Maximize Productivity: Integrate Google Docs with OpenAI

Table of Contents

• Introduction
• Extracting the Body of Text from a Google Document
• Feeding the Text into OpenAI with a Prompt
• Creating an End-to-End Working Example
• Creating a New Workflow
• Setting Up the Trigger for Google Drive
• Listening to Specific Folders for Changes
• Creating a New Google Document for Testing
• Retrieving the Document Content using Google Docs API
• Converting the Content into Text Format
• Using the Google Docs to Markdown Library
• Modifying the Workflow using Custom Node Code
• Adding the Google Docs to Markdown Path
• Passing the Converted Content to OpenAI Chat
• Summarizing the Text using OpenAI
• Troubleshooting: Filtering Google Doc Files Only
• Ensuring Permissions for Google Drive Files
• Conclusion

Extracting the Body of Text from a Google Document

Hey there, are You interested in learning how to extract the body of text from a Google Document and use it with OpenAI using Python? In this article, I'll provide you with a step-by-step guide on how to accomplish this. By the end, you'll be able to Create an end-to-end working example that extracts text from a Google Document, converts it into a format that OpenAI can Read, and feeds it into OpenAI's chat prompt for summarization. Let's get started!

Introduction

In today's digital age, extracting the body of text from a Google Document and using it with OpenAI has become a popular technique. Whether you're a content creator, researcher, or just curious, being able to automate the process of extracting and summarizing text can save you valuable time and effort. In this article, I'll guide you through the entire process, from setting up the workflow to retrieving the document content, converting it, and finally summarizing it using OpenAI. So grab a cup of coffee, sit back, and let's dive into the world of text extraction and summarization with Python.

Extracting the Body of Text from a Google Document

To begin with, we need to extract the body of text from a Google Document. This can be done using the Google Drive API and Python's libraries. By setting up a trigger for Google Drive and listening to specific folders for changes, we can automatically fetch the latest Google Document file. Once we have the file, we can use the Google Docs API to retrieve the document content. However, the content is not in a format that OpenAI can read. Therefore, we need to convert it into plain text using the Google Docs to Markdown library. This will enable us to pass the text into OpenAI's chat prompt for summarization. Sounds interesting, right? Let's get started by creating a new workflow.

Feeding the Text into OpenAI with a Prompt

Once we have extracted the body of text from the Google Document and converted it into a readable format, the next step is to feed this text into OpenAI using a prompt. OpenAI's chat prompt allows us to Interact with AI models, making it perfect for summarizing the text. By providing a prompt and the converted text, we can ask OpenAI to summarize the text into short bullet points. OpenAI will generate a response that includes the summarized version of the text. Exciting, isn't it? In the following sections, I'll guide you through the process of creating an end-to-end working example that automates this entire workflow.

Creating an End-to-End Working Example

In this section, I'll guide you through the process of creating an end-to-end working example that extracts the body of text from a Google Document and feeds it into OpenAI for summarization. We'll start by creating a new workflow in Pipe Dream, setting up the trigger for Google Drive, and listening to specific folders for changes. Then, we'll create a new Google Document and retrieve its content using the Google Docs API. After that, we'll convert the content into a readable format using the Google Docs to Markdown library. Finally, we'll pass the converted text into OpenAI's chat prompt and retrieve the summarized version of the text. Ready? Let's dive in!

Creating a New Workflow

To begin, let's create a brand new workflow in Pipe Dream. Name the workflow "Google Docs to OpenAI", and click on "Create Workflow" to start from scratch. We'll be building the workflow step by step, so don't worry if it seems overwhelming at first. Follow along, and you'll understand each part of the workflow.

Setting Up the Trigger for Google Drive

In order to fetch the Google Document files, we need to set up a trigger for the Google Drive app in Pipe Dream. To do this, click on the "Apps" option in the sidebar, search for "Google Drive", and select the Google Drive app. From there, choose the "New Files Instant" trigger, which will listen for new files created in the connected Google Drive account. If you want to listen to specific folders for changes, you can configure that as well. For this example, we'll listen to all files in the same drive.

Listening to Specific Folders for Changes

If you have a noisy Google Drive with many files, you may want to listen only to specific folders for changes. In that case, you can configure the trigger to listen to changes in specific folders. This allows you to filter out unnecessary files and focus only on the Relevant ones. However, for this example, we'll keep it simple and listen to all files in the same drive.

Creating a New Google Document for Testing

Now that we have set up the trigger for Google Drive, let's create a new Google Document. This document will serve as our test document for extracting the body of text. Go ahead and create the document, and make sure to paste some sample text into it. For this example, we'll use the recently released CPI (Consumer Price Index) summary from the Federal Reserve. Once the document is created, give it a title, such as "Consumer Price Index Summary".

Retrieving the Document Content using Google Docs API

With the test document in place, it's time to retrieve its content using the Google Docs API. In the workflow, add a new step and select the "Google Docs" app from the app selector. From the list of available actions, choose "Get Document". This action will allow us to fetch the content of a specific document. Select your account and enter the document ID. You can find the document ID by looking at the URL of the Google Document. Once you have entered the document ID, click on "Test" to retrieve the document content and test the Current step.

Converting the Content into Text Format

The content retrieved from the Google Docs API is not in a readable text format. It includes various markup and formatting information. To convert the content into plain text, we'll use the Google Docs to Markdown library. This library provides a Helper function called "Google docs to markdown" that converts the Google Docs API response into plain text in the Markdown format. Add a new step in the workflow and select the "Run Custom Node Code" action. Paste the path to the module from npm that imports the Google docs to markdown library. Modify the step to include the API response from the Google Docs app and pass it to the Google docs to markdown function. This will convert the content into a readable format that can be passed to the next step.

Using the Google Docs to Markdown Library

The Google Docs to Markdown library is a powerful tool that allows us to convert the content of a Google Document into plain text in the Markdown format. It handles complex formatting and retains the structure of the document. By using this library, we can ensure that the text is in a format that OpenAI can read and process effectively. The library works by parsing the Google Docs API response and converting the content into plain text while preserving the document structure. This makes it easy for us to extract the body of text and use it for further processing.

Modifying the Workflow using Custom Node Code

With the Google Docs to Markdown library in place, we need to modify the workflow to include the custom node code that converts the content. In the "Run Custom Node Code" step, paste the path to the module that imports the Google docs to markdown library. This will allow us to use the library's functions in our workflow. By passing the API response from the Google Docs step to the Google docs to markdown function, we can convert the content into plain text in the Markdown format. This ensures that the text is readable and can be processed by OpenAI.

Adding the Google Docs to Markdown Path

To ensure that the converted content is passed to the next step in the workflow, we need to add the path to the converted text in the "Open AI Chat" step. As you can see, the "Open AI Chat" step requires a user message and the document content. By clicking on the curly brackets icon, you can select the path to the converted text and include it in the user message. This will ensure that the converted content is passed to OpenAI for summarization.