Open Source AI Project


Kindle GPT is a project similar to ChatPDF, designed to export reading notes from your Kindle.


The Kindle GPT project focuses on enhancing the way users interact with their reading notes taken on Kindle devices. It is akin to ChatPDF in its functionality, aiming to transform the process of managing and utilizing reading notes by allowing users to not only export these notes but also to search through them and engage in a conversational manner, akin to interacting with a chatbot.

At the core of Kindle GPT is the utilization of OpenAI’s Embeddings, specifically the text-embedding-ada-002 model. This model generates embeddings for the reading notes, which are essentially numerical representations of text that capture semantic meaning. By converting notes into embeddings, the project facilitates a more nuanced and efficient search capability beyond simple keyword matching. This means users can query their notes in natural language and find relevant information even if the exact words are not used in the notes.

The project stands out by opting for an in-memory search mechanism over the more common approach of using a vector database for storing and querying embeddings. To achieve this, the author has developed a custom cosine similarity function, referred to as cosSim, which measures the cosine of the angle between two vectors (in this case, embeddings) to determine their level of similarity. This function is central to the project’s search feature, allowing for the direct retrieval of the most relevant reading notes based on the semantic similarity of their embeddings to the query.

By leveraging OpenAI’s advanced embedding model and a custom in-memory search algorithm, Kindle GPT offers a novel solution for readers looking to maximize the value of their Kindle notes. This approach not only makes searching through vast amounts of text both faster and more accurate but also introduces an interactive, conversational dimension to the experience of revisiting and learning from one’s reading material.

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