spring-ai-langsmith

Arconia OpenTelemetry with Spring AI and LangSmith

Application that demonstrates the use of Arconia OpenTelemetry with Spring AI and LangSmith.

Pre-requisites

• Java 25
• Podman/Docker

Ollama

The application consumes models from an Ollama inference server. If you don't have an Ollama server running locally on your laptop, an Ollama service will be automatically spun up for you by the Arconia Dev Services when you run the application. Either way, Spring AI will take care of pulling the needed Ollama models when the application starts, if they are not available yet on your machine.

LangSmith

This application uses LangSmith to visualize the interactions with the language model. To use LangSmith, you need to set the LANGSMITH_API_KEY environment variable with your LangSmith API key.

export LANGSMITH_API_KEY=your_langsmith_api_key

Running the application

Run the application as follows:

./gradlew bootRun

Alternatively, you can use the Arconia CLI:

arconia dev

Under the hood, the Arconia framework will automatically spin up an Ollama service, in case you don't have one running locally (see Arconia Dev Services for more information).

The application will be accessible at http://localhost:8080.

Metrics and traces are exported via OTLP to LangSmith using the HTTP/Protobuf format.

Calling the application

Note

These examples use the httpie CLI to send HTTP requests.

Chat

Call the application that will use a chat model to answer your question.

http :8080/chat question=="What is the capital of Italy?" -b

Next, try a request which uses tool calling.

http :8080/chat/tools authorName=="Philip Pullman" -b

Embedding

Call the application that will use an embedding model to generate embeddings for your query.

http :8080/embed query=="The capital of Italy is Rome"

Let's try now generating embeddings for multiple queries.

http :8080/embed/multiple-queries query1=="The capital of Italy is Rome" query2=="The capital of Denmark is Copenhagen" -b