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Spring AI Powered Local CLI Chat Bot

This example is a chatbot you use through the Command Line Interface (CLI). It's inspired by the spring-ai-cli-chatbot project, but unlike the original, it focuses on full local execution and offers AI-driven conversations without requiring external AI services.

Quick Start

Build and run the app:

./mvnw clean install
./mvnw spring-boot:run

Auto-configurations

AI Model

Spring AI works with Ollama for local LLM and embedding models. No API keys are required. To enable this, simply add the following dependency:

<dependency>
   <groupId>org.springframework.ai</groupId>
   <artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
</dependency>

Before using Ollama with Spring AI, ensure that Ollama is installed and running on your system, refer to the Spring AI Ollama Chat Prerequisites.

To use different models for local LLM and embedding in your Spring Boot application with Ollama, you can specify them using command-line arguments. Here’s how to do it:

./mvnw spring-boot:run -Dspring-boot.run.arguments="--spring.ai.ollama.chat.options.model=llama3.2:1b --spring.ai.ollama.embedding.options.model=bge-m3"

Tips

• For additional configuration options in Spring AI with Ollama:

  • LLM Settings: LLM Properties Documentation
  • Embedding Settings: Embedding Properties Documentation

• For a list of models supported by Ollama:

  • LLM Models
  • Embedding Models

Vector Store

@Bean
public VectorStore vectorStore(EmbeddingModel embeddingModel){
    return new SimpleVectorStore(embeddingModel);
}

The project uses Spring AI's SimpleVectorStore, eliminating the need for external vector databases.

PDF Document Processing

PDF document reading capability is enabled through the spring-ai-pdf-document-reader dependency.

Implementation Details

Vector Store Loading

vectorStore.add(new TokenTextSplitter().split(new PagePdfDocumentReader(localDocs).read()));

Chat Loop

try (Scanner scanner = new Scanner(System.in)) {
    while (true) {
        System.out.print("\nUSER: ");
        String userMessage = scanner.nextLine();
        System.out.print("\nASSISTANT: ");
        chatClient.prompt(userMessage).stream().content().toStream().forEach(System.out::print);
        System.out.println();
    }
}

Creates an interactive loop for chatbot interaction, streaming the assistant’s response in real-time.

Key Features

1. Fully Local Execution: All components run on your local machine, ensuring privacy and offline capability.
2. Ollama Integration: Uses Ollama for both LLM and embedding models, offering high-performance local AI processing.
3. Spring AI's SimpleVectorStore: Implements a lightweight vector store for efficient information retrieval without external dependencies.
4. Interactive Console Interface: Provides a streamlined console-based interface for real-time chatbot interaction.