Awesome
AI powered expert system demo
Spring AI re-implementation of https://github.com/marcushellberg/java-ai-playground
This app shows how you can use Spring AI to build an AI-powered system that:
- Has access to terms and conditions (retrieval augmented generation, RAG)
- Can access tools (Java methods) to perform actions (Function Calling)
- Uses an LLM to interact with the user
Requirements
- Java 17+
- OpenAI API key in
OPENAI_API_KEY
environment variable
Running
Run the app by running Application.java
in your IDE or mvn
in the command line.
With OpenAI Chat
Add to the POM the Spring AI Open AI boot starter:
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>
Add the OpenAI configuration to the application.properties
:
spring.ai.openai.api-key=${OPENAI_API_KEY}
spring.ai.openai.chat.options.model=gpt-4o
WIth VertexAI Gemini Chat
Add to the POM the Spring AI VertexAI Gemini and Onnx Transformer Embedding boot starters:
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-vertex-ai-gemini-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-transformers-spring-boot-starter</artifactId>
</dependency>
Add the VertexAI Gemini configuration to the application.properties
:
spring.ai.vertex.ai.gemini.project-id=${VERTEX_AI_GEMINI_PROJECT_ID}
spring.ai.vertex.ai.gemini.location=${VERTEX_AI_GEMINI_LOCATION}
spring.ai.vertex.ai.gemini.chat.options.model=gemini-1.5-pro-001
# spring.ai.vertex.ai.gemini.chat.options.model=gemini-1.5-flash-001
With Azure OpenAI Chat
Add to the POM the Spring AI Azure OpenAI boot starter:
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-azure-openai-spring-boot-starter</artifactId>
</dependency>
Add the Azure OpenAI configuration to the application.properties
:
spring.ai.azure.openai.api-key=${AZURE_OPENAI_API_KEY}
spring.ai.azure.openai.endpoint=${AZURE_OPENAI_ENDPOINT}
spring.ai.azure.openai.chat.options.deployment-name=gpt-4o
With Groq Chat
It reuses the OpenAI Chat client but pointed to the Groq endpoint
Add to the POM the Spring AI Open AI boot starter:
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-transformers-spring-boot-starter</artifactId>
</dependency>
Add the Groq configuration to the application.properties
:
spring.ai.openai.api-key=${GROQ_API_KEY}
spring.ai.openai.base-url=https://api.groq.com/openai
spring.ai.openai.chat.options.model=llama3-70b-8192
With Anthropic Claude 3 Chat
Add to the POM the Spring AI Anthropic Claude and Onnx Transformer Embedding boot starters:
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-anthropic-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-transformers-spring-boot-starter</artifactId>
</dependency>
Add the Anthropic configuration to the application.properties
:
spring.ai.anthropic.api-key=${ANTHROPIC_API_KEY}
spring.ai.openai.chat.options.model=llama3-70b-8192
spring.ai.anthropic.chat.options.model=claude-3-5-sonnet-20240620
Build Jar
./mvnw clean install -Pproduction
java -jar ./target/playground-flight-booking-0.0.1-SNAPSHOT.jar
docker run -it --rm --name postgres -p 5432:5432 -e POSTGRES_USER=postgres -e POSTGRES_PASSWORD=postgres ankane/pgvector