Welcome to the official GitHub repository for the Spring AI Course. This course helps you build intelligent applications using the Spring AI framework and integrate powerful LLMs like OpenAI into your Spring Boot apps.
Below are some carefully curated reference links and tools used throughout the course. Bookmark this information for quick access during development and exploration.
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Spring AI Official Documentation
The core reference for understanding Spring AI modules, configuration, and supported AI providers. -
OpenAI Platform Docs
Learn how to use OpenAI's APIs including ChatGPT, GPT-4, embeddings, and more.
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Ollama
Run open-source large language models (LLMs) locally on your machine with simple commands. -
AWS Bedrock
Access foundation models from various providers via a fully managed AWS service. -
Docker Desktop
Essential for running local AI model runtimes and Docker Compose setups used in the course. -
Docker Model Runner
Use Docker’s official tool for running and managing AI models locally.
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Attention Is All You Need (Transformer Paper)
The seminal research paper that introduced the Transformer architecture behind modern LLMs. -
OpenAI Tokenizer Tool
Visualize how OpenAI tokenizes input prompts and estimate token usage.
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Qdrant Vector Database
An open-source vector store used in Retrieval-Augmented Generation (RAG) demos with Spring AI. -
Model Context Protocol (MCP)
A protocol for connecting AI clients and servers in a decoupled and extensible way.
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Prometheus
Monitoring and alerting toolkit for collecting Spring Boot and AI app metrics. -
Micrometer
Java metrics collection library used with Spring Boot to expose observability data. -
OpenTelemetry
Industry-standard framework for distributed tracing and telemetry data. -
Grafana
Visualization tool for creating dashboards from Prometheus and other data sources. -
Jaeger Tracing
Distributed tracing platform used to trace and monitor AI request flows.
📬 For questions or issues, raise a GitHub issue or connect with the course instructor
Happy Learning! 🚀