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Enterprise Java
Intelligent Document Processing with Apache Camel, Docling & LangChain4j
Enterprise applications often need to process large numbers of documents such as PDFs, invoices, manuals, reports, and policy documents. Extracting…
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Enterprise Java
LLM Tool Call Reasoning with Embabel AI
Large language models become significantly more useful when they can interact with external tools instead of only generating text. A…
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Enterprise Java
LLM-as-a-Judge with Spring AI Recursive Advisors
Large Language Models (LLMs) are increasingly used not only to generate content, but also to evaluate the output produced by…
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Enterprise Java
Introduction to Apache Causeway
Building an enterprise application often involves implementing the same infrastructure repeatedly: domain objects, user interfaces, validation, persistence, navigation, and business…
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Enterprise Java
LLM Integration: Apache Camel & OpenAI Component
Large Language Models (LLMs) are increasingly becoming part of enterprise applications. However, integrating an LLM into an existing application is…
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Enterprise Java
Spring AI with Local LLMs Using LM Studio
Large Language Models (LLMs) are commonly accessed through cloud APIs provided by services such as OpenAI, Anthropic, or Google Gemini.…
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Enterprise Java
Access Request and Response Body in HandlerInterceptor
In a Spring Boot application, we sometimes need to inspect or log the HTTP request body and response body. This…
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Core Java
Diagrams from Java
Understanding the structure of a Java application becomes more challenging as the codebase grows. Generating diagrams from source code helps…
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Enterprise Java
Tracking Application Startup in Spring
Application startup performance is important for modern Spring applications. A slow startup can increase deployment time, delay container readiness, and…
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