provided by Mistral AI. Ensure your API key is kept secure (avoid hardcoding in production).

To obtain an API key for Mistral AI, you would typically follow these steps:

  1. Sign Up / Log In:

    • Go to the official Mistral AI website (or platform offering Mistral AI services).
    • Sign up for an account if you don't have one, or log in if you already have an account.

  2. Access the Developer Dashboard:

    • Once logged in, navigate to the developer or API section of the platform (usually under your account settings or a dedicated "API" tab).

  3. Generate API Key:

    • In the API section, you should see an option to generate a new API key.
    • Click on the option to create a new key. You may need to specify any permissions or scopes for the key, depending on what access you need.

  4. Copy the API Key:

    • After generating the API key, copy it to use in your application.
    • Be sure to store it securely (e.g., in environment variables or a secrets manager) as it grants access to your Mistral AI resources.

If you're unable to find specific instructions on the Mistral AI website, their documentation or support team should provide the necessary steps to generate and manage API keys.

Step 3: Create the Mistral Client Service

This service will interact with the Mistral API using the spring-ai-mistral-ai-spring-boot-starter.

Create MistralService Class

import org.springframework.ai.mistral.MistralClient;
import org.springframework.ai.mistral.MistralRequest;
import org.springframework.ai.mistral.MistralResponse;
import org.springframework.stereotype.Service;

@Service
public class MistralService {

    private final MistralClient mistralClient;

    public MistralService(MistralClient mistralClient) {
        this.mistralClient = mistralClient;
    }

    public String generateResponse(String prompt) {
        MistralRequest request = new MistralRequest();
        request.setPrompt(prompt);

        MistralResponse response = mistralClient.complete(request);
        return response.getText();
    }
}

Step 4: Create a REST Controller

Expose an endpoint that allows interaction with the Mistral service.

Create MistralController Class

import com.example.mistral.service.MistralService;
import org.springframework.web.bind.annotation.*;

@RestController
@RequestMapping("/api/mistral")
public class MistralController {

    private final MistralService mistralService;

    public MistralController(MistralService mistralService) {
        this.mistralService = mistralService;
    }

    @PostMapping("/generate")
    public String generateResponse(@RequestBody String prompt) {
        return mistralService.generateResponse(prompt);
    }
}

Step 5: Run Your Application

  1. Start your Spring Boot application:

    mvn spring-boot:run

  2. Test the application using tools like Postman or cURL.

Step 6: Test the API

Endpoint:

POST http://localhost:8080/api/mistral/generate

Request Body:

{
    "prompt": "Explain the basics of artificial intelligence."
}

Using cURL:

curl -X POST -H "Content-Type: application/json" -d '{"prompt":"Explain the basics of artificial intelligence."}' http://localhost:8080/api/mistral/generate

Expected Output

The response will be the generated text by Mistral AI based on the given prompt.

Example Response:

{
    "response": "Artificial intelligence (AI) is the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning, reasoning, and self-correction."
}

Step 7: Secure Your API Key

For production environments:

  • Use environment variables or a secure vault service to manage the API key.
  • Avoid exposing sensitive keys in version control.

Additional Tips

  1. Error Handling: Add custom error-handling logic to handle cases like invalid prompts, API failures, or invalid API keys.

    try {
    MistralResponse response = mistralClient.complete(request);
    return response.getText();
} catch (Exception e) {
    throw new RuntimeException("Failed to get a response from Mistral AI: " + e.getMessage());
}

  2. Logging: Use a logging framework (e.g., Logback or SLF4J) to log errors, requests, and responses for debugging and monitoring.

  3. Unit Testing: Mock the MistralClient to test the MistralService and MistralController without making actual API calls.

    @Test
public void testGenerateResponse() {
    MistralClient mockClient = mock(MistralClient.class);
    MistralService mistralService = new MistralService(mockClient);
    
    MistralRequest request = new MistralRequest();
    request.setPrompt("test");

    MistralResponse mockResponse = new MistralResponse();
    mockResponse.setText("test response");

    when(mockClient.complete(request)).thenReturn(mockResponse);

    assertEquals("test response", mistralService.generateResponse("test"));
}

This guide should help you fully set up and integrate Mistral AI into your Spring Boot project.

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