Dionext software development notes

AI. Java. Spring AI

https://www.youtube.com/watch?v=H_58SyQfl_U New Vector APIs coming to Java - Java 23 update

AI Model API Portable

Model API across AI providers for Chat, Text to Image, Audio Transcription, Text to Speech, and Embedding models. Both synchronous and stream API options are supported. With support for AI Models from OpenAI, Microsoft, Amazon, Google, Amazon Bedrock, Hugging Face and more https://docs.spring.io/spring-ai/reference/api/index.html

• OpenAI Chat Completion (streaming, multi-modality & function-calling support)

• Microsoft Azure Open AI Chat Completion (streaming & function-calling support)

• Ollama Chat Completion (streaming, multi-modality & function-calling support)

• Hugging Face Chat Completion (no streaming support)

• Google Vertex AI PaLM2 Chat Completion (no streaming support)

• Google Vertex AI Gemini Chat Completion (streaming, multi-modality & function-calling support)

• Amazon Bedrock

  • Cohere Chat Completion

  • Llama Chat Completion

  • Titan Chat Completion

  • Anthropic Chat Completion

  • Jurassic2 Chat Completion

• Mistral AI Chat Completion (streaming & function-calling support)

• Anthropic Chat Completion (streaming & function-calling support)

The project draws inspiration from notable Python projects, such as LangChain and LlamaIndex, but Spring AI is not a direct port of those projects. The project was founded with the belief that the next wave of Generative AI applications will not be only for Python developers but will be ubiquitous across many programming languages.
Spring AI provides the following features:

• Support for all major Model providers such as OpenAI, Microsoft, Amazon, Google, and Hugging Face.

• Supported Model types are Chat, Text to Image, Audio Transcription, Text to Speech, and more on the way.

• Portable API across AI providers for all models. Both synchronous and stream API options are supported. Dropping down to access model specific features is also supported.

• Mapping of AI Model output to POJOs.

• Support for all major Vector Database providers such as Apache Cassandra, Azure Vector Search, Chroma, Milvus, MongoDB Atlas, Neo4j, Oracle, PostgreSQL/PGVector, PineCone, Qdrant, Redis, and Weaviate.

• Portable API across Vector Store providers, including a novel SQL-like metadata filter API that is also portable.

• Function calling.

• Spring Boot Auto Configuration and Starters for AI Models and Vector Stores.

• ETL framework for Data Engineering.

https://docs.spring.io/spring-ai/reference/api/prompt.html
The primary roles are:

• System Role: Guides the AI's behavior and response style, setting parameters or rules for how the AI interprets and replies to the input. It's akin to providing instructions to the AI before initiating a conversation.

• User Role: Represents the user's input -- their questions, commands, or statements to the AI. This role is fundamental as it forms the basis of the AI's response.

• Assistant Role: The AI's response to the user's input. More than just an answer or reaction, it's crucial for maintaining the flow of the conversation. By tracking the AI's previous responses (its 'Assistant Role' messages), the system ensures coherent and contextually relevant interactions. The Assistant message may contain Function Tool Call request information as well. It's like a special feature in the AI, used when needed to perform specific functions such as calculations, fetching data, or other tasks beyond just talking.

• Tool/Function Role: The Too/Function Role focuses on returning additional information in response to Tool Call Aisstnat Messages.

https://spring.io/projects/spring-ai

https://docs.spring.io/spring-ai/reference/

https://docs.spring.io/spring-ai/reference/api/embeddings/ollama-embeddings.html Ollama - run AI models on your local machine

https://www.youtube.com/watch?v=QWKs0aOZaVQ&list=PLO66QfE8gWT1lyNltpE73ee8mVn6C4xN9 Spring AI Tutorials : Generative AI for Java Developers

https://www.youtube.com/watch?v=ACpLp2KXqgE Working with Prompts in Spring AI - Effectively Communicating with LLMs - Dan Vega

https://foojay.io/today/spring-ai-how-to-write-genai-applications-with-java/ (Neo4j Vector Database)

Getting started with (Retrieval Augmented Generation) RAG in Java & Spring AI https://www.youtube.com/watch?v=4-rG2qsTrAs

https://www.baeldung.com/spring-ai

https://www.youtube.com/watch?v=aNKDoiOUo9M Spring Tips: Spring AI D:\Projects\examples\ai\llm-rag-with-spring-ai (vector store example)

https://www.youtube.com/watch?v=yPu-WV_00Tk Spring Tips: Vector Databases with Spring AI https://www.youtube.com/watch?v=Q65-Zade25w

https://www.youtube.com/watch?v=QWgiOoB4OOU Spring into the AI Era: A Practical Exploration for Developers (Workshop) - базовый старый доклад

https://www.youtube.com/watch?v=jJ63tedBAzI Building a ChatGPT Clone in Java with HTMX, Spring Boot, and Spring AI провстое прокси приложение https://github.com/danvega/chatgpt-clone интересно своим интефейсом

https://www.youtube.com/watch?v=7K6YPRUtBkQ Generating Images with Spring AI

https://www.youtube.com/watch?v=qL9A21N-6J4 Unleashing AI in Java: A Guide to Semantic Kernel, LangChain4j, and Spring AI by Marcus Hellberg

https://www.youtube.com/watch?v=k3fSQpz2Esg Code your own dating bot with Spring Boot & React & AI https://github.com/koushikkothagal/tinder-ai-backend пример огранизации фейкового чат диалога , фронт на React

https://www.youtube.com/watch?v=0QVdJcxGf1M Generate Dynamic Websites using ChatGPT and Spring AI

https://www.youtube.com/watch?v=6Pgmr7xMjiY Java + RAG: Create an AI-Powered Financial Advisor using Spring AI

https://www.youtube.com/@DevMastersDb

https://www.youtube.com/watch?v=jClr5LtQFIQ&t=216s Spring AI RAG | Chat with your PDF Documents using Java and Spring Boot

https://dev.to/brunooliveira/basic-rag-app-with-spring-ai-docker-and-ollama-1i7j

    environment:
      - SPRING_DATASOURCE_URL=jdbc:postgresql://db:5432/ragdb
      - SPRING_DATASOURCE_USERNAME=postgres
      - SPRING_DATASOURCE_PASSWORD=password
      - SPRING_AI_OLLAMA_BASE_URL=http://ollama-llm:11434/
      - SPRING_AI_OLLAMA_CHAT_OPTIONS_MODEL=tinydolphin
      - SPRING_AI_OLLAMA_CHAT_OPTIONS_ALTERNATIVE_MODEL=tinyllama
      - SPRING_AI_OLLAMA_CHAT_OPTIONS_ALTERNATIVE_SECOND_MODEL=llama3.1
      - SPRING_AI_OLLAMA_EMBEDDING_OPTIONS_MODEL=mxbai-embed-large
      - SPRING_AI_VECTORSTORE_PGVECTOR_REMOVE_EXISTING_VECTOR_STORE_TABLE=true
      - SPRING_AI_VECTORSTORE_PGVECTOR_INDEX_TYPE=HNSW
      - SPRING_AI_VECTORSTORE_PGVECTOR_DISTANCE_TYPE=COSINE_DISTANCE
      - SPRING_AI_VECTORSTORE_PGVECTOR_DIMENSIONS=1024