LLM Applications with Java, Spring Boot, and LangChain4j

Samples showing how to build Java applications powered by Generative AI and LLMs using the LangChain4j Spring Boot extension.

Pre-Requisites

• Java 17+
• Docker/Podman
• OpenAI API Key (optional)
• Ollama (optional)

Content

1. Chat Models

Project	Description
chat-models-ollama	Text generation with LLMs via Ollama.
chat-models-openai	Text generation with LLMs via OpenAI.

2. Prompts

Project	Description
prompts-basics-ollama	Prompting using simple text with LLMs via Ollama.
prompts-basics-openai	Prompting using simple text with LLMs via OpenAI.
prompts-messages-ollama	Prompting using structured messages and roles with LLMs via Ollama.
prompts-messages-openai	Prompting using structured messages and roles with LLMs via OpenAI.
prompts-templates-ollama	Prompting using templates with LLMs via Ollama.
prompts-templates-openai	Prompting using templates with LLMs via OpenAI.

3. Output Parsers

Project	Description
output-parsers-ollama	Parsing the LLM output as structured objects (Beans, Map, List) via Ollama.
output-parsers-openai	Parsing the LLM output as structured objects (Beans, Map, List) via Open AI.

4. Embedding Models

Project	Description
embedding-models-ollama	Vector transformation (embeddings) with LLMs via Ollama.
embedding-models-openai	Vector transformation (embeddings) with LLMs via OpenAI.

5. Document Readers

Coming soon

6. Document Transformers

Coming soon

7. Document Writers

Coming soon

8. Vector Stores

Coming soon

9. Tools

Coming soon

10. Image Models

Coming soon

References and Additional Resources

• LangChain4j