Gists

Abstract

This article details the development of Smart Stowage Optimizer, a web-based digital twin for logistics that bridges the gap between physical safety and artificial intelligence. By integrating Gemini 3 Pro, the system solves the 3D Bin Packing Problem (3DBPP) using advanced spatial reasoning. Built with React 19 and Three.js, the application visualizes physics-aware load stability in real-time, offering a comparative analysis between traditional heuristic algorithms and modern generative AI agents.

Gists

Abstract

Gemini excels at text generation with RAG for large datasets, but smaller ones benefit from prompting or data upload. This report explores using Gemini 1.5 Flash/Pro with RAG on medium-sized, Google Spreadsheet-stored datasets for improved accuracy and effectiveness.

Introduction

Gemini’s text generation capabilities have seen significant advancements with the Retrieval-Augmented Generation (RAG). This approach excels for large datasets, where embedding data and querying the model leads to high-quality answers. However, for smaller datasets, directly including data in the prompt or an uploaded file can be more efficient. Ref

Gists

Abstract

This report proposes a novel learning method using Gemini to automate Q&A generation, addressing the challenges of manual Q&A creation. By integrating with Google tools, this approach aims to enhance learning efficiency, accessibility, and personalization while reducing costs.

Introduction

Mastering a new subject often demands a significant time commitment. A proven strategy for efficient learning is through question-and-answer (Q&A) practice. This method typically involves constructing a dataset of pertinent Q&A pairs and subsequently engaging in repeated practice until desired proficiency levels are achieved. While platforms such as Google Forms and Google Apps Script can streamline the Q&A creation and evaluation process, the manual generation of Q&A data remains a time-consuming and expensive endeavor. Minimizing the operational costs associated with scripting is crucial for long-term sustainability.

UnlockSmartInvoiceManagementWithGeminiAPI was updated to v1.0.3.

• v1.0.3 (August 3, 2024)

  1. On August 3, 2024, I upated GeminiWithFiles (https://github.com/tanaikech/GeminiWithFiles). In this version, PDF data can be processed with Gemini API without async/await. So, I updated UnlockSmartInvoiceManagementWithGeminiAPI.

You can see the detail information here https://github.com/tanaikech/UnlockSmartInvoiceManagementWithGeminiAPI

UnlockSmartInvoiceManagementWithGeminiAPI was updated to v1.0.2.

• v1.0.2 (July 23, 2024)

  1. On July 23, 2024, I noticed that PDF data could be directly parsed by Gemini API. It is considered that this is due to the update by the Google side. So, I updated setBlobs([blob], true) to setBlobs([blob], false) of the method parseInvoiceByGemini_. By this modification, the PDF blob is directly used with Gemini API. Ref

You can see the detail information here https://github.com/tanaikech/UnlockSmartInvoiceManagementWithGeminiAPI

UnlockSmartInvoiceManagementWithGeminiAPI was updated to v1.0.1.

• v1.0.1 (June 17, 2024)

  1. In order to easily customize the value of “jsonSchema” for generating content with Gemini API, I added it as a new sheet of “jsonSchema” sheet in the Spreadsheet. When you customize it, you can edit the cell “A1” of the “jsonSchema” sheet. By this, the script generates content with Gemini API using your customized JSON schema. The cell “A2” is the number of characters of “A1”.

You can see the detail information here https://github.com/tanaikech/UnlockSmartInvoiceManagementWithGeminiAPI

Gists

You can see the presentation of this application at https://www.youtube.com/watch?v=Dc2WPQkovZE.

Abstract

This report describes an invoice processing application built with Google Apps Script. It leverages Gemini, a large language model, to automatically parse invoices received as email attachments and automates the process using time-driven triggers.

Introduction

The emergence of large language models (LLMs) like ChatGPT and Gemini has significantly impacted various aspects of our daily lives. One such example is their ability to automate tasks previously requiring manual effort. In my case, Gemini has streamlined the processing of invoices I receive as email attachments in PDF format.

Gists

Abstract

Google Apps Script automates tasks (even offline) and builds web apps using spreadsheets as databases. This report presents a basic dining reservation system to illustrate key aspects of web app development with Apps Script, HTML, and Javascript.

Introduction

Google Apps Script is one of the powerful automation tools for achieving the automation process. When Google Apps Script can be used for the situation, even when users are away from their computers, automation can continue thanks to cloud computing. Also, Google Apps Script can manage Google Spreadsheet with Google Spreadsheet service and quickly deploy Web Apps with HTML and Javascript with minimal coding. Ref1 Ref2 When Google Spreadsheet is used as a database and the Web Apps are used as the user interface, various web applications can be created. In this report, in order to help understand the key aspects of building web applications with Google Apps Script, I would like to introduce a simple web application. Here, as a sample, the dining reservation system created by Google Apps Script, HTML, and Javascript is implemented as a web application.