
playground-flight-booking
Spring AI powered expert system demo
Stars: 71

This repository contains a Spring AI re-implementation of an expert system demo that showcases building an AI-powered system with capabilities such as retrieval augmented generation, function calling using Java methods, and interaction with the user through an LLM. The app requires Java 17+ and an OpenAI API key. It provides examples of integrating with various chat services like OpenAI, VertexAI Gemini, Azure OpenAI, Groq, and Anthropic Claude 3. Users can explore different chat options and models for AI interactions within the system.
README:
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
- Java 17+
- OpenAI API key in
OPENAI_API_KEY
environment variable
Run the app by running Application.java
in your IDE or mvn
in the command line.
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 configuraiton to the applicaiton.properties
:
spring.ai.openai.api-key=${OPENAI_API_KEY}
spring.ai.openai.chat.options.model=gpt-4o
Add to the POM the Spring AI VertexAI Gemeni and Onnx Transfomer Embedding boot starters:
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-vertex-ai-gemini-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-transformers-spring-boot-starter</artifactId>
</dependency>
Add the VertexAI Gemini configuraiton to the applicaiton.properties
:
spring.ai.vertex.ai.gemini.project-id=${VERTEX_AI_GEMINI_PROJECT_ID}
spring.ai.vertex.ai.gemini.location=${VERTEX_AI_GEMINI_LOCATION}
spring.ai.vertex.ai.gemini.chat.options.model=gemini-1.5-pro-001
# spring.ai.vertex.ai.gemini.chat.options.model=gemini-1.5-flash-001
Add to the POM the Spring AI Azure OpenAI boot starter:
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-azure-openai-spring-boot-starter</artifactId>
</dependency>
Add the Azure OpenAI configuraiton to the applicaiton.properties
:
spring.ai.azure.openai.api-key=${AZURE_OPENAI_API_KEY}
spring.ai.azure.openai.endpoint=${AZURE_OPENAI_ENDPOINT}
spring.ai.azure.openai.chat.options.deployment-name=gpt-4o
It reuses the OpenAI Chat client but ponted to the Groq endpont
Add to the POM the Spring AI Open AI boot starter:
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-transformers-spring-boot-starter</artifactId>
</dependency>
Add the Groq configuraiton to the applicaiton.properties
:
spring.ai.openai.api-key=${GROQ_API_KEY}
spring.ai.openai.base-url=https://api.groq.com/openai
spring.ai.openai.chat.options.model=llama3-70b-8192
Add to the POM the Spring AI Anthropic Claude and Onnx Transfomer 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 configuraiton to the applicaiton.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
./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
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