In today's world anything almost everything related to literature can be achieved by LLMs. Be it summarization, abstraction, translation, transformation, etc. But not always is it possible to do those operations on extremely large content. Even with the large token output limits of newly launched advanced LLMs it is not always economically and technically feasible to perform such operations. To cater to such a problem this paper explores the idea of summarization of extensive contents by a chunk-based approach which is both efficient and economical. This approach also understands the drawback of loss of information while chunking and efficiently solves that issue. The usage of such a framewo... More >