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Published 20 hours ago • verified publisher icon ThomasVitale
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Metadata

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

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

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Owner

verified publisher icon ThomasVitale

Metadata

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

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