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

Apache Camel AI is a set of components that allow various AI-related technologies to be integrated with Camel. Nowadays, LLMs such as OpenAI ChatGPT and Meta Llama are gaining a lot of attention, and many frameworks and tools are exploring ways to utilise them. Camel AI also includes the LangChain4j component suite, and there are already blog posts about how you can utilise LLMs using LangChain4j in the Camel Blog:

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CAMELAI

Camel Quarkus 3.14.0 release

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RELEASESCAMEL QUARKUS