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integrationGoogle Drive node
integrationGoogle Sheets node

Google Drive and Google Sheets integration

Save yourself the work of writing custom integrations for Google Drive and Google Sheets and use n8n instead. Build adaptable and scalable Data & Storage, and Productivity workflows that work with your technology stack. All within a building experience you will love.

How to connect Google Drive and Google Sheets

  • Step 1: Create a new workflow
  • Step 2: Add and configure nodes
  • Step 3: Connect
  • Step 4: Customize and extend your integration
  • Step 5: Test and activate your workflow

Step 1: Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

Google Drive and Google Sheets integration: Create a new workflow and add the first step

Step 2: Add and configure Google Drive and Google Sheets nodes

You can find Google Drive and Google Sheets in the nodes panel. Drag them onto your workflow canvas, selecting their actions. Click each node, choose a credential, and authenticate to grant n8n access. Configure Google Drive and Google Sheets nodes one by one: input data on the left, parameters in the middle, and output data on the right.

Google Drive and Google Sheets integration: Add and configure Google Drive and Google Sheets nodes

Step 3: Connect Google Drive and Google Sheets

A connection establishes a link between Google Drive and Google Sheets (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.

Google Drive and Google Sheets integration: Connect Google Drive and Google Sheets

Step 4: Customize and extend your Google Drive and Google Sheets integration

Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect Google Drive and Google Sheets with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

Google Drive and Google Sheets integration: Customize and extend your Google Drive and Google Sheets integration

Step 5: Test and activate your Google Drive and Google Sheets workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Google Drive to Google Sheets or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.

Google Drive and Google Sheets integration: Test and activate your Google Drive and Google Sheets workflow

AI Automated HR Workflow for CV Analysis and Candidate Evaluation

How it Works

This workflow automates the process of handling job applications by extracting relevant information from submitted CVs, analyzing the candidate's qualifications against a predefined profile, and storing the results in a Google Sheet. Here’s how it operates:

Data Collection and Extraction:
The workflow begins with a form submission (On form submission node), which triggers the extraction of data from the uploaded CV file using the Extract from File node.
Two informationExtractor nodes (Qualifications and Personal Data) are used to parse specific details such as educational background, work history, skills, city, birthdate, and telephone number from the text content of the CV.

Processing and Evaluation:
A Merge node combines the extracted personal and qualification data into a single output.
This merged data is then passed through a Summarization Chain that generates a concise summary of the candidate’s profile.
An HR Expert chain evaluates the candidate against a desired profile (Profile Wanted), assigning a score and providing considerations for hiring.
Finally, all collected and processed data including the evaluation results are appended to a Google Sheets document via the Google Sheets node for further review or reporting purposes [[9]].

Set Up Steps

To replicate this workflow within your own n8n environment, follow these steps:

Configuration:
Begin by setting up an n8n instance if you haven't already; you can sign up directly on their website or self-host the application.
Import the provided JSON configuration into your n8n workspace. Ensure that all necessary credentials (e.g., Google Drive, Google Sheets, OpenAI API keys) are correctly configured under the Credentials section since some nodes require external service integrations like Google APIs and OpenAI for language processing tasks.

Customization:
Adjust the parameters of each node according to your specific requirements. For example, modify the fields in the formTrigger node to match what kind of information you wish to collect from applicants.
Customize the prompts given to AI models in nodes like Qualifications, Summarization Chain, and HR Expert so they align with the type of analyses you want performed on the candidates' profiles.
Update the destination settings in the Google Sheets node to point towards your own spreadsheet where you would like the final outputs recorded.

Nodes used in this workflow

Popular Google Drive and Google Sheets workflows

+2

AI Automated HR Workflow for CV Analysis and Candidate Evaluation

How it Works This workflow automates the process of handling job applications by extracting relevant information from submitted CVs, analyzing the candidate's qualifications against a predefined profile, and storing the results in a Google Sheet. Here’s how it operates: Data Collection and Extraction: The workflow begins with a form submission (On form submission node), which triggers the extraction of data from the uploaded CV file using the Extract from File node. Two informationExtractor nodes (Qualifications and Personal Data) are used to parse specific details such as educational background, work history, skills, city, birthdate, and telephone number from the text content of the CV. Processing and Evaluation: A Merge node combines the extracted personal and qualification data into a single output. This merged data is then passed through a Summarization Chain that generates a concise summary of the candidate’s profile. An HR Expert chain evaluates the candidate against a desired profile (Profile Wanted), assigning a score and providing considerations for hiring. Finally, all collected and processed data including the evaluation results are appended to a Google Sheets document via the Google Sheets node for further review or reporting purposes [[9]]. Set Up Steps To replicate this workflow within your own n8n environment, follow these steps: Configuration: Begin by setting up an n8n instance if you haven't already; you can sign up directly on their website or self-host the application. Import the provided JSON configuration into your n8n workspace. Ensure that all necessary credentials (e.g., Google Drive, Google Sheets, OpenAI API keys) are correctly configured under the Credentials section since some nodes require external service integrations like Google APIs and OpenAI for language processing tasks. Customization: Adjust the parameters of each node according to your specific requirements. For example, modify the fields in the formTrigger node to match what kind of information you wish to collect from applicants. Customize the prompts given to AI models in nodes like Qualifications, Summarization Chain, and HR Expert so they align with the type of analyses you want performed on the candidates' profiles. Update the destination settings in the Google Sheets node to point towards your own spreadsheet where you would like the final outputs recorded.

AI Virtual TryOn automated generation 🤖🧠 for WooCommerce clothing catalog 👔

This AI Agent is designed to streamline the process of creating realistic images of clothing products worn by models, eliminating the need for expensive photoshoots. The primary goal is to automate the generation of virtual try-on images for an eCommerce store selling clothing, using advanced image processing technologies. Example of results How It Works Triggering the Workflow: The workflow can be triggered manually using the When clicking ‘Test workflow’ node or automatically via the Schedule Trigger node, which runs the workflow at regular intervals (e.g., every 5 minutes). Data Retrieval: The Get new product node retrieves data from a Google Sheets document containing the URLs of the model image, the clothing product image, and the WooCommerce product ID. The document also includes a column for the resulting virtual try-on image URL, which is initially empty. Setting Up the Request: The Set data node prepares the data for the AI request by assigning the model image URL and the product image URL to variables. AI Image Generation: The Create Image node sends a request to API to generate a virtual try-on image. The request includes the URLs of the model and the clothing product. When you register for the API service you will get 1$ for free. For continuous work add API credits to your account. Image Retrieval: The Get Url image node retrieves the URL of the generated virtual try-on image. The Get File image node downloads the generated image from the provided URL. Image Storage: The Upload Image node uploads the generated image to a specified Google Drive folder for storage. Updating Google Sheets: The Update result node updates the Google Sheets document with the URL of the generated virtual try-on image. Updating WooCommerce: The Update product node updates the corresponding product in WooCommerce by adding the generated virtual try-on image to the product's image gallery. Functionality This AI Agent is designed to streamline the process of creating realistic images of clothing products worn by models, eliminating the need for expensive photoshoots. The primary goal is to automate the generation of virtual try-on images for an eCommerce store selling clothing, using advanced image processing technologies. By offering realistic images of clothing items worn by models, this automation process saves time and resources, making product catalog management more efficient. This approach not only enhances the competitiveness of the eCommerce store but also provides greater flexibility in creating high-quality visual content adaptable to various digital marketing campaigns. Key Features Automated Virtual Try-On**: Generates realistic images of models wearing clothing items using AI. Google Sheets Integration**: Retrieves and updates data in Google Sheets for seamless data management. Image Storage**: Uploads generated images to Google Drive for easy access and archiving. WooCommerce Integration**: Updates product pages with virtual try-on images, enhancing the shopping experience. Scheduled Automation**: Can be triggered manually or run at regular intervals for continuous processing. This workflow is ideal for eCommerce businesses looking to enhance their product catalogs with high-quality, realistic images without the need for costly photoshoots. It leverages AI to provide a cost-effective and efficient solution for virtual try-on image generation.
+6

AI-Powered RAG Workflow For Stock Earnings Report Analysis

This n8n workflow creates a financial analysis tool that generates reports on a company's quarterly earnings using the capabilities of OpenAI GPT-4o-mini, Google's Gemini AI and Pinecone's vector search. By analyzing PDFs of any company's earnings reports from their Investor Relations page, this workflow can answer complex financial questions and automatically compile findings into a structured Google Doc. How it works: Data loading and indexing Fetches links to PDF earnings document from a Google Sheet containing a list of file links. Downloads the PDFs from Google Drive. Parses the PDFs, splits the text into chunks, and generates embeddings using the Embeddings Google AI node (text-embedding-004 model). Stores the embeddings and corresponding text chunks in a Pinecone vector database for semantic search. Report generation with AI agent Utilizes an AI Agent node with a specifically crafted system prompt. The agent orchestrates the entire process. The agent uses a Vector Store Tool to access and retrieve information from the Pinecone database. Report delivery Saves the generated report as a Google Doc in a specified Google Drive location. Set up steps Google Cloud Project & Vertex AI API: Create a Google Cloud project. Enable the Vertex AI API for your project. Google AI API key: Obtain a Google AI API key from Google AI Studio. Pinecone account and API key: Create a free account on the Pinecone website. Obtain your API key from your Pinecone dashboard. Create an index named company-earnings in your Pinecone project. Google Drive - download and save financial documents: Go to a company you want to analize and download their quarterly earnings PDFs Save the PDFs in Google Drive Create a Google Sheet that stores a list of file URLs pointing to the PDFs you downloaded and saved to Google Drive Configure credentials in your n8n environment for: Google Sheets OAuth2 Google Drive OAuth2 Google Docs OAuth2 Google Gemini(PaLM) Api (using your Google AI API key) Pinecone API (using your Pinecone API key) Import and configure the workflow: Import this workflow into your n8n instance. Update the List Of Files To Load (Google Sheets) node to point to your Google Sheet. Update the Download File From Google Drive to point to the column where the file URLs are Update the Save Report to Google Docs node to point to your Google Doc where you want the report saved.

Summarize the New Documents from Google Drive and Save Summary in Google Sheet

This workflow is created by AI developers at WeblineIndia. It streamlines the process of managing content by automatically identifying and fetching the most recently added Google Doc file from your Google Drive. It extracts the content of the document for processing and leverages an AI model to generate a concise and meaningful summary of the extracted text. The summarized content is then stored in a designated Google Sheet, alongside relevant details like the document name and the date it was added, providing an organized and easily accessible reference for future use. This automation simplifies document handling, enhances productivity, and ensures seamless data management. Steps : Fetch the Most Recent Document from Google Drive Action:** Use the Google Drive Node. Details:** List files, filter by date to fetch the most recently added .doc file, and retrieve its file ID and metadata. Extract Content from the Document Action:** Use the Google Docs Node. Details:** Set the operation to "Get Content," pass the file ID, and extract the document's text content. Summarize the Document Using an AI Model Action:** Use an AI Model Node (e.g., OpenAI, ChatGPT). Details:** Provide the extracted text to the AI model, use a prompt to generate a summary, and capture the result. Store the Summarized Content in Google Sheets Action:** Use the Google Sheets Node. Details:** Append a new row to the target sheet with details such as the original document name, summary, and date added. About WeblineIndia WeblineIndia specializes in delivering innovative and custom AI solutions to simplify and automate business processes. If you need any help, please reach out to us.
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API Schema Extractor

This workflow automates the process of discovering and extracting APIs from various services, followed by generating custom schemas. It works in three distinct stages: research, extraction, and schema generation, with each stage tracking progress in a Google Sheet. 🙏 Jim Le deserves major kudos for helping to build this sophisticated three-stage workflow that cleverly automates API documentation processing using a smart combination of web scraping, vector search, and LLM technologies. How it works Stage 1 - Research: Fetches pending services from a Google Sheet Uses Google search to find API documentation Employs Apify for web scraping to filter relevant pages Stores webpage contents and metadata in Qdrant (vector database) Updates progress status in Google Sheet (pending, ok, or error) Stage 2 - Extraction: Processes services that completed research successfully Queries vector store to identify products and offerings Further queries for relevant API documentation Uses Gemini (LLM) to extract API operations Records extracted operations in Google Sheet Updates progress status (pending, ok, or error) Stage 3 - Generation: Takes services with successful extraction Retrieves all API operations from the database Combines and groups operations into a custom schema Uploads final schema to Google Drive Updates final status in sheet with file location Ideal for: Development teams needing to catalog multiple APIs API documentation initiatives Creating standardized API schema collections Automating API discovery and documentation Accounts required: Google account (for Sheets and Drive access) Apify account (for web scraping) Qdrant database Gemini API access Set up instructions: Prepare your Google Sheets document with the services information. Here's an example of a Google Sheet – you can copy it and change or remove the values under the columns. Also, make sure to update Google Sheets nodes with the correct Google Sheet ID. Configure Google Sheets OAuth2 credentials, required third-party services (Apify, Qdrant) and Gemini. Ensure proper permissions for Google Drive access.

Create Content from Form Inputs and Save it to Google Drive using AI

AI Content Generator Workflow Introduction This workflow automates the process of creating high-quality articles using AI, organizing them in Google Drive, and tracking their progress in Google Sheets. It's perfect for marketers, bloggers, and businesses looking to streamline content creation. With minimal setup, you can have a fully operational system to generate, save, and manage your articles in one cohesive workflow. How It Works Collect Inputs: Users fill out a form with details like article title, keywords, and instructions. Generate Content: AI creates an outline and writes the article based on user inputs. Organize Files: Saves the outline and final article in Google Drive for easy access. Track Progress: Updates Google Sheets with links to the generated content for tracking. Set Up Steps Time Required**: Approximately 15–20 minutes to connect all integrations and test the workflow. Steps**: Connect Google Drive and Google Sheets: Authorize access to store files and update the spreadsheet. Set Up OpenAI Integration: Add your OpenAI API key for generating the outline and article content. Customize the Form: Modify the form fields to match the details you want to collect for each article. Test the Workflow: Run the workflow with sample inputs to ensure everything works smoothly. This workflow not only simplifies the process of article creation but also sets a foundation for expanding into additional automations, like posting to social media platforms.

Build your own Google Drive and Google Sheets integration

Create custom Google Drive and Google Sheets workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

Google Drive supported actions

Copy
Create a copy of an existing file
Create From Text
Create a file from a provided text
Delete
Permanently delete a file
Download
Download a file
Move
Move a file to another folder
Share
Add sharing permissions to a file
Update
Update a file
Upload
Upload an existing file to Google Drive
Search
Search or list files and folders
Create
Create a folder
Delete
Permanently delete a folder
Share
Add sharing permissions to a folder
Create
Create a shared drive
Delete
Permanently delete a shared drive
Get
Get a shared drive
Get Many
Get the list of shared drives
Update
Update a shared drive

Google Sheets supported actions

Create
Create a spreadsheet
Delete
Delete a spreadsheet
Append or Update Row
Append a new row or update an existing one (upsert)
Append Row
Create a new row in a sheet
Clear
Delete all the contents or a part of a sheet
Create
Create a new sheet
Delete
Permanently delete a sheet
Delete Rows or Columns
Delete columns or rows from a sheet
Get Row(s)
Retrieve one or more rows from a sheet
Update Row
Update an existing row in a sheet

FAQs

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