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Add the Spring AI Bill of Materials (BOM) and the starter for your preferred LLM provider (OpenAI in this example) to your pom.xml : spring ai in action pdf github
Let's build a practical implementation showcasing dynamic prompts, structured JSON output, and streaming data. Implement Structure Output with Beans
Spring AI provides an ETL (Extract, Transform, Load) framework for processing private files like PDFs. This public link is valid for 7 days
The "Spring AI in Action" ecosystem is growing daily. By combining conceptual PDF guides with practical, runnable GitHub repositories, you can rapidly move from basic text generation to complex, vector-backed enterprise AI agents. Stop translating your logic to Python—embrace native Java AI architecture today.
Which or model ecosystem do you plan to use? (OpenAI, Ollama, Anthropic, Azure, etc.) Can’t copy the link right now
If you are eager to dive deeper, I can provide more specific architectural blueprints.
If you are looking for ready-to-run repositories, complete code architectures, or community-compiled reference manuals, searching GitHub with target keywords will yield the best results:
Function calling allows LLMs to execute real-time Java code when they need current information (like checking weather, fetching current order statuses, or running calculations). Defining the Tool as a Java Function Bean