#LongContextLLMs

[bharatpatel1061]

Context Windows and Chunking: Managing Long Inputs for Agents

Agents powered by language models often face input size limits. Context windows—how much input the model can “see” at once—restrict long conversations or documents. This is where chunking and memory strategies come in.

Solutions include:

Recursive summarization

Context window rolling (sliding buffers)

External memory like vector stores

Managing long contexts is essential in legal, research, and technical workflows. Learn how modern AI agents optimize context use for long-form tasks.

Preprocess large inputs into semantically coherent chunks—it improves accuracy and avoids hallucinations.