Gists

Abstract

A new library, MimeTypeApp, simplifies using Gmail messages and attachments with the Gemini API for tasks like text analysis. It converts unsupported formats for seamless integration with Google Apps Script and Gemini.

Introduction

Recently, I published MimeTypeApp, a Google Apps Script library that simplifies parsing Gmail messages, including attachments, for use with the Gemini API. Ref This library addresses a key challenge: Gmail attachments come in various MIME types, while the Gemini API currently only accepts a limited set for processing. MimeTypeApp bridges this gap by providing functions to convert unsupported MIME types to formats compatible with Gemini. With MimeTypeApp, you can streamline your workflows that involve parsing Gmail messages and their attachments for tasks like text extraction, summarization, or sentiment analysis using the Gemini API. This report introduces a sample script that demonstrates how to leverage MimeTypeApp to achieve this functionality. By leveraging Google Apps Script’s integration capabilities, MimeTypeApp allows you to create powerful applications that seamlessly connect Gmail, Spreadsheets (for storing results or extracted data), and the Gemini API.

Gists

Abstract

This is a Google Apps Script library for converting files from various MIME types to a specified target MIME type. The library accepts both file IDs and blobs as input values.

Introduction

Recently, I encountered a scenario where I needed to convert files of various MIME types to a specific target MIME type. While converting files with known source MIME types is relatively straightforward, the process becomes more complex when the source MIME type is unknown. To simplify this task, I developed a Google Apps Script solution that can effectively convert files of diverse MIME types to a desired target MIME type. The script can accept both file IDs and blobs as input values.

GeminiWithFiles was updated to v2.0.3

• v2.0.3 (November 19, 2024)

  1. I modified the specification of setFileIdsOrUrlsWithResumableUpload. From v2.0.3, when you use this method, please include propertiesService: PropertiesService.getScriptProperties() into the initial object as follows. Because, when PropertiesService.getScriptProperties() is used in the library, the values are put into the library. When I created Ref and Ref, I supposed that the script is used by copying and pasting instead of the library. So, I included PropertiesService.getScriptProperties() in the script. But I noticed that when this is used with GeminiWithFiles, each user is required to use PropertiesService.getScriptProperties(). So, I modified this.
  2. As an additional option, when you want to upload the data with the resumable upload as a new upload, please set resumableUploadAsNewUpload: true. Ref By this, the property is cleared and the upload is run.

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

Gists

Description

Recently, I reported on a workaround for effectively working with Google Sheets tables using Google Apps Script: Ref. This approach addressed limitations in directly retrieving table data and ranges within Apps Script. In this follow-up report, I’m excited to provide a sample script that leverages this workaround to export your valuable Google Sheets tables directly as PDF files. This functionality empowers you to easily share and distribute your data in a clear and universally accessible format.

Gists

Abstract

Google Sheets’ new Tables feature enhances data organization but lacks direct management via Apps Script. This report proposes a workaround solution using Apps Script until native support arrives.

Introduction

Google Sheets recently introduced a new feature called Tables. Ref Tables offer a powerful way to organize and manage your data by transforming unformatted ranges into structured datasets with automatic headers, filtering options, and data validation capabilities. This not only improves the readability and maintainability of your spreadsheets but also allows for seamless integration with existing Google Sheets functions.

Gists

Abstract

Google Apps Script offers Document service for basic document tasks and Google Docs API for advanced control, requiring more technical expertise. This report bridges the gap with sample scripts to unlock the API’s potential.

Introduction

Google Apps Script provides two powerful tools for managing Google Documents: the Document service (DocumentApp) and the Google Docs API. Ref, Ref While the Document service offers a user-friendly interface for common document manipulation tasks within Apps Script, it has limitations. The Google Docs API, on the other hand, grants finer-grained control over document elements and functionalities not readily available through the Document service.

Gists

Abstract

This report showcases a practical application of Google Apps Script, demonstrating how new JavaScript methods can be used to create a script that automatically transfers selected rows between sheets in a Google Sheet.

Introduction

JavaScript, a fundamental pillar of contemporary web development, has experienced a significant rise in popularity due to its versatility and widespread adoption. As JavaScript’s influence has expanded, so too has Google Apps Script, a cloud-based scripting language constructed on the V8 JavaScript engine. This evolution has led to the introduction of novel methods and features, thereby expanding the capabilities of developers working within the Google Workspace ecosystem.

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 research explores “pseudo function calling” in Gemini API using prompt engineering with JSON schema, bypassing model dependency limitations.

Introduction

Large Language Models (LLMs) like Gemini and ChatGPT offer powerful functionalities, but their capabilities can be further extended through function calling. This feature allows the LLM to execute pre-defined functions with arguments generated based on the user’s prompt. This unlocks a wide range of applications, as demonstrated in these resources (see References).

GeminiWithFiles was updated to v2.0.2

• v2.0.2 (September 26, 2024)

  1. As the option for generationConfig, the properties response_schema and temperature were added.

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