Context assembly with LangChain4j and Ollama

This example is the one shown in the book. It wires four context sources into a single AI service: the system instruction, a bounded chat memory, a content retriever, and a tool object.

Three questions exercise the three sources in turn, so the console output shows which one answered each turn.

Requirements

• Java 21+
• Maven 3.9+
• Ollama installed locally
• A pulled chat model such as llama3.2:1b
• A pulled embedding model such as nomic-embed-text

Steps for running this example in the shell

1. Start Ollama and pull the models:

ollama serve
ollama pull llama3.2:1b
ollama pull nomic-embed-text

2. Run the application:

mvn compile exec:java

Output

Use the self-service portal to reset your password, then sign in again.
42
You first asked how to reset your password.