Practical AI examples using Spring AI

Included examples

Basic AI Chat - Simple chat interface with Spring AI
Document Analysis - Upload and analyze documents for summarization and action points
Sentiment Analysis - Analyze customer reviews with sentiment detection and response drafting
Image Data Extraction - Extract structured data from images
RAG Chat - Advanced Retrieval Augmented Generation with:
- Multi-source document retrieval
- Context-aware query rewriting
- Chat memory for conversational context
Function Calling - Demonstrate AI function calling capabilities with product data

Pre-Requisites

Java 21+
Container runtime (e.g. Podman or Docker) for running the OpenTelemetry and PostgreSQL Dev Services
The application expects you to have the following API key as an environment variable:

OPENAI_API_KEY: OpenAI API key

Running the examples

Run Application.java in your IDE or use the following command:

mvn spring-boot:run

Under the hood, the Arconia framework will automatically spin up a PostgreSQL database server and a Grafana LGTM observability platform using Testcontainers.

Observability

The application logs will show you the URL where you can access the Grafana observability platform.

...o.t.grafana.LgtmStackContainer: Access to the Grafana dashboard: http://localhost:38125

By default, logs, metrics, and traces are exported via OTLP using the HTTP/Protobuf format.

In Grafana, you can query the telemetry from the "Drilldown" and "Explore" sections.

Using local models

You can use local models with Ollama or LM Studio by updating the configuration in the application.properties file. Uncomment and modify the following settings: