This blog post shows a concrete example of transforming raw unstructured text into structured Java objects with Camel Quarkus and Quarkus LangChain4j. Introduction Following previous experiments about unstructured data extraction, some directions were given about how a large language model could be setup to transform unstructured data into its structured counterpart. In this blog post, we will see a ready to use example that could serve as a starting point to create your own Camel route performing data extraction.

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CAMELAI

The first law of software complexity says that “a well-designed system will degrade into a badly designed system over time”. This law can be ruthless for open source projects receiving hundreds of contributions every month. That’s why projects must refactor code, evaluate APIs, review tests, and modernize code to leverage the latest and greatest features from Java. Camel Test Support One area in Camel that has had little attention until recently was our test support code.

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CAMELTEST

Chunking is a crucial aspect of data processing that can significantly impact retrieval quality, query latency, costs, and even the accuracy of Large Language Model (LLM) outputs. In this blog post, we’ll explore what chunking is, its importance, and how the new Chunking DSL in Apache Camel 4.8.0 improves data processing workflows. The Problem with Traditional Chunking Approaches Before Camel 4.8.0, applications using Camel would have to implement custom chunking logic or rely on external libraries.

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CAMELAI