A chatbot using Generative AI has been added to the famous Spring Petclinic application. This version uses the LangChain4j project and currently supports OpenAI or Azure's OpenAI as the LLM provider. This is a fork from the spring-petclinic-ai based on Spring AI.
This sample demonstrates how to easily integrate AI/LLM capabilities into a Java application using LangChain4j. This can be achieved thanks to:
- A unified abstraction layer designed to decouple your code from specific implementations like LLM or embedding providers, enabling easy component swapping. Only the application.properties file references LLM providers such as OpenAI or Azure OpenAI.
- Memory offers context to the LLM for both your current and previous conversations, with support for multiple users.
Refer to the use of the
MessageWindowChatMemory
class in AssistantConfiguration and the@MemoryId
annotation in the Assistant interface. - AI Services enables declarative definitions of complex AI behaviors through a straightforward Java API.
See the use of the
@AiService
annotation in the Assistant interface. - System prompts play a vital role in LLMs as they shape how models interpret and respond to user queries.
Look at the
@SystemMessage
annotation usage in the Assistant interface. - Streaming response token-by-token when using the
TokenStream
return type and Spring Server-Sent Events supports. Take a look at the AssistantController REST controller - Function calling or Tools allows the LLM to call, when necessary, one or more java methods.
The AssistantTool component declares functions using the
@Tool
annotation from LangChain4j. - Structured outputs allow LLM responses to be received in a specified format as Java POJOs. AssistantTool uses Java records as the LLM/ input/output data structure.
- Retrieval-Augmented Generation (RAG) enables an LLM to incorporate and respond based on specific data—such as data from the petclinic database—by ingesting and referencing it during interactions.
The AssistantConfiguration declares the
EmbeddingModel
,InMemoryEmbeddingStore
andEmbeddingStoreContentRetriever
beans while the EmbeddingStoreInit class handles vets data ingestion at startup. The VetQueryRouter demonstrates how to conditionally skip retrieval, with decision-making driven by an LLM.
Spring Petclinic integrates a Chatbot that allows you to interact with the application in a natural language. Here are some examples of what you could ask:
- Please list the owners that come to the clinic.
- How many veterinary cardiologists are there?
- Is there an owner named Betty? What's her lastname?
- Which owners have dogs?
- Add a dog for Betty. Its name is Moopsie. His birthday is on 2 October 2024.
- Add today's visit to Moopsie.
Spring Petclinic currently supports OpenAI or Azure's OpenAI as the LLM provider.
In order to start spring-petlinic-langchain4j
perform the following steps:
- Decide which provider you want to use. By default, the
langchain4j-open-ai-spring-boot-starter
dependency is enabled. You can change it tolangchain4j-azure-open-ai-spring-boot-starter
in eitherpom.xml
or inbuild.gradle
, depending on your build tool of choice. - Create an OpenAI API key or a Azure OpenAI resource in your Azure Portal.
Refer to the OpenAI's quickstart or Azure's documentation for further information on how to obtain these.
You only need to populate the provider you're using - either openai, or azure-openai.
If you don't have your own OpenAI API key, don't worry!
You can temporarily use the
demo
key, which OpenAI provides free of charge for demonstration purposes. Thisdemo
key has a quota, is limited to the gpt-4o-mini model, and is intended solely for demonstration use. - Export your API keys and endpoint as environment variables:
- either OpenAI:
export OPENAI_API_KEY="your_api_key_here"
- or Azure OpenAI:
export AZURE_OPENAI_ENDPOINT="https://your_resource.openai.azure.com" export AZURE_OPENAI_KEY="your_api_key_here"
- Follow the next section Run Petclinic locally
Spring Petclinic is a Spring Boot application built using Maven or Gradle. You can build a jar file and run it from the command line (it should work just as well with Java 17 or newer):
git clone https://github.com/spring-petclinic/spring-petclinic-langchain4j.git
cd spring-petclinic
./mvnw package
java -jar target/*.jar
You can then access the Petclinic at http://localhost:8080/.
Or you can run it from Maven directly using the Spring Boot Maven plugin. If you do this, it will pick up changes that you make in the project immediately (changes to Java source files require a compile as well - most people use an IDE for this):
./mvnw spring-boot:run
NOTE: If you prefer to use Gradle, you can build the app using
./gradlew build
and look for the jar file inbuild/libs
.
There is no Dockerfile
in this project. You can build a container image (if you have a docker daemon) using the Spring Boot build plugin:
./mvnw spring-boot:build-image
Our issue tracker is available here.
In its default configuration, Petclinic uses an in-memory database (H2) which
gets populated at startup with data. The h2 console is exposed at http://localhost:8080/h2-console
,
and it is possible to inspect the content of the database using the jdbc:h2:mem:<uuid>
URL. The UUID is printed at startup to the console.
A similar setup is provided for MySQL and PostgreSQL if a persistent database configuration is needed. Note that whenever the database type changes, the app needs to run with a different profile: spring.profiles.active=mysql
for MySQL or spring.profiles.active=postgres
for PostgreSQL. See the Spring Boot documentation for more detail on how to set the active profile.
You can start MySQL or PostgreSQL locally with whatever installer works for your OS or use docker:
docker run -e MYSQL_USER=petclinic -e MYSQL_PASSWORD=petclinic -e MYSQL_ROOT_PASSWORD=root -e MYSQL_DATABASE=petclinic -p 3306:3306 mysql:8.4
or
docker run -e POSTGRES_USER=petclinic -e POSTGRES_PASSWORD=petclinic -e POSTGRES_DB=petclinic -p 5432:5432 postgres:16.3
Further documentation is provided for MySQL and PostgreSQL.
Instead of vanilla docker
you can also use the provided docker-compose.yml
file to start the database containers. Each one has a profile just like the Spring profile:
docker-compose --profile mysql up
or
docker-compose --profile postgres up
At development time we recommend you use the test applications set up as main()
methods in PetClinicIntegrationTests
(using the default H2 database and also adding Spring Boot Devtools), MySqlTestApplication
and PostgresIntegrationTests
. These are set up so that you can run the apps in your IDE to get fast feedback and also run the same classes as integration tests against the respective database. The MySql integration tests use Testcontainers to start the database in a Docker container, and the Postgres tests use Docker Compose to do the same thing.
There is a petclinic.css
in src/main/resources/static/resources/css
. It was generated from the petclinic.scss
source, combined with the Bootstrap library. If you make changes to the scss
, or upgrade Bootstrap, you will need to re-compile the CSS resources using the Maven profile "css", i.e. ./mvnw package -P css
. There is no build profile for Gradle to compile the CSS.
The following items should be installed in your system:
- Java 17 or newer (full JDK, not a JRE)
- Git command line tool
- Your preferred IDE
- Eclipse with the m2e plugin. Note: when m2e is available, there is an m2 icon in
Help -> About
dialog. If m2e is not there, follow the install process here - Spring Tools Suite (STS)
- IntelliJ IDEA
- VS Code
- Eclipse with the m2e plugin. Note: when m2e is available, there is an m2 icon in
-
On the command line run:
git clone https://github.com/spring-petclinic/spring-petclinic-langchain4j.git
-
Inside Eclipse or STS:
Open the project via
File -> Import -> Maven -> Existing Maven project
, then select the root directory of the cloned repo.Then either build on the command line
./mvnw generate-resources
or use the Eclipse launcher (right-click on project andRun As -> Maven install
) to generate the CSS. Run the application's main method by right-clicking on it and choosingRun As -> Java Application
. -
Inside IntelliJ IDEA:
In the main menu, choose
File -> Open
and select the Petclinic pom.xml. Click on theOpen
button.-
CSS files are generated from the Maven build. You can build them on the command line
./mvnw generate-resources
or right-click on thespring-petclinic
project thenMaven -> Generates sources and Update Folders
. -
A run configuration named
PetClinicApplication
should have been created for you if you're using a recent Ultimate version. Otherwise, run the application by right-clicking on thePetClinicApplication
main class and choosingRun 'PetClinicApplication'
.
-
-
Navigate to the Petclinic
Visit http://localhost:8080 in your browser.
Spring Boot Configuration | Class or Java property files |
---|---|
The Main Class | PetClinicApplication |
Properties Files | application.properties |
Caching | CacheConfiguration |
The Spring Petclinic "main" branch in the spring-projects GitHub org is the "canonical" implementation based on Spring Boot and Thymeleaf. There are quite a few forks in the GitHub org spring-petclinic. If you are interested in using a different technology stack to implement the Pet Clinic, please join the community there.
One of the best parts about working on the Spring Petclinic application is that we have the opportunity to work in direct contact with many Open Source projects. We found bugs/suggested improvements on various topics such as Spring, Spring Data, Bean Validation and even Eclipse! In many cases, they've been fixed/implemented in just a few days. Here is a list of them:
Name | Issue |
---|---|
Spring JDBC: simplify usage of NamedParameterJdbcTemplate | SPR-10256 and SPR-10257 |
Bean Validation / Hibernate Validator: simplify Maven dependencies and backward compatibility | HV-790 and HV-792 |
Spring Data: provide more flexibility when working with JPQL queries | DATAJPA-292 |
The issue tracker is the preferred channel for bug reports, feature requests and submitting pull requests.
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The Spring PetClinic sample application is released under version 2.0 of the Apache License.