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This workflow reads PDF textual content and sends the text to OpenAI. Attachments of interest will then be uploaded to a specified Google Drive folder. For example, you may wish to send invoices received from an email to an inbox folder in Google Drive for later processing. This workflow has been designed to easily change the search term to match your needs. See the workflow for more details. Prerequisites OpenAI credentials. Google credentials. How it works Triggers off on the On email received node. Iterates over the attachments in the email. Uses the OpenAI node to filter out the attachments that do not match the search term set in the Configure node. You could match on various PDF files (i.e. invoice, receipt, or contract). If the PDF attachment matches the search term, the workflow uses the Google Drive node to upload the PDF attachment to a specific Google Drive folder.

The workflow first populates a Pinecone index with vectors from a Bitcoin whitepaper. Then, it waits for a manual chat message. When received, the chat message is turned into a vector and compared to the vectors in Pinecone. The most similar vectors are retrieved and passed to OpenAI for generating a chat response. Note that to use this template, you need to be on n8n version 1.19.4 or later.

This workflow includes advanced features like text summarization and tokenization, it's ideal for automating document processing tasks that require parsing and summarizing text data from Google Drive. To use this template, you need to be on n8n version 1.19.4 or later.

This N8N workflow automates the process of sharing files from Google Drive. It includes OAuth2 authentication, batch processing, public link generation, and access status modification for efficient file handling. Suitable for users seeking to streamline their Google Drive file sharing process. sutiable for bulk actions, tested on 4.2K files folder working like charm. How It Works Initialize Workflow: The process begins with a Manual Trigger, allowing the user to start the workflow at their convenience. Folder ID Specification: A 'Set Folder ID' node where the user can enter the desired Google Drive Folder ID. List Files from Google Drive: The 'Google Drive' node lists all files within the specified folder using OAuth2 authentication. Batch Processing: The 'Loop Over Items' node processes the files in batches for efficiency. Generate Public Links: The 'Generate Download Links' node creates downloadable links for each file. Change File Access: The 'Change Status' node alters the file status to make them publicly accessible. Merge and Output: A 'Merge' node consolidates the data, preparing it for further actions or output. Set Up Steps Estimated Time**: The setup should take approximately 10-15 minutes. Initial Setup**: You'll need to provide OAuth2 credentials for Google Drive and specify a folder ID. Customization**: Adjust the batch size and file access permissions according to your needs. Detailed Descriptions**: For specific configuration details, refer to the sticky notes within the workflow. Example Item output { "link": "https://drive.google.com/u/3/uc?id=1hojqPfXchNTY8YRTNkxSo-8txK9re-V4&export=download&confirm=t&authuser=0", "name": "firefox_rNjA0ybKu7.png", "kind": "drive#permission", "id": "anyoneWithLink", "type": "anyone", "role": "reader", "allowFileDiscovery": false } You can store the output data with any data store node you want, for example save them into Excel Sheet or Airtable etc... Keywords: n8n workflow, Google Drive integration, file sharing automation, batch file processing, public link generation, OAuth2 authentication, workflow automation

Effortlessly optimize your workflow by automatically save all files you are receiving on Telegram to a Google Drive Folder. How it works Retrieve a message sent to your Telegram Bot containing a file Upload the file to your Google Drive Folder Set up Steps Create a Telegram Account and a Telegram Bot and connect your Telegram Bot to n8n by following the official n8n instructions Create a Google Drive Folder Connect your Google Drive with n8n following the official n8n instructions Set the right folder in the Google Drive node Use case examples Backup and Recovery Cross-Platform Access File Organization and Management File Collaboration and Sharing Storage Space Management

Who is this template for? This template is for everyone who has to take notes during a call: Talent Acquisition Managers / Talent Acquisition Specialists / Recruiters HR professionals Sales teams, customer success teams Product teams / User Experience Designers / anyone conducting user research interviews Use case This workflow allows specific events created on Google Calendar (or any other meeting scheduling tool like Calendly) to trigger the duplication and renaming of a specific template document. Example: For each new screening call that is scheduled in your calendar, you want to create a draft of your screening interview template for the role, titled "{Name of the candidate} | {Date of the interview}", and located in your Google Drive in a specific folder This workflow could then be extended to copy the link to the file on a Notion database that is shared with the team (check "To go further" section). This workflow ensures that if you're jumping from calls to calls, you're already set up to take notes, and every document is tidied up and sorted in a structured way! How it works The workflow starts when a new event is created in Google Calendar The Filter node then selects a specific type of events, depending on a chosen pattern (title includes a specific term, organizer is X, attendees include Y, etc.) The workflow then searches for a specific folder in your Google Drive, where the file you want to duplicate is located The workflow then searches for the specific file you want to duplicate The last step allows to duplicate and rename the file with variables from your Google Calendar event Set up Set up credentials for Google Calendar, Google Drive, and Google File. You'll need a Google Workspace account. Set up the Filter node with the pattern you want to look for to retreive specific events in your calendar Set up the Google Drive you want to search in Set up the Google File you want to duplicate Set up variable at the last step to rename your duplicated file however you want it, or add a description To go further Here's a few idea to enhance this workflow depending on your specific needs: Instead of a filter, separate your flow depending on your use case (ex: you have want to fetch different templates depending on the type of call it'll be). Switch Google Calendar for another trigger (Calendly, Hubspot..) 10 minutes before the event, send the duplicate Google File to the meeting organizer through Slack The day after the event, if the event hasn't been cancelled, add the link to the Google File to your ATS, Hubspot, etc.

This workflow allows you to ask questions about a PDF document. The answers are provided by an AI model of your choice, and the answer includes a citation pointing to the information it used. You can use n8n’s built-in chat interface to ask the questions, or you could customise this workflow to use another one (e.g. Slack, Teams, etc.) Example The workflow is set up with the Bitcoin whitepaper. So you could ask things like: Question: “Which email provider does the creator of Bitcoin use?“ Answer: “GMX [Bitcoin whitepaper.pdf, lines 1-35]” Requirements A Pinecone account (they have a free tier at the time of writing that is easily enough for this workflow) Access to a large language model (e.g. an OpenAI account) Customizing this workflow The workflow only reads in one document, but you could customise it to read in all the documents in a folder (or more). The workflow is set up to use GPT 3.5, but you could swap that out for any other model (including self-hosted ones).

Who is this for? This workflow template is perfect for content creators, researchers, students, or anyone who regularly works with audio files and needs to transcribe and summarize them for easy reference and organization. What problem does this workflow solve? Transcribing audio files and summarizing their content can be time-consuming and tedious when done manually. This workflow automates the process, saving users valuable time and effort while ensuring accurate transcriptions and concise summaries. What this workflow does This template automates the following steps: Monitors a specified Google Drive folder for new audio files Sends the audio file to OpenAI's Whisper API for transcription Passes the transcribed text to GPT-4 for summarization Creates a new page in Notion with the summary Setup To set up this workflow: Connect your Google Drive, OpenAI, and Notion accounts to n8n Configure the Google Drive node with the folder you want to monitor for new audio files Set up the OpenAI node with your API key and desired parameters for Whisper and GPT-4 Specify the Notion database where you want the summaries to be stored How to customize this workflow Adjust the Google Drive folder being monitored Modify the OpenAI node parameters to fine-tune the transcription and summarization process Change the Notion database or page properties to match your preferred structure With this AI-powered workflow, you can effortlessly transcribe audio files, generate concise summaries, and store them in a structured manner within Notion. Streamline your audio content processing and organization with this automated template.

This workflow will translate all your PDF documents from specified Google Drive folder to the desired language. Translated files will be automatically uploaded to the original folder. Required accounts 1️⃣ Google Drive account 2️⃣ DeepL developer account and API key How to setup? 1️⃣ Setup your google drive folder url, target and source language in the configuration node 2️⃣ Connect your Google Drive account with all Google Drive nodes 3️⃣ Setup HTTP header credentials that should be used for HTTP nodes in the template (replace yourAuthKey with your DeepL API key) 4️⃣ Set your DeepL header credentials in all HTTP nodes

How it works: Using a Crew of AI agents (Senior Researcher, Visionary, and Senior Editor), this crew will automatically determine the right questions to ask to produce a detailed fundamental stock analysis. This application has two components: a front-end and a Stock Q&A engine. The front end is the team of agents automatically figuring out the questions to ask, and the back-end part is the ability to answer those questions with the SEC 10K data. This template implements the Stock Q&A engine. For the front-end of the application, you can choose one of two options: using CrewAI with the Replit environment (code approach) fully visual approach with n8n template (AI-powered automated stock analysis) Setup steps: Use first workflow in template to upsert a company annual report PDF (such as from SEC 10K filling) Get URL for Webhook in second workflow template CrewAI front-end: Youtube overview video Fork this AI Agent environment Crew Agent Environment Set the webhook URL into N8N_WEBHOOK_URL variable Set OpenAI_API_KEY variable

How it works This workflow watches a selected Google Drive folder for any images added to it. It then takes that image, sends it the the tinypng.com service which optimises and reduces its size (where possible) Tinypng then returns the updated image which is then automatically saved in your chose Google Drive folder Setting things up It's pretty simple to configure and should only take around 5-10mins. You only need to set up credentials for Google Drive and Tinypng.com For Tinypng.com you can sign up for their free tier API access which gives you 500 optimisations per month Once you have those two things, you just need choose your 'input' folder to watch for images and your 'output' folder for where these images should be stored There are a few more optional things you can do such as the naming of your final image and also lots more you could do with the Tinypng API for more advanced image optimisation

This is an end-to-end workflow for creating a simple OpenAI Assistant. The whole process is done with n8n nodes and do not require any programming experience. The workflow is divided into three main steps: Step 1: Get a Google Drive File and Upload to OpenAI The workflow starts by retrieving a file from Google Drive using the "Get File" node. The example file used is a Music Festival document. The retrieved file is then uploaded to OpenAI using the "Upload File to OpenAI" node. Run this section only once. The file is stored persistently on the OpenAI side. Step 2: Set Up a New Assistant In this step, a new assistant is created using the "Create new Assistant" node. The assistant is given a name, description, and system prompt. The uploaded file from Step 1 is attached as a knowledge source for the assistant. Same as for Step 1, run this section only once. Step 3: Chat with the Assistant The "Chat Trigger" node initiates the conversation with the assistant. The "OpenAI Assistant" node handles the conversation, using the assistant created in Step 2. Step 4: Expand the Assistant This step provides resources for ideas on how to expand the Assistant's capabilities: Create a WhatsApp bot Create a simple Telegram bot Create a Telegram AI bot (YouTube video) By following this workflow, users can create their own AI-powered assistants using OpenAI's API and integrate them with various platforms like WhatsApp and Telegram.

This n8n workflow demonstrates how you can summarise and automate post-meeting actions from video transcripts fed into an AI Agent. Save time between meetings by allowing AI handle the chores of organising follow-up meetings and invites. How it works This workflow scans for the calendar for client or team meetings which were held online. * Attempts will be made to fetch any recorded transcripts which are then sent to the AI agent. The AI agent summarises and identifies if any follow-on meetings are required. If found, the Agent will use its Calendar Tool to to create the event for the time, date and place for the next meeting as well as add known attendees. Requirements Google Calendar and the ability to fetch Meeting Transcripts (There is a special OAuth permission for this action!) OpenAI account for access to the LLM. Customising the workflow This example only books follow-on meetings but could be extended to generate reports or send emails.

This n8n template demonstrates an approach to image embeddings for purpose of building a quick image contextual search. Use-cases could for a personal photo library, product recommendations or searching through video footage. How it works A photo is imported into the workflow via Google Drive. The photo is processed by the edit image node to extract colour information. This information forms part of our semantic metadata used to identify the image. The photo is also processed by a vision-capable model which analyses the image and returns a short description with semantic keywords. Both pieces of information about the image are combined with the metadata of the image to form a document describing the image. This document is then inserted into our vector store as a text embedding which is associated with our image. From here, the user can query the vector store as they would any document and the relevant image references and/or links should be returned. Requirements Google account to download image files from Google Drive. OpenAI account for the Vision-capable AI and Embedding models. Customise this workflow Text summarisation is just one of many techniques to generate image embeddings. If the results are unsatisfactory, there are dedicated image embedding models such as Google's vertex AI multimodal embeddings.

This is a simple template to show how to extract multiple email attachments and return them as an iterable output. How it works: The Gmail Trigger node detects any new email that has attachments. The Code node will then extract them as binary files and attaches them to the item. They can then be uploaded via the Google Drive node. Setup steps: add your Gmail Credentials add your Google Drive Credentials Follow the official n8n Documentation for help Feedback & Questions If you have any questions or feedback about this workflow - Feel free to get in touch at ria@n8n.io

This workflow allows you to recognize a folder with receipts or invoices (make sure your files are in .pdf, .png, or .jpg format). The workflow can be triggered via the "Test workflow" button, and it also monitors the folder for new files, automatically recognizing them. Video Demo https://youtu.be/mGPt7fqGQD8 1. n8n import glitch After import, the trigger node "When clicking 'Test workflow'" might be disconnected. You need to connect it via 2 arrows to "Google Sheets1" and "Google Drive" nodes. So, the workflow has 2 triggers - via button, and via Google Sheets "new file" event - both of these triggers should be connected to 2 nodes. Here is how it should look like: https://ocr.oakpdf.com/n8n_fix.png 2. Set up RapidAPI HTTP auth key Create new "HTTP header" n8n credential and paste your RapidAPI key from https://rapidapi.com/restyler/api/receipt-and-invoice-ocr-api into it. https://ocr.oakpdf.com/n8n_api_key.png Make sure "HTTP Request" node uses this credential. 3. Set up your Google Auth You need a Google connection to work with your Google Sheets and Google Drive accounts: https://docs.n8n.io/integrations/builtin/credentials/google/oauth-generic/#finish-your-n8n-credential 4. Set up Google Sheets Copy this Google Sheets document: https://docs.google.com/spreadsheets/d/1G0w-OMdFRrtvzOLPpfFJpsBVNqJ9cfRLMKCVWfrTQBg/edit?usp=sharing Custom document formats and advanced usage Email: contact@scrapeninja.net Linkedin: https://www.linkedin.com/in/anthony-sidashin/

Who this is for This template is for everyone that wants to download their n8n Cloud invoices automatically as a PDF instead of downloading them manually. How it works This workflow checks your Gmail inbox for new n8n invoice emails from n8n's payment provider Paddle. Once it finds something, it converts the URL into a PDF using pdflayer and saves it in Google Drive. Setup Setup your Gmail and Google Drive credentials Create a free account at https://pdflayer.com/ Insert your pdflayer API key into the Setup node Insert the URL to the wanted drive folder into the setup node (make sure to remove everything after the ?) How to adjust it to your need Instead of saving the PDF in Google drive, you could also save it in your local system, any other storage provider or send the PDF automatically to the right person in your company.

This is a demo workflow to showcase how to use Supabase to embed a document, retrieve information from the vector store via chat and update the database. Setup steps: set your credentials for Supabase set your credentials for an AI model of your choice set credentials for any service you want to use to upload documents please follow the guidelines in the workflow itself (Sticky Notes) Feedback & Questions If you have any questions or feedback about this workflow - Feel free to get in touch at ria@n8n.io

This n8n workflow demonstrates how we can use Multimodal LLMs to parse and extract from PDF documents in n8n. In this particular scenario, we're passing a candidate's CV/resume to an AI which filters out unqualified applications. However, this sneaky candidate has added in hidden prompt to bypass our bot! Whatever will we do? No fret, using AI Vision is one approach to solve this problem... read on! How it works Our candidate's CV/Resume is a PDF downloaded via Google Drive for this demonstration. The PDF is then converted into an image PNG using a tool called Stirling PDF. Since the hidden prompt has a white font color, it is is invisible in the converted image. The image is then forwarded to a Basic LLM node to process using our multimodal model - in this example, we'll use Google's Gemini 1.5 Pro. In the Basic LLM node, we'll need to set a User Message with the type of Binary. This allows us to directly send the image file in our request. The LLM is now immune to the hidden prompt and its response is has expected. The example CV/Resume with hidden prompt can be found here: https://drive.google.com/file/d/1MORAdeev6cMcTJBV2EYALAwll8gCDRav/view?usp=sharing Requirements Google Gemini API Key. Alternatively, GPT4 will also work for this use-case. Stirling PDF or another service which can convert PDFs into images. Note for data privacy, this example uses a public API and it is recommended that you self-host and use a private instance of Stirling PDF instead. Customising the workflow Swap out the manual trigger for another trigger such as a webhook to integrate into your existing services. This example demonstrates a validation use-case ie. "does the candidate look qualified?". You can try additionally extracting data points instead such as years of experiences, previous companies etc.

This n8n workflow is a proof-of-concept template exploring how we might work with multimodal LLMs and their multi-image analysis capabilities. In this demo, we compare 2 screenshots of a webpage taken at different timestamps and pass both to our multimodal LLM for a visual comparison of differences. Handling multiple binary inputs (ie. images) in an AI request is supported by n8n's basic LLM node. How it works This template is intended to run as 2 parts: first to generate the base screenshots and next to run the visual regression test which captures fresh screenshots. Starting with a list of webpages captured in a Google sheet, base screenshots are captured for each using a external web scraping service called Apify.com (I prefer Apify but feel free to use whichever web scraping service available to you) These base screenshots are uploaded to Google Drive and will be referenced later when we run our testing. Phase 2 of the workflow, we'll use a scheduled trigger to fire sometime in the future which will reuse our web scraping service to generate fresh screenshots of our desired webpages. Next, re-download our base screenshots in parallel and with both old and new captures, we'll pass these to our LLM node. In the LLM node's options, we'll define 2 "user message" inputs with the type of binary (data) for our images. Finally, we'll prompt our LLM with our testing criteria and capture the regressions detected. Note, results will vary depending on which LLM you use. A final report can be generated using the LLM's output and is uploaded to Linear. Requirements Apify.com API key for web screenshotting service Google Drive and Sheets access to store list of webpages and captures Customising this workflow Have your own preferred web screenshotting service? Feel free to swap out Apify with your service of choice. If the web screenshot is too large, it may prove difficult for the LLM to spot differences with precision. Try splitting up captures into smaller images instead.

This n8n workflow shows how using multimodal LLMs with AI vision can tackle tricky image validation tasks which are near impossible to achieve with code and often impractical to be done by humans at scale. You may need image validation when users submitted photos or images are required to meet certain criteria before being accepted. A wine review website may require users only submit photos of wine with labels, a bank may require account holders to submit scanned documents for verification etc. In this demonstration, our scenario will be to analyse a set of portraits to verify if they meet the criteria for valid passport photos according to the UK government website (https://www.gov.uk/photos-for-passports). How it works Our set of portaits are jpg files downloaded from our Google Drive using the Google Drive node. Each image is resized using the Edit Image node to ensure a balance between resolution and processing speed. Using the Basic LLM node, we'll define a "user message" option with the type of binary (data). This will allow us to pass our portrait to the LLM as an input. With our prompt containing the criteria pulled off the passport photo requirements webpage, the LLM is able to validate the photo does or doesn't meet its criteria. A structured output parser is used to structure the LLM's response to a JSON object which has the "is_valid" boolean property. This can be useful to further extend the workflow. Requirements Google Gemini API key Google Drive account Customising this workflow Not using Gemini? n8n's LLM node works with any compatible multimodal LLM so feel free to swap Gemini out for OpenAI's GPT4o or Antrophic's Claude Sonnet. Don't need to validate portraits? Try other use cases such as document classification, security footage analysis, people tagging in photos and more.

This n8n workflow demonstrates an approach to parsing bank statement PDFs with multimodal LLMs as an alternative to traditional OCR. This allows for much more accurate data extraction from the document especially when it comes to tables and complex layouts. Multimodal Parsing is better than traditiona OCR because: It reduces complexity and overhead by avoiding the need to preprocess the document into text format such as markdown before passing to the LLM. It handles non-standard PDF formats which may produce garbled output via traditional OCR text conversion. It's orders of magnitude cheaper than premium OCR models that still require post-processing cleanup and formatting. LLMs can format to any schema or language you desire! How it works You can use the example bank statement created specifically for this workflow here: https://drive.google.com/file/d/1wS9U7MQDthj57CvEcqG_Llkr-ek6RqGA/view?usp=sharing A PDF bank statement is imported via Google Drive. For this demo, I've created a mock bank statement which includes complex table layouts of 5 columns. Typically, OCR will be unable to align the columns correctly and mistake some deposits for withdrawals. Because multimodal LLMs do not accept PDFs directly, well have to convert the PDF to a series of images. We can achieve this by using a tool such as Stirling PDF. Stirling PDF is self-hostable which is handy for sensitive data such as bank statements. Stirling PDF will return our PDF as a series of JPGs (one for each page) in a zipped file. We can use n8n's decompress node to extract the images and ensure they are ordered by using the Sort node. Next, we'll resize each page using the Edit Image node to ensure the right balance between resolution limits and processing speed. Each resized page image is then passed into the Basic LLM node which will use our multimodal LLM of choice - Gemini 1.5 Pro. In the LLM node's options, we'll add a "user message" of type binary (data) which is how we add our image data as an input. Our prompt will instruct the multimodal LLM to transcribe each page to markdown. Note, you do not need to do this - you can just ask for data points to extract directly! Our goal for this template is to demonstrate the LLMs ability to accurately read the page. Finally, with our markdown version of all pages, we can pass this to another LLM node to extract required data such as deposit line items. Requirements Google Gemini API for Multimodal LLM. Google Drive access for document storage. Stirling PDF instance for PDF to Image conversion Customising the workflow At time of writing, Gemini 1.5 Pro is the most accurate in text document parsing with a relatively low cost. If you are not using Google Gemini however you can switch to other multimodal LLMs such as OpenAI GPT or Antrophic Claude. If you don't need the markdown, simply asking what to extract directly in the LLM's prompt is also acceptable and would save a few extra steps. Not parsing any bank statements any time soon? This template also works for Invoices, inventory lists, contracts, legal documents etc.

This n8n workflow template lets you easily generate comprehensive FAQ (Frequently Asked Questions) content for multiple services (or any items or pages you need to add the FAQs to). Simply provide the Google Sheets document containing the items to scrape, and the workflow automatically creates detailed, AI-enhanced FAQ documents. How it works The workflow reads data from a Google Sheets document containing information about different services and categories (again, in your case - whatever objects you need). For each service and category, it generates a set of standard questions and answers covering setup, permissions, integrations, use cases, and pricing benefits. An AI model (OpenAI's GPT) is used to enhance or complete some of the answers, making the content more comprehensive and natural-sounding. The workflow formats the Q&A pairs, combining AI-generated content with predefined answers where applicable. It creates a text file (JSON) for each service or category, containing the formatted Q&A pairs. The generated files are saved to specific folders in Google Drive, organized by the type of integration (native, credential-only, non-native) or category. After processing each service or category, it updates the status in the original Google Sheets document to mark it as completed. Ideal for: Marketing teams: Rapidly create comprehensive FAQ documents for multiple products or services. Customer support: Generate consistent and detailed answers for common customer queries. Product managers: Easily maintain up-to-date documentation as products evolve. Content creators: Streamline the process of creating informative content about various offerings. Accounts required Google account (for Google Sheets and Google Drive) OpenAI API account (for AI-enhanced content generation) n8n.io account (for workflow execution) Set up instructions Set up the required credentials for Google Sheets, Google Drive, and OpenAI when you first open the workflow. Prepare your Google Sheets document with the service/category information. Here's an example of Google Sheet. Fill the "Define Sheets" node with your sheets Adjust the folder IDs in the "Prepare Job" node to match your Google Drive structure. Configure the OpenAI model settings in the "OpenAI Chat Model" node if needed. Test the workflow with a small subset of data before running it on your entire dataset. Adjust the questions asked in the "Create your Q&A templates" section After testing, activate your workflow for automated FAQ generation. 🙏 Big, big kudos to Jim Le for his ideas, input and support when building this workflow. Your approach to AI workflows is always super helpful!

This n8n template takes a video and extracts frames from it which are used with a multimodal LLM to generate a script. The script is then passed to the same multimodal LLM to generate a voiceover clip. This template was inspired by Processing and narrating a video with GPT's visual capabilities and the TTS API How it works Video is downloaded using the HTTP node. Python code node is used to extract the frames using OpenCV. Loop node is used o batch the frames for the LLM to generate partial scripts. All partial scripts are combined to form the full script which is then sent to OpenAI to generate audio from it. The finished voiceover clip is uploaded to Google Drive. Sample the finished product here: https://drive.google.com/file/d/1-XCoii0leGB2MffBMPpCZoxboVyeyeIX/view?usp=sharing Requirements OpenAI for LLM Ideally, a mid-range (16GB RAM) machine for acceptable performance! Customising this workflow For larger videos, consider splitting into smaller clips for better performance Use a multimodal LLM which supports fully video such as Google's Gemini.

Description This template creates a nightly backup of all n8n workflows and saves them to a Google Drive folder. Each night, the previous night's backups are moved to an “n8n_old” folder and renamed with the corresponding date. Backups older than a specified age are automatically deleted (this feature is active for 30 days, you can remove it if you don't want the backups to be deleted). Prerequisites Google Drive account and credentials Get from the following link. Link n8n version from v 1.63.4 to 1.70.1 or higher N8n api key Guide from the following link. Link A destination folder for backups: “n8n_old” “n8n_backups” (if it doesn't exist, create it) Configuration Update all Google Drive nodes with your credentials. Edit the Schedule Trigger node with the desired time to run the backup. If you want to automatically purge old backups. Edit the “PURGE DAYS” node to specify the age of the backups you want to delete. Enable the “PURGE DAYS” node and the 3 subsequent nodes. Enable the workflow to run on the specified schedule. Last updated January 2025

Use Case Automate image replacement in Google Docs: You need to update document images dynamically You want to create multiple versions of a template with different images You need to batch process document images from a URL database You want to generate shareable documents with custom images What this Workflow Does The workflow automates image replacement in Google Docs: Accepts image URLs from your database Finds and replaces images in template documents Creates new document copies with updated images Optionally converts to PDF and makes documents shareable Setup Connect your image URL database (column name must be "url") Set up Google Docs OAuth 2 API credentials Optional: Create a template document in Google Drive with placeholder images Optional: Configure Google Drive authentication for additional features How to Adjust it to Your Needs Remove template copying for single document processing Adjust image ID selection for documents with multiple images Configure sharing settings and download formats Customize file naming and storage location More templates and n8n workflows >>> @simonscrapes

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.

This n8n workflow simplifies the process of removing backgrounds from images stored in Google Drive. By leveraging the PhotoRoom API, this template enables automatic background removal, padding adjustments, and output formatting, all while storing the updated images back in a designated Google Drive folder. This workflow is very useful for companies or individuals that are spending a lot of time into removing the background from product images. How it Works The workflow begins with a Google Drive Trigger node that monitors a specific folder for new image uploads. Upon detecting a new image, the workflow downloads the file and extracts essential metadata, such as the file size. Configurations are set for background color, padding, output size, and more, which are all customizable to match specific requirements. The PhotoRoom API is called to process the image by removing its background and adding padding based on the settings. The processed image is saved back to Google Drive in the specified output folder with an updated name indicating the background has been removed. Requirements PhotoRoom API Key Google Drive API Access Customizing the Workflow Easily adjust the background color, padding, and output size using the configuration node. Modify the output folder path in Google Drive or replace Google Drive with another storage service if needed. For advanced use cases, integrate further image processing steps, such as adding captions or analyzing content using AI.

his workflow automates time tracking using location-based triggers. How it works Trigger: It starts when you enter or exit a specified location, triggering a shortcut on your iPhone. Webhook: The shortcut sends a request to a webhook in n8n. Check-In/Check-Out: The webhook receives the request and records the time and whether it was a "Check-In" or "Check-Out" event. Google Sheets: This data is then logged into a Google Sheet, creating a record of your work hours. Set up steps Google Drive: Connect your Google Drive account. Google Sheets: Connect your Google Sheets account. Webhook: Set up a webhook node in n8n. iPhone Shortcuts: Create two shortcuts on your iPhone, one for "Check-In" and one for "Check-Out." Configure Shortcuts: Configure each shortcut to send a request to the webhook with the appropriate "Direction" header. It's easy to setup, around 5 minutes.

Hacker News to Video Content Overview This workflow converts trending articles from Hacker News into engaging video content. It integrates AI-based tools to analyze, summarize, and generate multimedia content, making it ideal for content creators, educators, and marketers. Features Article Retrieval: Pulls trending articles from Hacker News. Limits the number of articles to process (configurable). Content Analysis: Uses OpenAI's GPT model to: Summarize articles. Assess their relevance to specific topics like automation or AI. Extract key image URLs. Image and Video Generation: Leonardo.ai: Creates stunning AI-generated images based on extracted prompts. RunwayML: Converts images into high-quality videos. Structured Content Creation: Parses content into structured formats for easy reuse. Generates newsletter-friendly blurbs and social media-ready captions. Cloud Integration: Uploads generated assets to: Dropbox Google Drive Microsoft OneDrive MinIO Social Media Posting (Optional): Supports posting to YouTube, X (Twitter), LinkedIn, and Instagram. Workflow Steps 1. Trigger Initiated manually via the "Test Workflow" button. 2. Fetch Articles Retrieves articles from Hacker News. Limits the results to avoid processing overload. 3. Content Filtering Evaluates if articles are related to AI/Automation using OpenAI's language model. 4. Image and Video Generation Generates: AI-driven image prompts via Leonardo.ai. Videos using RunwayML. 5. Asset Management Saves the output to cloud storage services or uploads directly to social media platforms. Prerequisites API Keys**: Hacker News OpenAI Leonardo.ai RunwayML Creatomate n8n Installation**: Ensure n8n is installed and configured locally or on a server. Credentials**: Set up credentials in n8n for all external services used in the workflow. Customization Replace Hacker News with any other data source node if needed. Configure the "Article Analysis" node for different topics. Adjust the cloud storage services or add custom storage options. Usage Import this workflow into your n8n instance. Configure your API credentials. Trigger the workflow manually or schedule it as needed. Check the outputs in your preferred cloud storage or social media platform. Notes Extend this workflow further by automating social media posting or newsletter integration. For any questions, refer to the official documentation or reach out to the creator. About the Creator This workflow was built by AlexK1919, an AI-native workflow automation architect. Check out the overview video for a quick demo. Tools Used Leonardo.ai** RunwayML** Creatomate** Hacker News API** OpenAI GPT** Feel free to adapt and extend this workflow to meet your specific needs! 🎉

Case Study I'm too lazy to record every transaction for my expense tracking. Since all my expenses are digital, I just extract the transactions from bank PDF statements and screenshots into CSV to import into my budgeting software. Read more -> How I used A.I. to track all my expenses What this workflow does Upload your PDF or screenshots into Google Drive It then passes the PDF/image to Vertex Gemini to do some A.I. image recognition It then sends the transactions as CSV and stores it into another Google Drive folder Setup Set up 2 google drive folders. 1 for uploading and 1 for the output. Input your Google Drive crendtials Input your Vertex Gemini credentials How to adjust it to your needs You can upload other types of documents for information extraction. You can extract any text data from any image or PDF You can adjust the A.I. prompt to do different things

This workflow automates AI-based image generation using the Fal.ai Flux API. Define custom prompts, image parameters, and effortlessly generate, monitor, and save the output directly to Google Drive. Streamline your creative automation with ease and precision. Who is this for? This template is for content creators, developers, automation experts, and creative professionals looking to integrate AI-based image generation into their workflows. It’s ideal for generating custom visuals with the Fal.ai Flux API and automating storage in Google Drive. What problem is this workflow solving? Manually generating AI-based images, checking their status, and saving results can be tedious. This workflow automates the entire process — from requesting image generation, monitoring its progress, downloading the result, and saving it directly to a Google Drive folder. What this workflow does Sets Custom Image Parameters: Allows you to define the prompt, resolution, guidance scale, and steps for AI image generation. Sends a Request to Fal.ai: Initiates the image generation process using the Fal.ai Flux API. Monitors Image Status: Checks for completion and waits if needed. Downloads the Generated Image: Fetches the completed image once ready. Saves to Google Drive: Automatically uploads the generated image to a specified Google Drive folder. Setup 1. Prerequisites: • Fal.ai API Key: Obtain it from the Fal.ai platform and set it as the Authorization header in HTTP Header Auth credentials. • Google Drive OAuth Credentials: Connect your Google Drive account in n8n. 2. Configuration: • Update the “Edit Fields” node with your desired image parameters: • Prompt: Describe the image (e.g., “Thai young woman net idol 25 yrs old, walking on the street”). • Width/Height: Define image resolution (default: 1024x768). • Steps: Number of inference steps (e.g., 30). • Guidance Scale: Controls image adherence to the prompt (e.g., 3.5). • Set your Google Drive folder ID in the “Google Drive” node to save the image. 3. Run the Workflow: • Trigger the workflow manually to generate the image. • The workflow waits, checks status, and saves the final output seamlessly. Customization • Modify Image Parameters: Adjust the prompt, resolution, steps, and guidance scale in the “Edit Fields” node. • Change Storage Location: Update the Google Drive node with a different folder ID. • Add Notifications: Integrate an email or messaging node to alert you when the image is ready. • Additional Outputs: Expand the workflow to send the generated image to Slack, Dropbox, or other platforms. This workflow streamlines AI-based image generation and storage, offering flexibility and customization for creative automation.

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.

Video Guide I prepared a comprehensive guide detailing how to automate the parsing of invoices using n8n and LlamaParse, seamlessly capturing and storing vital billing information. Youtube Link Who is this for? This workflow is ideal for finance teams, accountants, and business operations managers who need to streamline invoice processing. It is particularly helpful for organizations seeking to reduce manual entry errors and improve efficiency in managing billing information. What problem does this workflow solve? Manually processing invoices can be time-consuming and error-prone. This automation eliminates the need for manual data entry by capturing invoice details directly from uploaded documents and storing structured data efficiently. This enhances productivity and accuracy across financial operations. What this workflow does The workflow leverages n8n and LlamaParse to automatically detect new invoices in a designated Google Drive folder, parse essential billing details, and store the extracted data in a structured format. The key functionalities include: Real-time detection of new invoices via Google Drive triggers. Automated HTTP requests to initiate parsing through Lama Cloud. Structured storage of invoice details and line items in a database for future reference. Google Drive Integration: Monitors a specific folder in Google Drive for new invoice uploads. Parsing with LlamaParse: Automatically sends invoices for parsing and processes results through webhooks. Data Storage in Airtable: Creates records for invoices and their associated line items, allowing for detailed tracking. Setup N8N Workflow Google Drive Trigger: Set up a trigger to detect new files in a specified folder dedicated to invoices. File Upload to LlamaParse: Create an HTTP request that sends the invoice file to LlamaParse for parsing, including relevant header settings and webhook URL. Webhook Processing: Establish a webhook node to handle parsed results from LlamaParse, extracting needed invoice details effectively. Invoice Record Creation: Create initial records for invoices in your database using the parsed details received from the webhook. Line Item Processing: Transform string data into structured line item arrays and create individual records for each item linked to the main invoice.

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.

This workflow implements a Retrieval Augmented Generation (RAG) chatbot that answers employee questions based on company documents stored in Google Drive. It automatically indexes new or updated documents in a Pinecone vector database, allowing the chatbot to provide accurate and up-to-date information. The workflow uses Google's Gemini AI for both embeddings and response generation. How it works The workflow uses two Google Drive Trigger nodes: one for detecting new files added to a specified Google Drive folder, and another for detecting file updates in that same folder. Automated Indexing: When a new or updated document is detected The Google Drive node downloads the file. The Default Data Loader node loads the document content. The Recursive Character Text Splitter node breaks the document into smaller text chunks. The Embeddings Google Gemini node generates embeddings for each text chunk using the text-embedding-004 model. The Pinecone Vector Store node indexes the text chunks and their embeddings in a specified Pinecone index. 7.The Chat Trigger node receives user questions through a chat interface. The user's question is passed to an AI Agent node. The AI Agent node uses a Vector Store Tool node, linked to a Pinecone Vector Store node in query mode, to retrieve relevant text chunks from Pinecone based on the user's question. The AI Agent sends the retrieved information and the user's question to the Google Gemini Chat Model (gemini-pro). The Google Gemini Chat Model generates a comprehensive and informative answer based on the retrieved documents. A Window Buffer Memory node connected to the AI Agent provides short-term memory, allowing for more natural and context-aware conversations. Set up steps Google Cloud Project and 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: Create a free account on the Pinecone website. Obtain your API key from your Pinecone dashboard. Create an index named company-files in your Pinecone project. Google Drive: Create a dedicated folder in your Google Drive where company documents will be stored. Credentials in n8n: Configure credentials in your n8n environment for: Google Drive OAuth2 Google Gemini(PaLM) Api (using your Google AI API key) Pinecone API (using your Pinecone API key) Import the Workflow: Import this workflow into your n8n instance. Configure the Workflow: Update both Google Drive Trigger nodes to watch the specific folder you created in your Google Drive. Configure the Pinecone Vector Store nodes to use your company-files index.

Overview This workflow helps you compare Claude 3.5 Sonnet and Gemini 2.0 Flash when extracting data from a PDF This workflow extracts and processes the data within a PDF in one single step, instead of calling an OCR and then an LLM” How it works The initial 2 steps download the PDF and convert it to base64. This base64 string is then sent to both Claude 3.5 Sonnet and Gemini 2.0 Flash to extract information. This workflow is made to let you compare results, latency, and cost (in their dedicated dashboard). How to use it Set up your Google Drive if not already done Select a document on your Google Drive Modify the prompt in "Define Prompt" to extract the information you need and transform it as wanted. Get a Claude API key and/or Gemini API key Note that you can deactivate one of the 2 API calls if you don't want to try both Test the Workflow

Workflow Documentation: HR Job Posting and Evaluation with AI Detailed Description The HR Job Posting and Evaluation with AI workflow is designed to streamline and enhance recruitment for technical roles, such as Automation Specialists. By automating key stages in the hiring process, this workflow ensures a seamless experience for both candidates and HR teams. From collecting applications to evaluating candidates using AI and scheduling interviews, this workflow provides an end-to-end solution for recruitment challenges. Who is this for? This workflow is ideal for: HR Professionals**: Managing multiple job postings and candidates efficiently. Recruitment Teams**: Handling large volumes of applications for technical positions. Hiring Managers**: Ensuring structured and objective candidate evaluations. What problem does this workflow solve? Time-Consuming Processes**: Automates repetitive tasks like data entry, CV management, and scheduling. Fair Candidate Evaluation**: Leverages AI to provide objective insights based on resumes and job descriptions. Streamlined Communication**: Ensures timely and personalized candidate interactions, improving their experience. What this workflow does This workflow automates the following steps: Form Submission: Collects candidate information via a structured application form. Data Storage: Stores applicant details in Airtable for centralized tracking. CV Management: Automatically uploads resumes to Google Drive for easy access and organization. AI-Powered Candidate Evaluation: Scores candidates based on their resumes and job descriptions using OpenAI, providing actionable insights. Interview Scheduling: Automates scheduling based on candidate and interviewer availability. Communication: Sends customized emails to candidates for interview invitations and feedback. Setup Prerequisites To use this workflow, you’ll need: n8n Account**: To create and run the workflow. Airtable Account**: For managing applicant data. Google Drive Account**: For storing candidate CVs. OpenAI API Key**: For AI-powered candidate scoring. SMTP Email Account**: For sending candidate communications. Setup Process Airtable Configuration: Create a base in Airtable with tables for Applicants and Job Positions. Google Drive Setup: Create a folder for CV storage and ensure you have write permissions. Integrate Airtable in n8n: Use the Airtable API key to connect Airtable to n8n. Integrate Google Drive in n8n: Authorize Google Drive to enable CV storage automation. OpenAI Integration: Add your OpenAI API key to n8n for candidate scoring. Email Configuration: Set up your SMTP email account in n8n for sending notifications and invitations. How to customize this workflow Tailor the workflow to fit your unique recruitment needs: Edit Job Descriptions: Adjust the form parameters to match the specific role and qualifications. Refine AI Evaluation Criteria: Modify OpenAI prompts to reflect the skills and competencies for the desired position. Personalize Email Templates: Update email content to match your organization’s tone and branding. Add New Features: Incorporate additional steps like feedback collection or integration with other HR tools. Conclusion The HR Job Posting and Evaluation with AI workflow simplifies and automates the recruitment process, enabling HR teams to focus on engaging with candidates rather than handling administrative tasks. With its powerful integrations and customization options, this workflow helps organizations hire efficiently while improving the candidate experience.

This workflow automatically fetches newly uploaded files from a specific folder in Google Drive, shares them via email with specified recipients, and logs the file details (name, ID, created time, modified time) into Airtable for easy tracking. It streamlines the process of file sharing and management while keeping track of important metadata in a central place. Step-by-Step Instructions Google Drive Node (Fetch New File) Action: This node fetches newly uploaded files from the specific folder you’ve mentioned in your Google Drive. Configuration: Set the folder ID in the Google Drive node where the files are uploaded. Use the “New File in Folder” trigger to automatically detect new files added to the folder. Send Email Node (Share File via Email) Action: After detecting the new file, this node shares the file via email with the recipient you specify. Configuration: Set the recipient's email address. Include the file URL from the Google Drive node in the email body, allowing easy access to the file. Add the file name as part of the email subject or body to notify the recipient about the new file. Airtable Node (Store File Metadata) Action: This node stores the file’s metadata, such as name, ID, creation time, modification time, and the email address to which it was sent, in your Airtable database. Configuration: Set up Airtable with a table. Map the output from the Google Drive node to store the file metadata, and use the email address from the email node for tracking. 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.

What this workflow does Monitors Google Drive: The workflow triggers whenever a new CSV file is uploaded. Uses AI to Identify PII Columns: The OpenAI node analyzes the data and identifies PII-containing columns (e.g., name, email, phone). Removes PII: The workflow filters out these columns from the dataset. Uploads Cleaned File: The sanitized file is renamed and re-uploaded to Google Drive, ensuring the original data remains intact. How to customize this workflow to your needs Adjust PII Identification: Modify the prompt in the OpenAI node to align with your specific data compliance requirements. Include/Exclude File Types: Adjust the Google Drive Trigger settings to monitor specific file types (e.g., CSV only). Output Destination: Change the folder in Google Drive where the sanitized file is uploaded. Setup Prerequisites: A Google Drive account. An OpenAI API key. Workflow Configuration: Configure the Google Drive Trigger to monitor a folder for new files. Configure the OpenAI Node to connect with your API Set the Google Drive Upload folder to a different location than the Trigger folder to prevent workflow loops.

1. How it Works This n8n workflow automates fine-tuning OpenAI models through these key steps: Manual Trigger**: Starts with the "When clicking ‘Test workflow’" event to initiate the process. Downloads a .jsonl file from Google Drive Upload to OpenAI**: Uploads the .jsonl file to OpenAI via the "Upload File" node (with purpose "fine-tune"). Create Fine-tuning Job**: Sends a POST request to the endpoint https://api.openai.com/v1/fine_tuning/jobs with: { "training_file": "{{ $json.id }}", "model": "gpt-4o-mini-2024-07-18" } OpenAI automatically starts training the model based on the provided file. Interaction with the Trained Model**: An "AI Agent" uses the custom model (e.g., ft:gpt-4o-mini-2024-07-18:n3w-italia::XXXX7B) to respond to chat messages. 2. Set up Steps To configure the workflow: Prepare the Training File: Create a .jsonl file following the specified syntax (e.g., travel assistant Q/A examples). Upload it to Google Drive and update the ID in the "Google Drive" node. Configure Credentials: Google Drive: Connect an account via OAuth2 (googleDriveOAuth2Api). OpenAI: Add your API key in the "OpenAI Chat Model" and "Upload File" nodes. Customize the Model: In the "OpenAI Chat Model" node, specify the name of your fine-tuned model (e.g., ft:gpt-4o-mini-...). Update the HTTP request body (Create Fine-tuning Job) if needed (e.g., a different base model). Start the Workflow: Use the manual trigger ("Test workflow") to begin the upload and training process. Test the model via the "Chat Trigger" (chat messages). Integrated Documentation: Follow the instructions in the Sticky Notes to: Properly format the .jsonl (Step 1). Monitor progress on OpenAI (Step 2, link: https://platform.openai.com/finetune/). Note: Ensure the .jsonl file adheres to OpenAI’s required structure and that credentials are valid.

Workflow Overview This workflow automates the creation and management of a custom OpenAI Assistant for a travel agency ("Travel with us"), leveraging Google Drive for document storage. How It Works 1. Create the OpenAI Assistant Node**: OpenAI Action: Creates a custom assistant named "Travel with us" Assistant using the gpt-4o-mini model. Instructions: Respond only using the provided document (e.g., agency-specific info). Stay friendly, brief, and focused on travel-related queries. Ignore irrelevant questions politely. Credentials: Requires OpenAI API key. 2. Upload Agency Document Google Drive Node**: Action: Downloads a Google Doc as a PDF. OpenAI2 Node**: Action: Uploads the PDF to OpenAI with purpose: "assistants". Output: Generates a file_id. 3. Update the Assistant with the Document OpenAI Node**: Action: Updates the assistant to include the uploaded file. 4. Chat Interaction Chat Trigger**: Activates when a message is received ("When chat message received"). OpenAI Assistant Node**: Action: Uses the updated assistant to respond to user queries. Memory: Window Buffer Memory retains chat context for coherent conversations. Set Up Steps Prepare the Document: Store your travel agency guide in Google Drive (e.g., as a Google Doc). Update the Google Drive node with your document’s ID. Configure Credentials: Google Drive: Connect via OAuth2 (googleDriveOAuth2Api). OpenAI: Add your API key to all OpenAI nodes. Customize the Assistant: Modify the instructions in the OpenAI node to reflect your agency’s needs. Ensure the document includes FAQs, policies, and travel info. Test the Workflow: Trigger manually ("Test workflow") to create the assistant and upload the file. Send a chat message (e.g., "What are your travel packages?") to test responses. Dependencies Google Drive Account**: To store and retrieve the agency document. OpenAI API Access**: For assistant creation and file uploads.

This workflow combines OpenAI, Retrieval-Augmented Generation (RAG), and WooCommerce to create an intelligent personal shopping assistant. It handles two scenarios: Product Search: Extracts user intent (keywords, price ranges, SKUs) and fetches matching products from WooCommerce. General Inquiries: Answers store-related questions (e.g., opening hours, policies) using RAG and documents stored in Google Drive. How It Works 1. Chat Interaction & Intent Detection Chat Trigger**: Starts when a user sends a message ("When chat message received"). Information Extractor**: Uses OpenAI to analyze the message and determine if the user is searching for a product or asking a general question. Extracts: search (true/false). keyword, priceRange, SKU, category (if product-related). Example: { "search": true, "keyword": "red handbags", "priceRange": { "min": 50, "max": 100 }, "SKU": "BAG123", "category": "women's accessories" } 2. Product Search (WooCommerce Integration) AI Agent**: If search: true, routes the request to the personal_shopper tool. WooCommerce Node: Queries the WooCommerce store using extracted parameters (keyword, priceRange, SKU). Filters products in stock (stockStatus: "instock"). Returns matching products (e.g., "red handbags under €100"). 3. General Inquiries (RAG System) RAG Tool**: If search: false, uses the Qdrant Vector Store to retrieve store information from documents. Google Drive Integration: Documents (e.g., store policies, FAQs) are stored in Google Drive. Downloaded, split into chunks, and embedded into Qdrant for semantic search. OpenAI Chat Model: Generates answers based on retrieved documents (e.g., "Our store opens at 9 AM"). Set Up Steps 1. Configure the RAG System Google Drive Setup**: Upload store documents . Update the Google Drive2 node with your folder ID. Qdrant Vector Database**: Clean the collection (update Qdrant Vector Store node with your URL). Use Embeddings OpenAI to convert documents into vectors. 2. Configure OpenAI & WooCommerce OpenAI Credentials**: Add your API key to all OpenAI nodes (OpenAI Chat Model, Embeddings OpenAI, etc.). WooCommerce Integration**: Connect your WooCommerce store (credentials in the personal_shopper node). Ensure product data is synced and accessible. 3. Customize the AI Agent Intent Detection**: Modify the Information Extractor’s system prompt to align with your store’s terminology. RAG Responses**: Update the tool description to reflect your store’s documents. Notes This template is ideal for e-commerce businesses needing a hybrid assistant for product discovery and customer support. Need help customizing? Contact me for consulting and support or add me on Linkedin.

This workflow converts any n8n workflow outputs into Markdown notes that are accessible in your Obsidian Vault through Google Drive synchronization. Setup Requirements Create a designated folder in Google Drive (Desktop). Create a symbolic link between this folder and a new target folder in your Obsidian Vault. Configure Google Drive n8n node settings. Send the output of any workflow to the trigger, and the notes will appear in your Vault folder. Optional Features You can use AI agents to: Write notes in your preferred format (e.g., Zettelkasten). Compose YAML front matter. Suggest tags. Use Cases Convert RSS feed items to notes. Create notes from YouTube video transcripts. Transform tasks in Slack messages into Obsidian tasks. (Requires setting up a corresponding workflow, e.g., RSS trigger, YouTube transcriber, or Slack bot.)

n8n Workflow: Automate SIEM Alert Enrichment with MITRE ATT&CK & Qdrant Who is this for? This workflow is ideal for: Cybersecurity teams & SOC analysts* who want to automate *SIEM alert enrichment**. IT security professionals* looking to integrate *MITRE ATT&CK intelligence** into their ticketing system. Organizations using Zendesk for security incidents* who need enhanced *contextual threat data**. Anyone using n8n and Qdrant* to build *AI-powered security workflows**. What problem does this workflow solve? Security teams receive large volumes of raw SIEM alerts that lack actionable context. Investigating every alert manually is time-consuming and can lead to delayed response times. This workflow solves this problem by: ✔ Automatically enriching SIEM alerts with MITRE ATT&CK TTPs. ✔ Tagging & classifying alerts based on known attack techniques. ✔ Providing remediation steps to guide the response team. ✔ Enhancing security tickets in Zendesk with relevant threat intelligence. What this workflow does 1️⃣ Ingests SIEM alerts (via chatbot or ticketing system like Zendesk). 2️⃣ Queries a Qdrant vector store containing MITRE ATT&CK techniques. 3️⃣ Extracts relevant TTPs (Tactics, Techniques, & Procedures) from the alert. 4️⃣ Generates remediation steps using AI-powered enrichment. 5️⃣ Updates Zendesk tickets with threat intelligence & recommended actions. 6️⃣ Provides structured alert data for further automation or reporting. Setup Guide Prerequisites n8n instance** (Cloud or Self-hosted). Qdrant vector store** with MITRE ATT&CK data embedded. OpenAI API key** (for AI-based threat processing). Zendesk account** (for ticket enrichment, if applicable). Clean Mitre Data Python Script Cleaned Mitre Data Full Mitre Data Steps to Set Up 1️⃣ Embed MITRE ATT&CK data into Qdrant This workflow pulls MITRE ATT&CK data from Google Drive and loads it into Qdrant. The data is vectorized using OpenAI embeddings for fast retrieval. 2️⃣ Deploy the n8n Chatbot The chatbot listens for SIEM alerts and sends them to the AI processing pipeline. Alerts are analyzed using an AI agent trained on MITRE ATT&CK. 3️⃣ Enrich Zendesk Tickets The workflow extracts MITRE ATT&CK techniques from alerts. It updates Zendesk tickets with contextual threat intelligence. The remediation steps are included as internal notes for SOC teams. How to Customize This Workflow 🔧 Modify the chatbot trigger: Adapt the chatbot node to receive alerts from Slack, Microsoft Teams, or any other tool. 🔧 Change the SIEM input source: Connect your workflow to Splunk, Elastic SIEM, or Chronicle Security. 🔧 Customize remediation steps: Use a custom AI model to tailor remediation responses based on organization-specific security policies. 🔧 Extend ticketing integration: Modify the Zendesk node to also work with Jira, ServiceNow, or another ITSM platform. Why This Workflow is Powerful ✅ Saves time: Automates alert triage & classification. ✅ Improves security posture: Helps SOC teams act faster on threats. ✅ Leverages AI & vector search: Uses LLM-powered enrichment for real-time context. ✅ Works across platforms: Supports n8n Cloud, Self-hosted, and Qdrant. 🚀 Get Started Now! 📖 Watch the Setup Video 💬 Have Questions? Join the Discussion in the YouTube Comments!

The provided workflow in n8n is designed to create a Business WhatsApp AI RAG (Retrieval-Augmented Generation) Chatbot. How it works: Webhook Setup: The workflow begins by setting up webhooks for verification and response. The Verify webhook receives GET requests and sends back a verification code, while the Respond webhook handles incoming POST requests from Meta regarding WhatsApp messages. Message Handling: Once a message is received, the workflow checks if the incoming JSON contains a user message. If it does, the message is processed further; otherwise, a generic response is sent. AI Agent Interaction: The user's message is passed to the AI Agent node, which uses a conversational agent with a predefined system message tailored for an electronics store. This ensures that the AI provides accurate and professional responses based on the knowledge base. Knowledge Base Utilization: The AI Agent references a knowledge base stored in Qdrant, a vector database. Documents from Google Drive are downloaded, vectorized using OpenAI embeddings, and stored in Qdrant for retrieval during conversations. Response Generation: The AI Agent generates a response using the OpenAI chat model (gpt-4o-mini) and sends it back to the user via WhatsApp. Set up steps: Create Qdrant Collection: Update the QDRANTURL and COLLECTION variables in the workflow. Use the Create collection HTTP request node to initialize the collection in Qdrant. Vectorize Documents: Configure the Get folder and Download Files nodes to fetch documents from a specified Google Drive folder. Use the Embeddings OpenAI node to generate embeddings for the downloaded files. Store the vectorized documents in Qdrant using the Qdrant Vector Store node. Configure Webhooks: Ensure both Verify and Respond webhooks have the same URL. Set the Verify webhook to use the GET HTTP method and the Respond webhook to use the POST HTTP method. Set Up AI Agent: Define the system prompt for the AI Agent, specifying guidelines for product information, technical support, customer service, and knowledge base usage. Link the AI Agent to the OpenAI chat model and configure any additional tools as needed. Test Workflow: Trigger the workflow manually using the When clicking ‘Test workflow’ node to ensure all components are functioning correctly. Monitor the flow of data through the nodes and verify that responses are being generated and sent accurately. By following these steps, the workflow will be fully operational, enabling a robust AI-powered chatbot capable of handling customer inquiries via WhatsApp. Need help customizing? Contact me for consulting and support or add me on Linkedin.

The "Voice RAG Chatbot with ElevenLabs and OpenAI" workflow in n8n is designed to create an interactive voice-based chatbot system that leverages both text and voice inputs for providing information. Ideal for shops, commercial activities and restaurants How it works: Here's how it operates: Webhook Activation: The process begins when a user interacts with the voice agent set up on ElevenLabs, triggering a webhook in n8n. This webhook sends a question from the user to the AI Agent node. AI Agent Processing: Upon receiving the query, the AI Agent node processes the input using predefined prompts and tools. It extracts relevant information from the knowledge base stored within the Qdrant vector database. Knowledge Base Retrieval: The Vector Store Tool node interfaces with the Qdrant Vector Store to retrieve pertinent documents or data segments matching the user’s query. Text Generation: Using the retrieved information, the OpenAI Chat Model generates a coherent response tailored to the user’s question. Response Delivery: The generated response is sent back through another webhook to ElevenLabs, where it is converted into speech and delivered audibly to the user. Continuous Interaction: For ongoing conversations, the Window Buffer Memory ensures context retention by maintaining a history of interactions, enhancing the conversational flow. Set up steps: To configure this workflow effectively, follow these detailed setup instructions: ElevenLabs Agent Creation: Begin by creating an agent on ElevenLabs (e.g., named 'test_n8n'). Customize the first message and define the system prompt specific to your use case, such as portraying a character like a waiter at "Pizzeria da Michele". Add a Webhook tool labeled 'test_chatbot_elevenlabs' configured to receive questions via POST requests. Qdrant Collection Initialization: Utilize the HTTP Request nodes ('Create collection' and 'Refresh collection') to initialize and clear existing collections in Qdrant. Ensure you update placeholders QDRANTURL and COLLECTION accordingly. Document Vectorization: Use Google Drive integration to fetch documents from a designated folder. These documents are then downloaded and processed for embedding. Employ the Embeddings OpenAI node to generate embeddings for the downloaded files before storing them into Qdrant via the Qdrant Vector Store node. AI Agent Configuration: Define the system prompt for the AI Agent node which guides its behavior and responses based on the nature of queries expected (e.g., product details, troubleshooting tips). Link necessary models and tools including OpenAI language models and memory buffers to enhance interaction quality. Testing Workflow: Execute test runs of the entire workflow by clicking 'Test workflow' in n8n alongside initiating tests on the ElevenLabs side to confirm all components interact seamlessly. Monitor logs and outputs closely during testing phases to ensure accurate data flow between systems. Integration with Website: Finally, integrate the chatbot widget onto your business website replacing placeholder AGENT_ID with the actual identifier created earlier on ElevenLabs. By adhering to these comprehensive guidelines, users can successfully deploy a sophisticated voice-driven chatbot capable of delivering precise answers utilizing advanced retrieval-augmented generation techniques powered by OpenAI and ElevenLabs technologies.

This workflow is ideal for businesses looking to automate their email responses, especially for handling inquiries about company information. It leverages AI to ensure accurate and professional communication. How It Works Email Trigger: The workflow starts with the Email Trigger (IMAP) node, which monitors an email inbox for new messages. When a new email arrives, it triggers the workflow. Email Preprocessing: The Markdown node converts the email's HTML content into plain text for easier processing by the AI models. Email Summarization: The Email Summarization Chain node uses an AI model (DeepSeek R1) to generate a concise summary of the email. The summary is limited to 100 words and is written in Italian. Email Classification: The Email Classifier node categorizes the email into predefined categories (e.g., "Company info request"). If the email does not fit any category, it is classified as "other". Email Response Generation: The Write email node uses an AI model (OpenAI) to draft a professional response to the email. The response is based on the email content and is limited to 100 words. The Review email node uses another AI model (DeepSeek) to review and format the drafted response. It ensures the response is professional and formatted in HTML (e.g., using `, , , ` tags where necessary). Email Sending: The Send Email node sends the reviewed and formatted response back to the original sender. Vector Database Integration: The Qdrant Vector Store node retrieves relevant information from a vector database (Qdrant) to assist in generating accurate responses. This is particularly useful for emails classified as "Company info request". The Embeddings OpenAI node generates embeddings for the email content, which are used to query the vector database. Document Vectorization: The workflow includes steps to create and refresh a Qdrant collection (Create collection and Refresh collection nodes). Documents from Google Drive are downloaded (Get folder and Download Files nodes), processed into embeddings (Embeddings OpenAI1 node), and stored in the Qdrant vector store (Qdrant Vector Store1 node). Set Up Steps Configure Email Trigger: Set up the Email Trigger (IMAP) node with the appropriate IMAP credentials to monitor the email inbox. Set Up AI Models: Configure the DeepSeek R1, OpenAI, and DeepSeek nodes with the appropriate API credentials for text summarization, response generation, and review. Set Up Email Classification: Define the categories in the Email Classifier node (e.g., "Company info request", "Other"). Ensure the OpenAI 4-o-mini node is configured to assist in classification. Set Up Vector Database: Configure the Qdrant Vector Store and Qdrant Vector Store1 nodes with the appropriate Qdrant API credentials and collection details. Set up the Embeddings OpenAI and Embeddings OpenAI1 nodes to generate embeddings for the email content and documents. Set Up Document Processing: Configure the Get folder and Download Files nodes to access and download documents from Google Drive. Use the Token Splitter and Default Data Loader nodes to process and split the documents into manageable chunks for vectorization. Set Up Email Sending: Configure the Send Email node with the appropriate SMTP credentials to send responses. Test the Workflow: Trigger the workflow manually using the When clicking ‘Test workflow’ node to ensure all steps execute correctly. Verify that emails are summarized, classified, and responded to accurately. Activate the Workflow: Once tested, activate the workflow to automate the process of handling incoming emails. Key Features Automated Email Handling**: Automatically processes incoming emails, summarizes them, and generates professional responses. AI-Powered Classification**: Uses AI to classify emails into relevant categories for targeted responses. Vector Database Integration**: Retrieves relevant information from a vector database to enhance response accuracy. Document Vectorization**: Processes and stores documents from Google Drive in a vector database for quick retrieval. Professional Email Formatting**: Ensures responses are professionally formatted and concise. Need help customizing? Contact me for consulting and support or add me on Linkedin.

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. Need help customizing? Contact me for consulting and support or add me on Linkedin.

How it Works This workflow automates the handling of incoming emails, summarizes their content, generates appropriate responses using a retrieval-augmented generation (RAG) approach, and obtains approval or suggestions before sending replies. Below is an explanation of its functionality divided into two main sections: Email Handling and Summarization: The process begins with the Email Trigger (IMAP) node which listens for new emails in a specified inbox. Once an email is received, the Markdown node converts its HTML content into plain text if necessary, followed by the Email Summarization Chain that uses AI to create a concise summary of up to 100 words. Response Generation and Approval: A Write email node generates a professional response based on the summarized content, ensuring brevity and professionalism while keeping within the word limit. Before sending out any automated replies, the system sends these drafts via Gmail for human review and approval through the Gmail node configured with free-text response options. If approved, the finalized email is sent back to the original sender using the Send Email node; otherwise, it loops back for further edits or manual intervention. Additionally, there's a Text Classifier node designed to categorize feedback from humans as either "Approved" or "Declined", guiding whether the email should proceed directly to being sent or require additional editing. Set Up Steps To replicate this workflow within your own n8n environment, follow these essential configuration steps: Configuration: Begin by setting up an n8n instance either locally or via cloud services offered directly from their official site. Import the provided JSON configuration file into your workspace, making sure all required credentials such as IMAP, SMTP, OpenAI API keys, etc., are properly set up under Credentials since multiple nodes rely heavily on external integrations for functionalities like reading emails, generating summaries, crafting replies, and managing approvals. Customization: Adjust parameters according to specific business needs, including but not limited to adjusting the conditions used during conditional checks performed by nodes like Approve?. Modify the template messages given to AI models so they align closely with organizational tone & style preferences while maintaining professionalism expected in business communications. Ensure correct mappings between fields when appending data to external systems where records might need tracking post-interaction completion, such as Google Sheets or similar platforms.

Workflow based on the following article. https://www.anthropic.com/news/contextual-retrieval This n8n automation is designed to extract, process, and store content from documents into a Pinecone vector store using context-based chunking. The workflow enhances retrieval accuracy in RAG (Retrieval-Augmented Generation) setups by ensuring each chunk retains meaningful context. Workflow Breakdown: 🔹 Google Drive - Retrieve Document: The automation starts by fetching a source document from Google Drive. This document contains structured content, with predefined boundary markers for easy segmentation. 🔹 Extract Text Content - Once retrieved, the document’s text is extracted for processing. Special section boundary markers are used to divide the text into logical sections. 🔹 Code Node - Create Context-Based Chunks: A custom code node processes the extracted text, identifying section boundaries and splitting the document into meaningful chunks. Each chunk is structured to retain its context within the entire document. 🔹 Loop Node - Process Each Chunk: The workflow loops through each chunk, ensuring they are processed individually while maintaining a connection to the overall document context. 🔹 Agent Node - Generate Context for Each Chunk: We use an Agent node powered by OpenAI’s GPT-4.0-mini via OpenRouter to generate contextual metadata for each chunk, ensuring better retrieval accuracy. 🔹 Prepend Context to Chunks & Create Embeddings - The generated context is prepended to the original chunk, creating context-rich embeddings that improve searchability. 🔹 Google Gemini - Text Embeddings: The processed text is passed through Google Gemini text-embedding-004, which converts the text into semantic vector representations. 🔹 Pinecone Vector Store - Store Embeddings: The final embeddings, along with the enriched chunk content and metadata, are stored in Pinecone, making them easily retrievable for RAG-based AI applications. Use Case: This automation enhances RAG retrieval by ensuring each chunk is contextually aware of the entire document, leading to more accurate AI responses. It’s perfect for applications that require semantic search, AI-powered knowledge management, or intelligent document retrieval. By implementing context-based chunking, this workflow ensures that LLMs retrieve the most relevant data, improving response quality and accuracy in AI-driven applications.

This workflow takes off the task of backing up workflows regularly on Github and uses Google Drive as the main tool to host these. This can be a good way to keep track of your workflows so that you never lose any workflows in case your n8n goes down. How does it work Creates a new folder within a specified folder with the time its backed up Loops around all workflows, converts them to a JSON file and uploads them to the created folder Gets the previous backups and deletes them This has a clean feel and look as it simplifies the backup while not keeping a cache of workflows on your drive. Setup Create a new folder Create new service account credentials Share the folder with the service account email Upload this workflow to your canvas and map the credentials Set the schedule that you need your workflows to run and manage your backups Activate the workflow Happy Productivity! @Imperol

This workflow automates the retrieval of invoice PDFs from the Smartbill API and saves them to Google Drive in a dynamically created folder based on last month’s date. It also generates a range of invoice numbers, ensuring proper formatting, and uploads each PDF with a structured filename. Overview Trigger and Data Setup: The workflow is manually triggered. It sets the invoice range (start and end numbers), invoice series, the parent Google Drive folder ID and the folder where to save the PDF files. Folder Handling: Folder Name Calculation: Calculates a default folder name based on last month’s date (formatted as YYYY-MM). Invoice Generation: A code node generates invoice items by iterating over a specified range of numbers. Each invoice number is padded to custom number of digits (e.g., 0013), and the invoice series and folder ID are attached to each item. Retrieving Invoice PDFs: For each generated invoice, the Smartbill API is called (using an HTTP Request node) to retrieve the corresponding invoice PDF. How to Use Credentials:** Ensure you have configured the Smartbill API (HTTP Basic Auth) and Google API credentials correctly. Parameter Adjustment:** Modify the SetData node if you need to change the invoice range, series, or target parent folder. Execution:** Click Execute Workflow to run the workflow manually.

Overview This n8n workflow automates the process of extracting published WordPress posts, converting them into a CSV file, and uploading it to Google Drive. It’s perfect for content backups, SEO audits, and data migration. Features Fetches all published posts from a WordPress website Extracts key post details (ID, Title, Link) Converts the extracted data into a CSV file Uploads the CSV file to Google Drive for easy access and storage Use Cases SEO Optimization**: Export post data for keyword analysis and performance tracking Automated Content Backup**: Store WordPress post details in Google Drive. You can add more fields to the Csv file if needed Workflow Steps 1. Trigger Workflow Manually The workflow starts when triggered manually in n8n. 2. Retrieve WordPress Posts The workflow fetches all published posts using the WordPress API. It extracts: Post ID Title Link Rendered Content 3. Format Data The retrieved data is structured to ensure correct CSV formatting. 4. Convert to CSV File The formatted data is transformed into a downloadable CSV file. 5. Upload to Google Drive The CSV file is automatically uploaded to a specified Google Drive folder for easy access and storage. How to Use Connect your WordPress and Google Drive accounts to n8n. Run the workflow manually or set up a scheduled trigger. Access the CSV file from your Google Drive folder.

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.

Description This automation template is designed for content creators, digital marketers, and social media managers looking to simplify their video posting workflow. It automates the process of generating engaging video descriptions and uploading content to both Instagram and TikTok, making your social media management more efficient and error-free. Who Is This For? Content Creators & Influencers:** Streamline your video uploads and focus more on creating content. Digital Marketers:** Ensure consistent posting across multiple platforms with minimal manual intervention. Social Media Managers:** Automate repetitive tasks and maintain a steady online presence. What Problem Does This Workflow Solve? Manually creating descriptions and uploading videos to different platforms can be time-consuming and error-prone. This workflow addresses these challenges by: Automating Video Uploads:** Monitors a designated Google Drive folder for new videos. Generating Descriptions:** Uses OpenAI to transcribe video audio and generate engaging, customized social media descriptions. Ensuring Multi-Platform Consistency:** Simultaneously posts your video with the generated description to Instagram and TikTok. Error Notifications:** Optional Telegram integration sends alerts in case of issues, ensuring smooth operations. How It Works Video Upload: Place your video in the designated Google Drive folder. Description Generation: The automation triggers OpenAI to transcribe your video’s audio and generate a captivating description. Content Distribution: Automatically uploads the video and description to both Instagram and TikTok. Error Handling: Sends Telegram notifications if any issues arise during the process. Setup Generate an API token at upload-post.com and configure it in both the Upload to TikTok and Upload to Instagram nodes. Google Cloud Project: Create a project in Google Cloud Platform, enable the Google Drive API, and generate the necessary OAuth credentials to connect to your Google Drive account. Set up your Google Drive folder in the Google Drive Trigger node. Customize the OpenAI prompt in the Generate Social Description node to match your brand’s tone. (Optional) Configure Telegram credentials for error notifications. Requirements Accounts:** upload-post.com, Google Drive, and (optionally) Telegram. API Keys & Credentials:** Upload-post.com API token, OpenAI API key, and (optional) Telegram bot token. Google Cloud:** A project with the Google Drive API enabled and valid OAuth credentials. Use this template to enhance your productivity, maintain consistency across your social media channels, and engage your audience with high-quality video content.

The best content automation in the market! This advanced workflow not only creates and publishes SEO-optimized blog posts to your WordPress website but also backs up all content and images to a designated folder in your Google Drive. In addition, It generates a unique image for each chapter and a featured image for the overall article, and it automatically collects internal website links—seamlessly inserting them throughout each chapter and the entire article. This integrated approach enhances on-page SEO, improves navigation, and streamlines your content creation process, saving you time while ensuring your work is securely stored. How it works Triggers upon adding a new row to a Google Sheets. Generates a full blog post by writing content based on customizable parameters such as topic, target audience, length, style, and seed keyword. Generates and adds images for each chapter as well as a featured image for the article. Gathers internal website links and strategically embeds them within each chapter and throughout the article, boosting SEO and enhancing user navigation. Publishes the blog post directly to your WordPress website. Saves all content (blog post and images) to Google Drive, organizing them in a folder named after the blog post title. Unique features Full Automation: The workflow is designed to be 100% automated. Once imported and configured, it can run without manual intervention. Simple Activation: It can be easily triggered through the Google Spreadsheets interface. You simply add a new row to a Google Sheet. Customization Options: Offers a wide array of customization options, including topic, category, target audience, word count, number of chapters, length of introduction and conclusion, and writing style. It also allows for the inclusion of calls-to-action (CTAs) and company/product introductions. Automatic Content Saving: After writing a blog post, all content and images are automatically saved to Google Drive, preventing data loss. The folder is even named after the title of the blog post. SEO-Optimized Content: It's designed to create content optimized for SEO using seed keywords. AI Model Flexibility: It’s super easy to switch between different AI models through the Open Router node. Rate Limit Handling: Includes "Wait" nodes to avoid rate limits. Internal Link Limit: Limits the number of internal links to 20 by default. Set up steps Install the workflow template: Import the JSON file into your n8n instance. Connect the workflow to your accounts: This includes linking your WordPress website, Google Drive, and AI models (such as OpenAI GPT-4o). Configure the Google Sheet: Ensure your Google Sheet is set up to trigger the workflow upon adding a new row and that the input data is correctly formatted. Customize the workflow: Adjust parameters like topic, target audience, and writing style to match your specific content needs. Optimize prompts for best results. Test the workflow: Use low-cost AI models and image settings initially to ensure everything runs smoothly. Tailor Further as Needed: Modify workflow elements to align perfectly with your needs and content strategy.

This workflow automates the generation of multi-speaker podcasts using AI-powered text-to-speech technology. It starts by retrieving a podcast script from a Google Sheets document, where each speaker’s lines are clearly defined. The workflow then processes the script, generates a natural-sounding audio file with different voices for each speaker, and stores the final audio file in Google Drive. The workflow is designed to save time and resources by automating the podcast production process, making it ideal for content creators, marketers, and businesses that need to produce high-quality audio content regularly. How It Works Triggering the Workflow: The workflow starts with the When clicking ‘Test workflow’ node, which can be triggered manually to begin the process. Data Retrieval: The Get Podcast text node retrieves data from a Google Sheets document containing the podcast script. The document includes columns for the speaker's name and the corresponding text. Data Aggregation: The Get all rows node aggregates the data from the Google Sheets document, combining the speaker names and their respective text into a single dataset. Text Formatting: The Full Podcast Text node processes the aggregated data, formatting it into a single string where each speaker's text is prefixed with their name. Audio Generation: The Create Audio node sends a request to the API to generate a multi-speaker podcast audio file. The request includes the formatted text and specifies the voices for each speaker. When you register for the API service you will get 1$ for free. For continuous work add API credits to your account. Status Check: The Get status node checks the status of the audio generation request. If the status is "COMPLETED", the workflow proceeds; otherwise, it waits again. Audio Retrieval: The Get Url Audio node retrieves the URL of the generated audio file. The Get File Audio node downloads the audio file from the provided URL. Audio Storage: The Upload Audio node uploads the generated audio file to a specified Google Drive folder for storage. Key Features Multi-Speaker Support**: Generates podcasts with different voices for each speaker, creating a more dynamic and engaging listening experience. Google Sheets Integration**: Retrieves podcast scripts from a Google Sheets document, making it easy to manage and update content. AI-Powered Text-to-Speech**: Uses advanced AI models to generate natural-sounding audio from text. Automated Audio Generation**: Streamlines the process of creating podcast audio files, reducing the need for manual recording and editing. Google Drive Storage**: Automatically uploads the generated audio files to Google Drive for easy access and sharing. This workflow is ideal for businesses and content creators looking to automate the production of multi-speaker podcasts. It leverages AI to handle the complex task of generating natural-sounding audio, allowing users to focus on creating compelling content.

Intelligent Email Support System with Vector Database Overview This n8n workflow automates email support using AI and vector database technology to provide smart, context-aware responses. It seamlessly integrates email automation and document management, ensuring efficient customer support. 📌 System Components ✉️ Email Support System Email Monitoring & Classification Gmail trigger node monitoring inbox AI-powered email classification Intelligent routing (support vs non-support inquiries) AI Response Generation LangChain agent for response automation OpenAI integration for NLP-driven replies Vector-based knowledge retrieval Automated draft creation in Gmail Vector Database System Supabase vector store for document management OpenAI embeddings for vector conversion Fast and efficient similarity search 📂 Document Management System Google Drive Integration Monitors specific folders for new/updated files Automatic document processing Supports various file formats Document Processing Pipeline Auto file download & text extraction Smart text chunking for better indexing Embedding generation via OpenAI Storage in Supabase vector database 🔄 Workflow Processes 📧 Email Support Flow Monitor Gmail inbox for new emails AI classification of incoming messages Route support emails to AI response generator Perform vector similarity search for knowledge retrieval Generate personalized AI-driven response Create email drafts in Gmail 📁 Document Management Flow Monitor Google Drive for new/updated files Auto-download and process documents Clean up outdated vector entries for updated files Extract and split document text efficiently Generate OpenAI embeddings Store processed data in Supabase vector DB ⚙️ Setup Instructions 1️⃣ Prerequisites Supabase** account & project OpenAI API key** Gmail account** with OAuth2 setup Google Drive API** access n8n installation** 2️⃣ Supabase Database Setup -- Create the vector extension create extension if not exists vector; -- Create the documents table create table documents ( id bigserial primary key, content text, metadata jsonb, embedding vector(1536) ); -- Create an index for similarity search create index on documents using ivfflat (embedding vector_cosine_ops) with (lists = 100); 3️⃣ Google Drive Setup Create & configure two monitored folders: RAG folder for new documents documents Assign correct folder permissions Add folder IDs to the workflow 4️⃣ Document Processing Configuration Set up triggers for file creation and file updates Configure text extraction: Define chunk size & overlap settings Set document metadata processing 🔍 Maintenance & Optimization 📌 Regular Tasks Monitor system performance Update the knowledge base regularly Review AI response quality Optimize vector search parameters Clean up outdated document embeddings ✅ Best Practices Document Organization Maintain structured folders & naming conventions Keep knowledge base content updated System Optimization Track AI classification accuracy Tune response times & chunk sizes Perform regular database maintenance 🛠️ Troubleshooting Email Issues Verify Gmail API credentials Check AI service uptime Monitor classification performance Document Processing Issues Ensure correct file permissions Validate extraction & embedding processes Debug vector database insertions

This n8n workflow is designed to automate the aggregation, processing, and reporting of community statistics related to n8n creators and workflows. Its primary purpose is to generate insightful reports that highlight top contributors, popular workflows, and key trends within the n8n ecosystem. Here's how it works and why it's important: How It Works Data Retrieval: The workflow fetches JSON data files from a GitHub repository containing statistics about creators and workflows. It uses HTTP requests to access these files dynamically based on pre-defined global variables. Data Processing: The data is parsed into separate streams for creators and workflows. It processes the data to identify key metrics such as unique weekly and monthly inserters/visitors. Ranking and Filtering: The workflow sorts creators by their weekly inserts and workflows by their popularity. It selects the top 10 creators and top 50 workflows for detailed analysis. Report Generation: Using AI tools like GPT-4 or Google Gemini, the workflow generates a Markdown report summarizing trends, contributors, and workflow statistics. The report includes tables with detailed metrics (e.g., unique visitors, inserters) and insights into why certain workflows are popular. Distribution: The report is saved locally or uploaded to Google Drive. It can also be shared via email or Telegram for broader accessibility. Automation: A schedule trigger ensures the workflow runs daily or as needed, keeping the reports up-to-date. Why It's Important Community Insights**: This workflow provides actionable insights into the n8n community by identifying impactful contributors and popular workflows. This fosters collaboration and innovation within the ecosystem. Time Efficiency**: By automating data collection, processing, and reporting, it saves significant time and effort for community managers or administrators. Recognition of Contributors**: Highlighting top creators encourages engagement and recognizes individuals driving value in the community. Trend Analysis**: The workflow helps uncover patterns in usage, enabling better decision-making for platform improvements or feature prioritization. Scalability**: With its modular design, this workflow can be easily adapted to include additional metrics or integrate with other tools.

💡🌐 Essential Multipage Website Scraper with Jina.ai Use responsibly and follow local rules and regulations This N8N workflow enables automated multi-page website scraping using Jina.ai's powerful web scraping capabilities, with seamless integration to Google Drive for content storage. Here's how it works: Main Features The workflow automatically scrapes multiple pages from a website's sitemap and saves each page's content as a separate Google Drive document. Key Components Input Configuration Starts with a sitemap URL (default: https://ai.pydantic.dev/sitemap.xml)** Processes the sitemap to extract individual page URLs Includes filtering options to target specific topics or pages Scraping Process Uses Jina.ai's web scraper to extract content from each URL Converts webpage content into clean markdown format Extracts page titles automatically for document naming Storage Integration Creates individual Google Drive documents for each scraped page Names documents using the format "URL - Page Title" Saves content in markdown format for better readability Usage Instructions Set your target website's sitemap URL in the "Set Website URL" node Configure the "Filter By Topics or Pages" node to select specific content Adjust the "Limit" node (default: 20 pages) to control batch size Connect your Google Drive account Run the workflow to begin automated scraping Additional Features Built-in rate limiting through the Wait node to prevent overloading servers Batch processing capability for handling large sitemaps The workflow requires no API key for Jina.ai, making it accessible for immediate use while maintaining responsible scraping practices.

🎦🚀 YouTube Video Comment Analysis Agent This n8n workflow is designed to help YouTube creators analyze video details and comments to generate a comprehensive and actionable report. The workflow provides insights into video performance, audience engagement, and viewer feedback, helping creators identify trends, interests, and opportunities for future content creation. ✨ Key Features Video Performance Analysis: Extracts metrics like views, likes, and comments to evaluate the video's success. Comment Sentiment Analysis: Determines the tone of comments (positive, neutral, or negative) to understand audience sentiment. Recurring Themes Detection: Identifies common topics or questions in comments to highlight viewer interests. Engagement Drivers: Pinpoints what aspects of the video resonated most with viewers. Actionable Recommendations: Offers strategies for creating follow-up content or improving future videos. Keyword Suggestions: Extracts frequently mentioned terms for better discoverability on YouTube. Collaboration Opportunities: Suggests potential partnerships based on viewer feedback or related channels. 🛠️ How to Use Set Up Workflow Variables: Add your GOOGLE_API_KEY and the VIDEO_ID of the YouTube video you want to analyze in the "Workflow Variables" node. Ensure your Google API key has access to the YouTube Data API. Run the Workflow: Trigger the workflow manually or through another workflow using the "Execute Workflow Trigger" node. The workflow will fetch video details and comments using pagination to ensure all data is captured. Generate Insights: The workflow processes video details and comments to create a detailed report with actionable insights. Outputs include sentiment analysis, engagement drivers, content opportunities, and audience profiling. View or Share Results: The report is converted into Markdown and can be emailed via Gmail or saved to Google Drive as a document. 🌟 Value from This Workflow Gain a deeper understanding of your audience's preferences and feedback. Identify trends and engagement drivers to replicate success in future videos. Discover new content opportunities based on viewer questions and suggestions. Improve discoverability by leveraging keyword suggestions extracted from comments. Build stronger connections with your audience by addressing their needs effectively.

Summary This template uses the item handling nodes, and expression-support in n8n, without using a Code node, to extract multiple attachments from a GMail (trigger input) message/event, and (conditionally) upload each of them to Google Drive. Note: There is another template titled Get Multiple Attachments from Gmail and upload them to GDrive that does basically the same thing, but it uses a Code node. Details Using Split Out instead of Code The “secret” to how this works is that n8n supports a special input field name $binary that references the entire set of (multiple) binary data sub-elements in a single input item. It may look like an expression, but in this case it is a “fixed” (literal) value used as the Fields to Split Out parameter value. Dealing with names that are prefixed/suffixed with an Index The next challenge with multiple attachments from a GMail message is that each one is still assigned different name like "attachment_0", "attachment_1", etc. This makes it tricky to reference them in a generic way. However, once n8n splits the items out, the binary in each item is always the first (i.e. index-zero / [0]) and ONLY key/value. So, that makes it possible get the key-name and attributes of the corresponding value indirectly with some clever expression syntax. Input Data Field Name -> Expression: {{ $binary.keys()[0] }} - This returns the name, regardless of whether it is "attachment_0", "attachment_1", or whatever else. Attachment file name: -> Expression: {{ $binary.values()[0].fileName }} Attachment file name extension: -> Expression: {{ $binary.values()[0].fileExtension }} Attachment file type: -> Expression: {{ $binary.values()[0].fileType }} Attachment file size (e.g. string "100 kB"): -> Expression: {{ $binary.values()[0].fileSize }} Attachment file size (numeric): -> Expression: {{ $binary.values()[0].fileSize.split(' ')[0].toNumber() }} Attachment mime type: -> Expression: {{ $binary.values()[0].mimeType }} Attachment id (storage GUID): -> Expression: {{ $binary.values()[0].id }} Flow Control Since each of the attachments becomes a single item, it is relatively straightforward to introduce other n8n nodes like If, Switch, or Filter and route each single attachment item into different workflow paths. The template demonstrates how each attachment binary could be routed based on its file size, as an example.

🗂️ Bulk File Upload to Google Drive with Folder Management How it works User submits files and target folder name via form Workflow checks if folder exists in Drive Creates folder if needed or uses existing one Processes and uploads all files maintaining structure Set up steps (Est. 10-15 mins) Set up Google Drive credentials in n8n Replace parent folder ID in search query with your Drive folder ID Configure form node with: Multiple file upload field Folder name text field Test workflow with sample files 💡 Detailed configuration steps and patterns are documented in sticky notes within the workflow. Perfect for: Bulk file organization Automated Drive folder management File upload automation Maintaining consistent file structures

✍️🌄 WordPress + AI Content Creator This workflow automates the creation and publishing of multi-reading-level content for WordPress blogs. It leverages AI to generate optimized articles, automatically creates featured images, and provides versions of the content at different reading levels (Grade 2, 5, and 9). How It Works Content Generation & Processing 🎯 Starts with a manual trigger and a user-defined blog topic Uses AI to create a structured blog post with proper HTML formatting Separates and validates the title and content components Saves a draft version to Google Drive for backup Multi-Reading Level Versions 📚 Automatically rewrites the content for different reading levels: Grade 9: Sophisticated language with appropriate metaphors Grade 5: Simplified with light humor and age-appropriate examples Grade 2: Basic language with simple metaphors and child-friendly explanations WordPress Integration 🌐 Creates a draft post in WordPress with the Grade 9 version Generates a relevant featured image using Pollinations.ai Automatically uploads and sets the featured image Sends success/error notifications via Telegram Setup Steps Configure API Credentials 🔑 Set up WordPress API connection Configure OpenAI API access Set up Google Drive integration Add Telegram bot credentials for notifications Customize Content Parameters ⚙️ Adjust reading level prompts as needed Modify image generation settings Set WordPress post parameters Test and Deploy 🚀 Run a test with a sample topic Verify all reading level versions Check WordPress draft creation Confirm notification system This workflow is perfect for content creators who need to maintain a consistent blog presence while catering to different audience reading levels. It's especially useful for educational content, news sites, or any platform that needs to communicate complex topics to diverse audiences.

🤖 AI-Powered RAG Chatbot with Google Drive Integration This workflow creates a powerful RAG (Retrieval-Augmented Generation) chatbot that can process, store, and interact with documents from Google Drive using Qdrant vector storage and Google's Gemini AI. How It Works Document Processing & Storage 📚 Retrieves documents from a specified Google Drive folder Processes and splits documents into manageable chunks Extracts metadata using AI for enhanced search capabilities Stores document vectors in Qdrant for efficient retrieval Intelligent Chat Interface 💬 Provides a conversational interface powered by Google Gemini Uses RAG to retrieve relevant context from stored documents Maintains chat history in Google Docs for reference Delivers accurate, context-aware responses Vector Store Management 🗄️ Features secure delete operations with human verification Includes Telegram notifications for important operations Maintains data integrity with proper version control Supports batch processing of documents Setup Steps Configure API Credentials: Set up Google Drive & Docs access Configure Gemini AI API Set up Qdrant vector store connection Add Telegram bot for notifications Add OpenAI Api Key to the 'Delete Qdrant Points by File ID' node Configure Document Sources: Set Google Drive folder ID Define Qdrant collection name Set up document processing parameters Test and Deploy: Verify document processing Test chat functionality Confirm vector store operations Check notification system This workflow is ideal for organizations needing to create intelligent chatbots that can access and understand large document repositories while maintaining context and providing accurate responses through RAG technology.

✨😃 Automated Workflow Backups to Google Drive This workflow automates the process of backing up your n8n workflows to Google Drive daily. It creates timestamped folders, saves workflows as JSON files, and manages old backups by retaining only the most recent seven days of data. Notifications are sent via Telegram to keep you informed of the backup status. How It Works Backup Creation Process 🗂️ Triggering Backups**: The workflow starts with either a manual trigger or a scheduled trigger that runs daily. Folder Creation**: Creates a new folder in Google Drive with a timestamped name (e.g., n8n-Workflow-Backups-YYYY-MM-DD). Workflow Retrieval**: Fetches all workflows from your n8n instance. File Conversion**: Converts each workflow into a JSON file for storage. File Upload**: Saves the JSON files into the newly created Google Drive folder. Backup Management 🔄 Folder Search**: Searches for existing backup folders in Google Drive with names matching n8n-Workflow-Backups. Retention Policy**: Identifies folders older than seven days using a custom JavaScript function and deletes them permanently to free up space. Notifications 📲 Telegram Alerts**: Sends a message via Telegram once the backup process is complete, including the folder name and a link to access it in Google Drive. Setup Steps API Configuration 🔑 Google Drive Integration: Set up Google Drive OAuth2 credentials in n8n. Specify the root folder or desired location for backups. n8n API Access: Configure n8n API credentials to allow fetching workflows. Telegram Notifications: Add your Telegram bot credentials and chat ID for notification delivery. Workflow Customization ⚙️ Define the schedule for automatic backups (e.g., daily at midnight). Adjust the retention period if you need more or fewer days of backups. Customize the Telegram message format as needed. Testing & Deployment 🚀 Run the workflow manually to verify folder creation and file uploads. Check that old folders are deleted correctly after seven days. Confirm Telegram notifications are sent with accurate details. Use Case Scenarios This workflow is perfect for teams or individuals who want to ensure their n8n workflows are securely backed up and organized. It is especially useful for: Protecting against accidental data loss. Automating routine administrative tasks. By combining automated backups, retention management, and real-time notifications, this workflow ensures your n8n workflows are always safe and accessible!

Personal Portfolio CV Rag Chatbot - with Conversation Store and Email Summary Target Audience This template is perfect for: Individuals looking to create a working professional and interactive personal portfolio chatbot. Developers interested in integrating RAG Chatbot functionality with conversation storage. 1. Description Create a stunning Personal Portfolio CV with integrated RAG Chatbot capabilities, including conversation storage and daily email summaries. 2.Features: Training: Setup Ingestion stage Upload your CV to Google Drive and let the Drive trigger updates to read your resume cv and convert it into your vector database (RAG purpose). Modify any parts as needed. Chat & Track: Use any frontend/backend interface to call the chat API and chat history API. Reporting Daily Chat Conversations: Receive daily automatic summaries of chat conversations. Data stored via NocoDB. 3.Setup Guide: Step-by-Step Instructions: Ensure all credentials are ready. Follow the notes provided. Ingestion: Upload your CV to Google Drive. The Drive triggers RAG update in your vector database. You can change the folder name, files and indexname of the vector database accordingly. Chat: Use any frontend/backend interface to call the chat API (refer to the notes for details) . [optional] Use any frontend/backend interface to call the update chat history API (refer to the notes for details). 3.Tracking Chat: Get daily automatic summaries of chat conversations.Format email conversations report as you like. You are ready to go!

Welcome to my Automated Image Metadata Tagging Workflow! This workflow automatically analyzes the image content with the help of AI and writes it directly back into the image file as keywords. This workflow has the following sequence: Google Drive trigger (scan for new files added in a specific folder) Download the added image file Analyse the content of the image and extract the file as Base64 code Merge Metadata and Base64 Code Code Node to write the Keywords into the Metadata (dc:subject) Convert to file and update the original file in the Google Drive folder The following accesses are required for the workflow: Google Drive: Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) You can contact me via LinkedIn, if you have any questions: https://www.linkedin.com/in/friedemann-schuetz

Welcome to my Automated Image Metadata Tagging Workflow! DISCLAIMER: This workflow only works with self-hosted n8n instances! You have to install the n8n-nodes-exif-data Community Node! An alternative for cloud using is this workflow This workflow automatically analyzes the image content with the help of AI and writes it directly back into the image file as keywords. (https://n8n.io/workflows/2995).** This workflow has the following steps: Google Drive trigger (scan for new files added in a specific folder) Download the added image file Analyse the content of the image Merge Metadata and image file Write the Keywords into the Metadata (dc:subject/keywords) and create new image file Update the original file in the Google Drive folder The following accesses are required for the workflow: You have to install the n8n-nodes-exif-data Community Node** Google Drive: Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) You can contact me via LinkedIn, if you have any questions: https://www.linkedin.com/in/friedemann-schuetz

🐶🤖 AI Agent for Pet Shops – Automate Customer Service & Bookings! 🐾💡 Transform Your Pet Shop with AI-Powered Automation! 🚀 Enhance customer experience and optimize operations with this n8n AI Agent designed for pet shops. 📲🐾 Automate client interactions, appointment scheduling, and service recommendations—saving time and increasing revenue! 🔹 Key Features: ✅ Instant WhatsApp responses – AI-powered chatbot handles customer inquiries. 💬 ✅ Automated appointment scheduling – Clients can book services hassle-free. 📅✂️ ✅ Personalized reminders – Reduce no-shows with automated notifications. 📢🐾 ✅ Customer data & service history management – Track interactions effortlessly. 📊📁 ✅ Product & service recommendations – Improve sales with smart suggestions. 🎁🐶 📌 How It Works 1️⃣ The workflow captures customer inquiries via WhatsApp. 2️⃣ AI processes requests, provides information, and offers booking options. 3️⃣ Clients can schedule grooming, vet visits, or other services in seconds. 4️⃣ Automated reminders ensure appointments are remembered. 5️⃣ Customer data is stored for better service personalization. ⚙️ Setup & Customization 🔧 Connect your WhatsApp API (evolution) for instant messaging. 🔧 Integrate with Google Calendar for appointment booking. 🔧 Customize reminders, services, and pricing rules to fit your business. 💡 Reduce manual work, improve customer satisfaction, and scale your pet shop with AI automation! 🐶🤖 [PT-BR] Agente de IA para Pet Shops – Atendimento e Agendamentos Automatizados! 🐾💡 Transforme Seu Pet Shop com Automação Inteligente! 🚀 Otimize o atendimento ao cliente e agilize processos com este Agente de IA para n8n. 📲🐾 Automatize interações, agendamentos e recomendações de serviços—economizando tempo e aumentando as vendas! 🔹 Principais Funcionalidades: ✅ Atendimento automático no WhatsApp – IA responde clientes instantaneamente. 💬 ✅ Agendamento de serviços automatizado – Clientes marcam banho, tosa ou consultas facilmente. 📅✂️ ✅ Lembretes personalizados – Reduza faltas com notificações automáticas. 📢🐾 ✅ Gestão de clientes e histórico de serviços – Controle dados de forma eficiente. 📊📁 ✅ Sugestão de produtos e serviços – Venda mais com recomendações inteligentes. 🎁🐶 📌 Como Funciona 1️⃣ O fluxo recebe perguntas dos clientes via WhatsApp. 2️⃣ A IA processa os pedidos e fornece opções de agendamento. 3️⃣ O cliente escolhe o serviço desejado e agenda em segundos. 4️⃣ Lembretes automáticos garantem que os clientes não esqueçam os horários. 5️⃣ O histórico do cliente é salvo para oferecer um atendimento mais personalizado. ⚙️ Configuração e Personalização 🔧 Conecte sua API do WhatsApp (evolution) para interação automática. 🔧 Integre ao Google Calendar para gerenciar agendamentos. 🔧 Personalize valores, serviços e regras de envio de lembretes conforme sua necessidade. 💡 Automatize processos, melhore a experiência do cliente e escale seu pet shop com IA! 🚀

Description This workflow automates document processing using LlamaParse to extract and analyze text from various file formats. It intelligently processes documents, extracts structured data, and delivers actionable insights through multiple channels. How It Works Document Ingestion & Processing 📄 Monitors Gmail for incoming attachments or accepts documents via webhook Validates file formats against supported LlamaParse extensions Uploads documents to LlamaParse for advanced text extraction Stores original documents in Google Drive for reference Intelligent Document Analysis 🧠 Automatically classifies document types (invoices, reports, etc.) Extracts structured data using customized AI prompts Generates comprehensive document summaries with key insights Converts unstructured text into organized JSON data Invoice Processing Automation 💼 Extracts critical invoice details (dates, amounts, line items) Organizes financial data into structured formats Calculates tax breakdowns, subtotals, and payment information Maintains detailed records for accounting purposes Multi-Channel Delivery 📱 Saves extracted data to Google Sheets for tracking and analysis Sends concise summaries via Telegram for immediate review Creates searchable document archives in Google Drive Updates spreadsheets with structured financial information Setup Steps Configure API Credentials 🔑 Set up LlamaParse API connection Configure Gmail OAuth for email monitoring Set up Google Drive and Sheets integrations Add Telegram bot credentials for notifications Customize AI Processing ⚙️ Adjust document classification parameters Modify extraction templates for specific document types Fine-tune summary generation prompts Customize invoice data extraction schema Test and Deploy 🚀 Test with sample documents of various formats Verify data extraction accuracy Confirm notification delivery Monitor processing pipeline performance

Who is this for? This workflow is ideal for businesses, accountants, and finance teams who receive bank slip images via LINE and want to automate the extraction of transaction details. It eliminates manual data entry and speeds up financial tracking. What problem does this workflow solve? Many businesses receive bank transfer slips via LINE from customers, but manually recording transaction details into spreadsheets is time-consuming and error-prone. This workflow automates the entire process, extracting structured data from the bank slips and storing it in Google Sheets for seamless record-keeping. What this workflow does: Receives bank slip images from LINE BOT Extracts transaction details (sender, receiver, amount, transaction ID) using SpaceOCR Automatically logs extracted data into Google Sheets Works with Standard Bank Slips & PromptPay transactions Eliminates manual data entry and reduces errors Setup Instructions: 1. Prerequisites A LINE BOT with Messaging API enabled A SpaceOCR API Key (Get from https://spaceocr.com/) A Google Sheets account to store extracted data An n8n instance running (Cloud or Self-hosted) 2. Setup Google Sheets Create a Google Sheet with the following structure: A (Date) B (Time) C (Sender) D (Receiver) E (Bank Name) F (Amount) G (Transaction ID) Ensure your Google Sheets API is enabled and connected to n8n. For an example of the required format, check this Google Sheets template: Google Sheets Template 3. Configure n8n Workflow 1. Webhook Node (Receives bank slip from LINE BOT) Set method:* Set Path:* 2. HTTP Request (Download Image from LINE Message) Retrieves image URL from the LINE message payload 3. SpaceOCR Node (Extract Text from Bank Slip) Input:* API Key:* #### 4. Google Sheets Node (Save Transaction Data) Select your Google Sheet Map extracted data (sender, receiver, amount, etc.) to the respective columns 4. Deploy & Test Activate the workflow in n8n Set Webhook URL in LINE Developer Console Send a test bank slip image to the LINE BOT Check Google Sheets for extracted transaction data

Attachments Gmail to Drive and Google Sheets Description Automatically process invoice emails by saving attachments to Google Drive and extracting key invoice data to Google Sheets using AI. This workflow monitors your Gmail for unread emails with attachments, saves PDFs to a specified Google Drive folder, and uses OpenAI's GPT-4o to extract invoice details (date, description, amount) into a structured spreadsheet. Use cases Invoice Management**: Automatically organize and track invoices received via email Financial Record Keeping**: Maintain a structured database of all invoice information Document Organization**: Keep digital copies of invoices organized in Google Drive Automated Data Entry**: Eliminate manual data entry for invoice processing Resources Gmail account Google Drive account Google Sheets account OpenAI API key Setup instructions Prerequisites Active Gmail, Google Drive, and Google Sheets accounts OpenAI API key (GPT-4o model access) n8n instance with credentials manager Steps Gmail and Google Drive Setup: Connect your Gmail account in n8n credentials Connect your Google Drive account with appropriate permissions Create a destination folder in Google Drive for invoice storage Google Sheets Setup: Connect your Google Sheets account Create a spreadsheet with columns: Invoice date, Invoice Description, Total price, and Fichero Copy your spreadsheet ID for configuration OpenAI Setup: Add your OpenAI API key to n8n credentials Configure Email Filter: Update the email filter node to match your specific sender requirements Benefits Time Saving**: Eliminates manual downloading, filing, and data entry Accuracy**: AI-powered data extraction reduces human error Organization**: Consistent file naming and storage structure Searchability**: Creates a searchable database of all invoice information Automation**: Runs every minute to process new emails as they arrive Related templates Email Parser to CRM Document Processing Workflow Financial Data Automation

The best content automation template in the market is now even better—with “deep research” on time-sensitive topics\! Unlike most n8n content automation templates that are mainly for “demo purposes,” this advanced n8n workflow is for the real PROs. It conducts in-depth research on the latest information about a topic, then automatically creates and publishes SEO-optimized blog posts to your WordPress website. In addition, it generates a unique image for each chapter and a featured image for the overall article, and it collects internal website links—seamlessly inserting links throughout each chapter and the entire article. Furthermore, it backs up all content and images to a designated folder in your Google Drive. This integrated approach not only creates high-quality, comprehensive content for readers but also enhances on-page SEO, improves navigation, and streamlines your content creation process—saving you time while ensuring your work is securely stored. This is a complimentary variation of the n8n WordPress Auto-Blogging Pro for SEO topics. That one specializes in auto-blogging content about established topics that do not need up-to-date information while this one takes it further by incorporating online research into the workflow. Both make up the perfect combo to run your blog on autopilot\! How It Works Trigger: It activates upon adding a new row to a Google Sheet. Users can control many customizable parameters, such as key topic, number of subtopics, target audience, length, and style. Initial Research: The workflow initiates preliminary research on the topic to gather insights for the content planning phase. Structure Planning: Based on the initial research, it plans a detailed structure for the entire article and breaks the article into subtopics strongly tied to the main topic. In-Depth Research & Writing: For each subtopic, it conducts further research to gather the most up-to-date, relevant information, then uses that research to write each chapter in depth. Image Generation: It generates and adds images for each chapter, as well as a featured image for the article. Internal Linking: The system gathers internal website links and strategically embeds them within each chapter and throughout the article, boosting SEO and enhancing user navigation. Final Assembly & Publishing: All texts, images, and links are combined into one comprehensive article, which is then published directly to your WordPress website. You can also choose to post it as a draft for final review. Auto Backup to Drive: Get peace of mind knowing all content (blog post and images) is automatically saved to Google Drive, organized in a folder named after the blog post title. Unique Features Deep Research: The workflow leverages advanced, real-time research to gather the latest information about a topic. It breaks down the key topic into subtopics and conducts in-depth research on each one, ensuring the most comprehensive and current knowledge. Full Automation: Designed to be 100% automated, the workflow runs without manual intervention once imported and configured. Simple Activation: It is easily triggered through the Google Sheets interface—simply add a new row to a Google Sheet. Customization Options: Offers a wide array of options, including topic, category, target audience, word count, number of chapters, length of introduction and conclusion, and writing style. It also allows for the inclusion of calls-to-action (CTAs) and company/product introductions. Advanced Loop in Loop: Clever looping is used to write each chapter and generate images, ensuring optimal results. “Wait” nodes are added where appropriate to avoid API call rate limits. Automatic Content Saving: After the blog post is created, all content and images are automatically saved to Google Drive, preventing data loss. The folder is named after the blog post title. SEO-Optimized Content: It is designed to create SEO-optimized content using seed keywords. Internal Link Limit: The workflow limits the number of internal links to 20 by default. Error Catch: “If” nodes are strategically used to ensure that the output from AI nodes strictly meets the JSON schema, ensuring a smooth flow of data without interruption. And many more big and small improvements. Requirements Please make sure you have these requirements ready to ensure smooth deployment of this n8n workflow template: OpenAI API or equivalent for text and image generation PerplexityAI API or equivalent for online research A WordPress website (other website platforms will not work\!) Google Sheets for triggering the workflow, or a trigger of your choice Google Drive and Google Docs for auto backup Set Up Steps Install the Workflow Template: Import the JSON files into your n8n instance. There are 2 files: one for the main workflow and one for the research tool (PerplexityAI). Connect the Workflow with Your Accounts: Link your accounts for OpenAI API, PerplexityAI API, Google Drive, Google Sheets, Google Docs, and WordPress website. Configure the Google Sheet: Ensure your Google Sheet is set up to trigger the workflow upon adding a new row and that the input data is correctly formatted. Customize the Inputs: Adjust parameters like topic, target audience, and writing style to match your specific content needs. Optimize prompts for the best results. Test the Workflow: Use low-cost AI models and image settings initially to ensure everything runs smoothly. Tailor Further as Needed: Modify workflow elements to perfectly align with your needs and content strategy. Tips for PROs Image Generation: The default AI model for image generation is OpenAI’s Dall-E. However, the outputs of this model are not impressive. Consider using FLUX.1 for better image quality. Research: PerplexityAI is the tool of choice for research. The default model used in this workflow is “sonar” due to its fast speed and low cost. Feel free to experiment with its other models, including the “sonar-deep-research” model, which is dedicated to deep research. Triggering: Triggering with a new row on Google Sheets is limited and unreliable. Consider setting an auto trigger with a daily schedule at a specific time. You can even put the whole workflow in a loop to process multiple rows one-by-one from Google Sheets. Human in the Loop: It is possible to incorporate a human review process. For example, after the article is posted to WordPress as a draft, a human can review the draft. Only after approval will the post be published, and a final copy of the post will be saved to the shared Drive folder.

AI-Powered WhatsApp Assistant for Restaurant & Delivery – Automate Orders, Calculate Delivery Fees & Enhance Customer Service with n8n 📌 Optimize your restaurant's delivery process with AI-powered automation! This n8n workflow enables an intelligent WhatsApp assistant for restaurants, burger joints, and delivery businesses. The AI chatbot efficiently handles orders, calculates delivery fees based on distance, manages customer interactions, and seamlessly integrates with your CRM and database for streamlined operations. ⚠️ Important Notice: This template is only compatible with self-hosted n8n instances as it uses community nodes. Ensure secure credential management when configuring APIs. 🔹 Key Features ✅ AI-Powered Order Processing – Automatically receive and confirm orders via WhatsApp. ✅ Real-Time Distance Calculation – Determines the delivery distance and calculates the fee dynamically. ✅ Automated Customer Interaction – Engages customers with intelligent conversation and order updates. ✅ WhatsApp Integration – Processes messages, saves customer details, and retrieves past interactions. ✅ Secure Customer Data Storage – Saves order history, customer preferences, and location details in a database. ✅ Seamless CRM & POS System Integration – Sync orders and customer data with your existing platforms. 📌 How It Works 1️⃣ A customer sends a message via WhatsApp to start an order. 2️⃣ The AI assistant guides them through the menu, recommends items, and confirms their choices. 3️⃣ The system retrieves and saves customer details (name, phone number, and address). 4️⃣ The AI calculates the delivery distance and applies the appropriate delivery fee. 5️⃣ The order details are saved and forwarded to the restaurant’s system for preparation. 6️⃣ The assistant keeps the customer updated about the order status. ⚙️ Setup & Customization 🔧 Webhook for WhatsApp – Capture and process customer messages automatically. 🔧 OpenAI-Powered AI Assistant – Configure conversation flows for natural and engaging interactions. 🔧 Delivery Fee Calculation – Set your delivery price per kilometer and adjust base rates. 🔧 Database & CRM Integration – Store customer details, order history, and location data. 🔧 Customizable Order Flow – Adapt the workflow for different restaurant models. 🔧 Secure Credential Management – Store API keys safely to prevent unauthorized access. 💡 Requirements: This template is recommended for users with basic knowledge of n8n. If you need custom development or setup assistance, contact us via WhatsApp: +55 17 99155-7874. 🚀 Automate order processing, reduce manual tasks, and improve customer satisfaction with AI-powered WhatsApp automation! Assistente de WhatsApp com IA para Restaurantes & Delivery – Automatize Pedidos, Calcule Taxas de Entrega e Melhore o Atendimento ao Cliente com n8n 📌 Otimize o processo de entrega do seu restaurante com automação baseada em IA! Este fluxo para n8n permite criar um atendente virtual inteligente no WhatsApp, ideal para hamburguerias, restaurantes e serviços de delivery. O chatbot baseado em IA recebe pedidos, calcula a taxa de entrega com base na distância, interage com os clientes e integra-se ao seu CRM para operações mais eficientes. ⚠️ Aviso Importante: Este template é compatível apenas com instâncias auto-hospedadas do n8n, pois utiliza nós da comunidade. Certifique-se de gerenciar credenciais de forma segura ao configurar APIs. 🔹 Principais Funcionalidades ✅ Processamento Inteligente de Pedidos – Recebe e confirma pedidos automaticamente via WhatsApp. ✅ Cálculo Dinâmico da Taxa de Entrega – Mede a distância e aplica a taxa correta automaticamente. ✅ Atendimento Automatizado ao Cliente – Interage com clientes de forma natural e profissional. ✅ Integração com WhatsApp – Captura mensagens, armazena dados e recupera histórico de pedidos. ✅ Armazenamento Seguro de Dados do Cliente – Salva pedidos, preferências e endereços de entrega. ✅ Sincronização com CRM e Sistema de PDV – Conecta-se ao seu sistema de gestão para um fluxo contínuo. 📌 Como Funciona 1️⃣ O cliente envia uma mensagem via WhatsApp para iniciar um pedido. 2️⃣ O assistente de IA apresenta o menu, sugere itens e confirma a escolha do cliente. 3️⃣ O sistema captura e salva os dados do cliente (nome, telefone e endereço). 4️⃣ A IA calcula a distância de entrega e aplica a taxa de acordo com a localização. 5️⃣ Os detalhes do pedido são registrados e enviados para a cozinha. 6️⃣ O assistente atualiza o cliente sobre o status do pedido. ⚙️ Configuração e Personalização 🔧 Webhook para WhatsApp – Configuração para capturar e processar pedidos automaticamente. 🔧 Assistente de IA com OpenAI – Configuração de fluxos conversacionais naturais e envolventes. 🔧 Cálculo de Taxa de Entrega – Definição de valores por quilômetro e ajustes de tarifas base. 🔧 Banco de Dados & CRM – Armazena dados de clientes, histórico de pedidos e localização. 🔧 Fluxo de Pedidos Personalizável – Adapte para diferentes tipos de restaurantes e serviços de delivery. 🔧 Gerenciamento Seguro de Credenciais – Proteja suas chaves de API contra acessos não autorizados. 💡 Requisitos: Este template é recomendado para usuários que já possuem conhecimentos básicos em n8n. Se precisar de personalização ou suporte para instalação, entre em contato pelo WhatsApp: +55 17 99155-7874. 🚀 Automatize o processamento de pedidos, reduza tarefas manuais e melhore a satisfação dos clientes com um WhatsApp automatizado e inteligente!

Find Job Postings from LinkedIn, Indeed, and Glassdoor and Save Them to Google Sheets Using AI Overview Effortlessly discover and apply to jobs tailored to your profile—AI handles the search, you handle the interviews. Say goodbye to endless job board scrolling. This automation leverages AI to analyze your resume, identify your skills, experience, and more, to match you with the most relevant job opportunities. It sources job postings from LinkedIn, Indeed, Glassdoor, ZipRecruiter, Monster, and other public job sites on the web. With seamless integration and automatic organization of results, you can focus on applying rather than searching. Key Features Intelligent Resume Parsing Extracts key information from your PDF resume using AI. Identifies skills, experience, education, and job preferences. Targeted Job Matching Uses the parsed resume data to search for jobs that align with your profile. Ensures relevance by analyzing job descriptions for matching criteria. Automated Data Organization Compiles job listings into a structured Google Spreadsheet. Eliminates the need for manual data entry, saving valuable time. Easy Access and Review Stores results in a familiar Google Sheets format for easy tracking. Allows for filtering and sorting to prioritize applications. Setup Instructions Prerequisites A free API key for the job search service. Google Drive and Google Sheets accounts. An updated resume in PDF format. Step 1: Connect Your Resume Parsing AI Upload your PDF resume to Google Drive. Configure the AI parser node in n8n to extract relevant information. Map the extracted fields (e.g., skills, job title, experience) for job searching. Step 2: Automate the Job Search Use the extracted data to perform a job search on LinkedIn, Indeed, Glassdoor, and other supported job sites. Retrieve job postings based on relevant keywords and location preferences. Step 3: Save Job Listings to Google Sheets Create a new Google Sheet to store job listings. Set up the automation to write job details (e.g., title, company, location, link) into the sheet. Format the sheet for better readability and tracking. Step 4: Review and Apply to Jobs Open your Google Sheet to view job matches. Click on the links to apply directly on the respective job sites. Update the status of each job application as you progress. Why Use This Automation? Saves Time**: Automates job searching and listing compilation. Enhances Efficiency**: Eliminates manual scrolling and data entry. Improves Organization**: Keeps all job opportunities in a structured format. Optimizes Your Job Hunt**: Increases chances of landing the perfect role. Designed specifically for job seekers aiming to optimize their search process, this automation integrates with Google Drive and Sheets, streamlining your job hunt and enhancing your chances of finding the right opportunity. Get started today and accelerate your career growth!

Detailed Technical Description This n8n workflow automates Yape payment receipt processing, integrating Telegram bot, AI-powered OCR, and Google Sheets automation. By leveraging ChatGPT Vision Computing, it extracts and structures transaction details, eliminating the need for manual entry. Ideal for freelancers, businesses, and finance teams, this workflow ensures error-free, real-time financial tracking. The AI agent powered by DeepSeek refines and formats the extracted text, storing it in Google Sheets for easy accessibility and reporting. Users can track payments, monitor cash flow, and generate financial reports without any manual work. This seamless integration boosts efficiency, reduces errors, and automates financial record-keeping with 100% accuracy. 🛠️ Technologies Used: ✅n8n – Workflow orchestrator. ✅Telegram – Handles image reception and notifications. ✅Google Drive – Manages file creation and storage. ✅Google Sheets – Automatically logs extracted data into spreadsheets. 🤖Artificial Intelligence: ✅ChatGPT Vision Computing – Performs OCR on payment receipts. ✅DeepSeek AI – Organizes and converts extracted data into a structured format. 📌 pre-conditions: 📩 A Telegram Bot – Must be created to receive images. Setup Guide 🔑 Google Sheets API Key – Required to store extracted data. Setup Guide ⚛️ ChatGPT API Key – Used for OCR and AI text extraction. Get it here 🐋 DeepSeek API Key – Processes extracted text into structured data. Get it here 1️⃣ Image Reception & OCR Processing 📩 The user attaches a Yape payment receipt image to the Telegram bot conversation. 🤳🏻 2️⃣ Analyze Image (OCR) 👁️‍🗨️ A ⚛️ChatGPT Vision Computing model processes the image and extracts all visible text, ensuring high-accuracy OCR for structured data extraction. 3️⃣ Analyze and format text Intelligent Data Processing with AI 🤖 The extracted text is sent to a 🐋DeepSeek-based AI agent that: Identifies and structures key transaction details (amount, date, sender, transaction ID, etc.). Converts the data into a structured JSON format. 4️⃣ Data Storage in Google Sheets 📊 Google Drive integration is established. If the Google Sheets file does not exist, it is automatically created. Extracted data is automatically recorded in the corresponding spreadsheet, enabling effortless tracking and streamlined financial organization. 🚀 Benefits: ✅ Time-saving – Eliminates manual payment processing. ✅ Error-free data entry – Reduces human mistakes in record-keeping. ✅ 100% automation – No manual intervention required. ✅ Seamless integration – Easily connects with other workflows. 💡NOTE: The extracted transaction data will be stored in a Google Sheets file with the following columns: | Column Name | Description | |:---------------------:|-----------------------------------------------------------| | id | Unique identifier for each transaction. | | beneficiaryName | Name of the recipient of the payment. | | amount | Payment amount in the specified currency. | | currency | Currency used for the transaction (e.g., PEN, USD). | | company | The entity or service handling the transaction. | | date | Date of the transaction in a human-readable format. | | hour | Time of the transaction. | | originalDate | The exact date extracted from the receipt. | | dateToISO | Standardized ISO 8601 date format. | | operation | Type of financial operation (e.g., deposit, transfer). | | operationNumber | Unique operation number provided by the payment system. | | beneficiaryNumber | Account or phone number of the recipient. | | commission | Any commission or fee charged for the transaction. | | account | Account number or reference used for the payment. | | channel | Payment method used (e.g., app, POS, bank transfer). | | agentCode | Identifier of the agent or entity processing the payment. | This workflow is perfect for businesses, freelancers, and individuals who need a fully automated solution to process Yape payment receipts efficiently. By leveraging AI-powered OCR and structured data extraction, it eliminates manual effort, reduces errors, and ensures that all transactions are accurately logged in Google Sheets. Whether you're managing personal finances, freelance payments, or business transactions, this system provides a seamless, hands-free approach to financial tracking, allowing you to focus on what truly matters.

Automate Audio Transcription, AI Summarization, and Google Drive Storage Who is this for? Content Teams, Researchers, and Administrators who need to automatically process voice memos, meeting recordings, or interview audio into structured, searchable documents. What problem does this solve? Eliminates manual transcription work by automatically converting audio files into organized text documents with AI analysis, while maintaining human oversight through approval workflows. What this workflow does Smart Audio Processing: Triggers when new .m4a files appear in Google Drive Uses OpenAI's Whisper for accurate transcription Implements dual-format reporting (JSON + Markdown) Human Oversight (optional): Requires email approval before processing 45-minute response window with escalation options AI-Powered Analysis: Generates structured JSON reports with: Key points & action items Sentiment analysis Technical terminology glossary Creates Markdown versions for easy reading Document Management: Stores raw transcripts + reports in Google Drive Automatic file naming with timestamps Sends completion alerts via Email/Telegram Workflow visualization showing audio file processing path Setup Credentials Needed: Google Drive API access OpenAI API key (GPT-4o-mini) Gmail & Telegram integrations Configuration: Set your Google Drive folder ID in 3 nodes Update email addresses in Gmail nodes Customize approval timeout in "Gmail User for Approval" Customization Points: File extension filters (.m4a) AI report templates and prompts Notification channels (Email/Telegram) How to customize Approval Process**: Add SMS/Teams notifications via additional nodes File Types**: Modify filter node for .mp3/.wav support Analysis Depth**: Adjust GPT-4 prompts in "Summarize to JSON" nodes Storage**: Connect to Notion/Airtable instead of Google Drive

This workflow automates the process of generating AI-powered video from image and then generates a video that is uploaded to Google Drive. This workflow is a powerful tool for automating the creation of AI-generated videos from images, saving time and ensuring a seamless process from input to final output. Below is a breakdown of the workflow: 1. How It Works The workflow is designed to create videos from images using AI and manage the generated content. Here's how it works: Form Submission: The workflow starts with a Form Trigger node, where users submit a form with the following fields: Description: The text description for the video. Duration (in seconds): The length of the video. Aspect Ratio: The aspect ratio of the video (e.g., 16:9, 9:16, 1:1). Image URL: The URL of the image to be used for video generation. Set Data: The Set Data node organizes the form inputs into a structured format for further processing. Create Video: The Create Video node sends a POST request to generate the video. The request includes the description, image URL, duration, and aspect ratio. Wait and Check Status: The Wait 60 sec. node pauses the workflow for 60 seconds to allow the video generation process to complete. The Get Status node checks the status of the video generation by querying the API. Completed?: The Completed? node checks if the video generation is complete. If not, the workflow loops back to wait and check again. Retrieve and Upload Video: Once the video is generated, the Get Url Video node retrieves the video URL. The Get File Video node downloads the video file. The Upload Video node uploads the video to a specified folder in Google Drive. Watch the resulting video 2. Set Up Steps To set up and use this workflow in n8n, follow these steps: API Key: Create an account on account and obtain your API Key. In the Create Video node, set up HTTP Header Authentication: Name: Authorization Value: Key YOURAPIKEY Google Drive Integration: Set up Google Drive credentials in n8n for the Upload Video node. Specify the folder ID in Google Drive where the generated videos will be uploaded. Form Configuration: The Form Trigger node is pre-configured with fields for: Description: The text description for the video. Duration (in seconds): The length of the video. Aspect Ratio: Choose between 16:9, 9:16, or 1:1. Image URL: The URL of the image to be used for video generation. Customize the form fields if needed. Test the Workflow: Submit the form with the required details (description, duration, aspect ratio, and image URL). The workflow will: Generate the video using the API. Check the status until the video is ready. Upload the video to Google Drive. Optional Customization: Modify the workflow to include additional features, such as: Adding more aspect ratio options. Sending notifications when the video is ready. Integrating with other storage services (e.g., Dropbox, AWS S3).

Mistral OCR is a super convenient way to parse and extract data from multi-page PDFs or single images using AI. What makes it special and differs it from the competition is that Mistral OCR also performs document page splitting and markdown conversion. This helps reduce dependencies required for document parsing workflows where tools like StirlingPDF. Read the official documentation on Mistral OCR API here: https://docs.mistral.ai/capabilities/document/#tag/ocr/operation/ocr_v1_ocr_post How it works To access Mistral-OCR, you'll need to use Mistral Cloud API via the HTTP request node Mistral OCR can only accept 2 file types: PDF and Image. Here, we use 2 different request to the Mistral-OCR API to parse a bank statement PDF and an screenshot of a bank statement to extract the tables. Next, we explore a more secure method of uploading documents to the Mistral OCR API by using Mistral's cloud storage. In example 2, we first store a copy of our documents to Mistral cloud and then generate a signed URL to retreive the file before sending it to Mistral OCR. This ensures the file is not accessible publicly and protects it from unauthorised access. Finally, another way to use Mistral-OCR is via document understanding. This allows you to ask questions about the document rather than extract contents from it. In example 3, I demonstrate this use-case asking Mistral-small to tell me how many deposits are shown in the bank statement. How to use Ensure your documents are either publicly accessible for Mistral-OCR or upload them to Mistral Cloud. Alternatively, signed urls from AWS S3 or Cloudflare R2 should also work. Requirements Mistral Cloud account and API Key. You'll also need credit on your account to use Mistral-OCR. Customising the workflow Mistral-OCR also works for images such as charts and diagrams so try using it on Financial Reports. Mistral-OCR is even cheaper with batching enabled. This returns your results within 24hrs but is half the price per page.

This workflow automates document summarization directly from Google Drive, processes the content using Mistral AI, and delivers a clean, styled summary via Gmail. It's ideal for professionals who need quick insights from lengthy documents without manually reading through them. ✅ Key Features: Google Drive Integration: Fetches a file (PDF/DOCX) from your Drive. AI Summarization: Uses Mistral AI to extract key points efficiently. Styled Email Output: Delivers a formatted, easy-to-read summary to your inbox with a timestamp. Error Handling: Built to skip corrupted files or missing credentials. 🔧 Nodes Breakdown: 1️⃣ Manual Trigger — Starts the workflow manually for easy testing. 2️⃣ Google Drive Node — Downloads a specified file from Google Drive (supports PDF/DOCX). 3️⃣ Mistral Cloud Chat Model Node — Connects to Mistral AI for summarization. 4️⃣ Summarization Chain Node — Breaks the file into chunks, processes content, and generates a concise summary. 5️⃣ Gmail Node — Sends the styled summary directly to the user’s inbox, with custom formatting and current time in the Lagos timezone. Extra Features: Dynamic Time Formatting: Supports Lagos timezone (easily adjustable). HTML Styling: Beautiful email formatting with headers, icons, and line breaks for clarity. Custom Email Sender Name: Branded output (e.g., "Swot.AI"). Future Expansion: Can extend to WhatsApp or Slack with minor tweaks. Use Cases: Legal teams summarizing contracts. Content creators extracting highlights from research papers. Business analysts getting insights from reports on-the-go. Customization Tips: Change the timezone (Africa/Lagos) to match your preferred location. Add error-handling nodes for missing files or API failures. Swap Mistral AI with OpenAI for different summarization behavior. Why To Use This Workflow? This automation saves hours of manual reading. It’s perfect for personal productivity, legal analysis, content creation, or business reporting. With clean formatting and a professional email summary — your team will get instant insights in seconds!

This workflow automates the backup of your n8n workflows data to Google Drive every day. It ensures that important configurations and execution logs are securely stored, reducing the risk of data loss and improving workflow resilience. 🔹 Why Use This? ✅ Automates routine backups effortlessly. ✅ Reduces manual intervention and potential data loss. ✅ Securely stores critical workflow configurations in Google Drive. With this workflow, you can focus on innovation while n8n takes care of your backups. 🔐✨ 🚀 How It Works This workflow operates seamlessly with a combination of scheduled triggers, JSON data transformation, and secure cloud storage. 🛠 Setup Steps Trigger the backup – Choose between manual execution or automated scheduling at 1:30 AM daily. Data preparation – Your workflow parameters define the backup location and organize files effectively. Transformation & Encoding – The data is processed and converted into a JSON file in base64 format. Cloud Storage – The backup is securely uploaded to your designated Google Drive folder. 🔧 Customization Options You can modify various aspects of the backup workflow to better suit your needs: 1️⃣ Adjusting Backup Frequency By default, the workflow runs daily at 1:30 AM. To change this: Open the Trigger Node in n8n. Modify the Cron Expression or select a different frequency (e.g., hourly, weekly, or custom intervals). 2️⃣ Selecting Specific Workflows to Backup Instead of backing up all workflows, you can filter which ones to include: Add a Filter Node before exporting data. Define specific workflow IDs or names to include in the backup. 3️⃣ Changing the Backup Destination The default destination is Google Drive, but you can change this: Replace the Google Drive Node with a different storage provider (e.g., Dropbox, AWS S3, or local storage via FTP/SFTP). Configure authentication for the new destination. 4️⃣ Modifying Data Format By default, the workflow stores data in JSON format. If you need a different format: Convert JSON to CSV using the Spreadsheet File Node. Store backups in a compressed format (ZIP) by adding a Compression Node. 5️⃣ Encrypting the Backup for Extra Security For added protection: Use the Crypto Node to encrypt the JSON file before uploading. Set up an Access-Controlled Folder in Google Drive with limited permissions. ✅ Verify That Your Backup Works Before relying on this workflow for your automated backups, make sure it works correctly by performing a quick test: Manually trigger the workflow in n8n and check if the backup file appears in your Google Drive. Open Google Drive, navigate to the backup folder, and download the JSON file. Verify its content by checking if the data matches your workflow’s execution logs. Try to import the JSON file back into n8n using the “Import File” function to ensure the workflow structure is intact. Alternatively, copy and paste a test file into Google Drive and confirm that it appears correctly in your workflow logs. This quick test will confirm that your backup is running smoothly and that your data is retrievable whenever needed. 📁 How to Find Your Google Drive Directory ID To ensure that the backup is uploaded to the correct folder, you need to retrieve your Google Drive Directory ID. Follow these simple steps: Open Google Drive. Navigate to the folder where you want to store your backups. Click on the folder and check the URL in your browser. The Directory ID is the long string of characters at the end of the URL after /folders/. Example: 📌 If your folder URL is: https://drive.google.com/drive/folders/14oUlH_LW_NT0Xb2woZWvuzRncV-bhla Then, your Directory ID is: 14oUlH_LW_NT0Xb2woZWvuzRncV-bhla Copy this Directory ID and use it in the workflow's parameters to ensure the backup is saved in the correct location. Phil | Inforeole

Who is this for? Content creators, digital marketers, and social media managers who want to automate the creation of short-form videos for platforms like TikTok, YouTube Shorts, and Instagram Reels without extensive video editing skills. What problem does this workflow solve? Creating engaging short-form videos consistently is time-consuming and requires multiple tools and skills. This workflow automates the entire process from ideation to publishing, significantly reducing the manual effort needed while maintaining content quality. What this workflow does This all-in-one solution transforms ideas into fully produced short-form videos through a 5-step process: Generate video captions from ideas stored in a Google Sheet Create AI-generated images using Flux and the OpenAI API Convert images to videos using Kling's API Add voice-overs to your content with Eleven Labs Complete the video production with Creatomate by adding templates, transitions, and combining all elements The workflow handles everything from sourcing content ideas to rendering the final video, and even notifies you on Discord when videos are ready. Setup (Est. time: 20-30 minutes) Before getting started, you'll need: n8n installation (tested on version 1.81.4) OpenAI API Key (free trial credits available) PiAPI (free trial credits available) Eleven Labs (free account) Creatomate API Key (free trial credits available) Google Sheets API enabled in Google Cloud Console Google Drive API enabled in Google Cloud Console OAuth 2.0 Client ID and Client Secret from your Google Cloud Console Credentials How to customize this workflow to your needs Adjust the Google Sheet structure to include additional data like video length, duration, style, etc. Modify the prompt templates for each AI service to match your brand voice and content style Update the Creatomate template to reflect your visual branding Configure notification preferences in Discord to manage your workflow This workflow combines multiple AI technologies to create a seamless content production pipeline, saving you hours of work per video and allowing you to focus on strategy rather than production.

Social Media Content Publishing Factory for Streamlined Content Creation Across Platforms Who is this for? This workflow is designed for content creators, social media managers, and marketing teams who need to efficiently create and publish content across multiple social media platforms. It's perfect for businesses looking to maintain a consistent presence across X (Twitter), Instagram, Facebook, LinkedIn, Threads, and YouTube Shorts without spending hours crafting platform-specific content manually. What problem is this workflow solving? Creating tailored content for different social media platforms is time-consuming and requires understanding each platform's unique requirements and audience expectations. This workflow solves the challenge of: Maintaining consistent messaging across platforms while respecting platform-specific formats Generating optimized content that follows best practices for each platform Creating accompanying visuals without graphic design skills Streamlining the approval process before publishing Reducing the time spent on repetitive content creation tasks What this workflow does This automated content factory takes your content idea and transforms it into platform-optimized posts for all major social media channels. The workflow: Accepts your content idea or topic through a chat interface Leverages AI to generate tailored content for each platform (X/Twitter, Instagram, Facebook, LinkedIn, Threads, YouTube Shorts) Creates appropriate images using AI image generation Sends content for approval via email before publishing Publishes approved content to selected platforms Maintains chat memory to improve future content generation Setup Connect your social media platform credentials (X/Twitter, Instagram, Facebook, LinkedIn) Set up your email account for the approval process Configure your OpenAI API key for AI content generation Update the image generation service credentials (Pollinations.ai is used by default) Customize the system prompts and schemas in the Google Docs nodes with your brand voice and content requirements How to customize this workflow to your needs Modify the system prompts in the Google Docs nodes to match your brand voice and content strategy Adjust the social media schemas to include specific fields relevant to your content Update the approval process to include additional stakeholders if needed Add or remove social media platforms based on your marketing strategy Customize the image generation prompts to better match your visual branding Integrate with your existing content calendar or CRM systems This workflow eliminates the need to manually craft different versions of the same content for each platform, saving hours of work while ensuring your social media presence remains consistent and optimized for maximum engagement.

Transcript Evalu8r – AI-Powered Transcribing and Transcript Analysis Workflow Overview Transcript Evalu8r is an AI-powered transcript analysis workflow that automates the processing, visualization, and evaluation of transcribed conversations. This n8n workflow template is designed to help users quickly analyze sentiment, extract topics and intents, generate key insights, and enhance transcript navigation. It is ideal for customer service teams, legal professionals, researchers, content creators, and businesses seeking actionable intelligence from recorded conversations. Key Features 🔹 Automated Transcript Processing Audio-to-Text Conversion** – Upload an audio file and generate transcripts. File Upload Management** – Track file uploads with real-time progress indicators. Transcript Selection** – Browse and select previously analyzed transcripts from a dropdown. Download Transcripts* – Export transcripts in various formats (Google Docs and JSON*). Error Handling** – Detects and alerts users about upload or processing failures. 🔹 Advanced UI Components Interactive Transcript Viewer** – Displays full transcripts with: Timestamps and speaker identification. Clickable words for easy navigation. Auto-scrolling to highlight the active portion of the transcript. Key Points & Action Items Summary** – AI extracts: Critical insights from conversations. Actionable follow-ups detected in the discussion. Speaker Labeling* – Dynamically assigns *real speaker names** instead of generic placeholders (e.g., "Speaker 1"). Collapsible Sections* – Enables users to *expand/collapse** transcript details, key insights, and analysis sections. 🔹 AI-Powered Conversation Analysis Sentiment Analysis & Visualization** Dynamic sentiment graph tracks emotional shifts. Color-coded speaker sentiment tracking: 🔵 Positive ⚫ Neutral 🔴 Negative Time-based sentiment tracking – Shows sentiment fluctuations across the conversation. Topic & Intent Recognition** Automated Topic Extraction – Identifies key themes discussed. Hierarchical Topic Organization – Groups related topics for structured insights. Intent Classification – Recognizes whether statements reflect: Questioning Commands Decision-making Information seeking Confidence Scoring – Displays confidence levels for topic and intent detection. Speaker Contribution Metrics** Talk-time percentages per speaker. Interruption detection – Highlights moments where speakers cut each other off. Word Frequency Analysis – Identifies commonly used terms and phrases. 🔹 Seamless Workflow Automation API Integration* – Connects with transcription engines like *OpenAI Whisper, AWS Transcribe, and Deepgram**. Webhook Support** – Automates workflows when new transcripts are available. Batch Processing* – Handles *multiple transcript analyses** simultaneously. Export & Reporting** – Sends insights to Google Sheets, Notion, Airtable, or Slack. How It Works Upload an audio file or select a pre-existing transcript. Transcript Processing: Speech-to-text conversion (if required). AI-driven sentiment, topic, and intent analysis. Visualizations & Insights: Review sentiment charts, speaker contributions, and key topics. Extract action items and critical takeaways. Download results or trigger automated follow-ups. Use Cases ✅ Customer Support Review – Detect customer concerns and analyze sentiment trends. ✅ Podcast & Video Content Analysis – Summarize episodes and extract key themes. ✅ Sales Call Insights – Identify common objections and customer pain points. ✅ Market Research – Extract trends from focus groups and discussions. ✅ Legal Compliance Monitoring – Track policy violations in recorded conversations. Setup Instructions Import the Transcript Evalu8r workflow into your n8n instance. Connect DeepGram Speech to Text API. Configure workflow parameters (sentiment thresholds, topic extraction settings). Run the workflow to analyze and visualize transcript data. Review insights and export as needed. Why Use Transcript Evalu8r? 🚀 Automate tedious transcript analysis 💡 Unlock hidden insights in conversations 📊 Visualize conversations with interactive sentiment tracking ⚡ Boost efficiency with AI-powered automation 🔗 Seamlessly integrate with your existing workflows Requirements n8n instance** (cloud or self-hosted) API key for DeegGram API

Who is this for? This workflow is perfect for anyone looking to automate the process of replacing variables in Google Docs with data from form. What problem does this workflow solve? This workflow automates the process of filling Google Docs templates with data coming from n8n forms or other variables. It’s especially useful for generating documents like contracts, invoices, or reports quickly and efficiently without manual intervention. What does this workflow do? The workflow receives data from a form in n8n. It uses the form data to replace the corresponding variables (e.g., {{example_variable}}) in a Google Docs template. The document is then generated with the new values, ready for further use, such as sending or archiving. How to set up this workflow? Prepare the template: Create a Google Docs template with variables in the {{variable}} format that you want to replace with form data. Modify the variables in the n8n form: Make sure the form fields correspond to the variables you want to replace in the Google Docs template. Connect to Google Docs: Set up the connection to Google Docs in n8n using the appropriate authentication credentials. Test the workflow: Run the workflow to ensure that the form data correctly replaces the variables in the Google Docs template. How to customize this workflow to your needs? Change the data source: You can modify the form or other data sources (e.g., API) from which the replacement values will be fetched. Customize the Google Docs template: Adapt the template to include additional fields for replacement as needed. Integrate with other applications: You can expand the workflow to include actions like sending the generated document via email, saving it to Google Drive, or passing it to other systems.

Who is this for? Content creators, social media managers, digital marketers, and researchers who need to download original TikTok videos without watermarks for analysis, repurposing, or archiving purposes. What problem does this workflow solve? Downloading TikTok videos without watermarks typically requires using questionable third-party websites that may have limitations, ads, or privacy concerns. This workflow provides a clean, automated solution that can be integrated into your own systems and processes. What this workflow does This workflow automates the process of downloading TikTok videos without watermarks in three simple steps: Fetch the TikTok video page by providing the video URL Extract the raw video URL from the page's HTML data Download the original video file without watermark (Optional) Upload to Google Drive with public sharing link generation The workflow uses web scraping techniques to extract the original video source directly from TikTok's own servers, maintaining the highest possible quality without any added watermarks or branding. Setup (Est. time: 5-10 minutes) Before getting started, you'll need: n8n installation The URL of a TikTok you want to download (Optional) Google Drive API enabled in Google Cloud Console with OAuth Client ID and Client Secret credentials if you want to use the upload feature How to customize this workflow to your needs Replace the example TikTok URL with your desired video links Modify the file naming convention for downloaded videos Integrate with other nodes to process videos after downloading Create a webhook to trigger the workflow from external applications Set up a schedule to regularly download videos from specific accounts This workflow can be extended to support various use cases like trending content analysis, competitor research, creating compilation videos, or building a content library for inspiration. It provides a foundation that can be customized to fit into larger automated workflows for content creation and social media management.

ideoGener8r – Self-Hosted Ideogram AI Interface in n8n 🔥 March Sale – n8n Community Members Get ideoGener8r for Just $27! (Reg. $47) Use Coupon Code: ILoven8n (Valid until 3/31/2025 for n8n community members) ideoGener8r is an n8n template that sets up a self-contained, front-end interface for Ideogram AI image generation. It offers a complete workflow to generate, upscale, remix, and store images—entirely on your self-hosted n8n instance. Key Benefits & Limited-Time Offer Fully Self-Hosted**: Avoid monthly fees and keep your data private. All-in-One**: Generate, remix, and upscale images without third-party tools. Streamlined Automation**: Integrates directly with Google Sheets & Drive. Sale: **Save $20 – Get ideoGener8r for just $27 with coupon code ILoven8n (valid until 3/31/2025). Requirements & Overview Ideogram AI API Key Sign up at Ideogram AI and create an API key. Google Sheets & Drive A Google Sheet for storing metadata. A Google Drive folder for saving generated images. n8n Auth Credentials Basic Auth for the login webhook. Header Auth (Bearer token) for the generation/remix webhooks. With ideoGener8r, you can instantly create a private user interface—within n8n—to produce AI images on demand, trigger image generation through webhooks, and automatically log data to Google Sheets. Required Google Sheet Columns Your Google Sheet must contain (at minimum) the following columns for proper logging: Cheeck Setup note in workflow for csv template Step-by-Step Setup Instructions Import the Template Download the JSON file you received upon purchase. In your n8n instance, go to Workflows → Import, then upload the JSON file. Configure Ideogram API In n8n, create an HTTP Header Auth credential. For the “Authorization” header, use Bearer YOUR_IDEOGRAM_API_KEY. Attach this credential to the Ideogram-related nodes (e.g., IDEOGRAM Image generator, ideogram Upscale). Google Sheets Setup Copy or create a Google Sheet with the columns listed above. In the template, locate the Google Sheets “Append” nodes. Select the correct Sheet, tab, and map each column accordingly. Google Drive Folder Create a Drive folder to store images (sharing permissions are up to you). In the Google Drive nodes, enter the folder ID to save new images there. Basic Auth for Login Open the Login Webhook-ideoGener8r node. Set it to use Basic Auth and create credentials for a username/password. This will secure the login route (e.g., /ideogener8r-login). Bearer Token for Generation & History Open the “Generation Webhook” (e.g., /ideogen) and “History Webhook” (e.g., /ideogener8r-history). Set them to Header Auth and use Authorization: Bearer <YOUR_SECRET_TOKEN>. Any requests to these endpoints must include that token in the header. Publish & Test Activate or publish your workflow. Go to /ideogener8r-login, enter your Basic Auth credentials, and test by generating images. Verify that images appear in your Google Drive folder, and the metadata is logged in the Google Sheet. Ideogram API Details Endpoint**: The template uses Ideogram’s /generate, /upscale, and /remix endpoints. Headers**: You must provide your API key as a Bearer token in the request header. Rate Limits**: Check your Ideogram AI account for any usage or rate-limiting policies. More info at ideoGener8r.com

AI-Powered Tech Radar Advisor This project is built on top of the famous open source ThoughtWorks Tech Radar. You can use this template to build your own AI-Powered Tech Radar Advisor for your company or group of companies. Target Audience This template is perfect for: Tech Audit & Governance Leaders:** Those seeking to build a tech landscape AI platform portal. Tech Leaders & Architects:** Those aiming to provide modern AI platforms that help others understand the rationale behind strategic technology adoption. Product Managers:** Professionals looking to align product innovation with the company's current tech trends. IT & Engineering Teams:** Teams that need to aggregate, analyze, and visualize technology data from multiple sources efficiently. Digital Transformation Experts:** Innovators aiming to leverage AI for actionable insights and strategic recommendations. Data Analysts & Scientists:** Individuals who want to combine structured SQL analysis with advanced semantic search using vector databases. Developers:** Those interested in integrating RAG chatbot functionality with conversation storage. 1. Description Tech Constellation is an AI-powered Tech Radar solution designed to help organizations visualize and steer their technology adoption strategy. It seamlessly ingests data from a Tech Radar Google Sheet—converting it into both a MySQL database and a vector index—to consolidate your tech landscape in one place. The platform integrates an interactive AI chat interface powered by four specialized agents: AI Agent Router:** Analyzes and routes user queries to the most suitable processing agent. SQL Agent:** Executes precise SQL queries on structured data. RAG Agent:** Leverages semantic, vector-based search for in-depth insights. Output Guardrail Agent:** Validates responses to ensure they remain on-topic and accurate. This powerful template is perfect for technology leaders, product managers, engineering teams, and digital transformation experts looking to make data-driven decisions aligned with strategic initiatives across groups of parent-child companies. 2. Features Data Ingestion A Google Sheet containing tech radar data is used as the primary source. The data is ingested and converted into a MySQL database. Simultaneously, the data is indexed into a vector database for semantic (vector-based) search. Interactive AI Chat Chat Integration:** An AI-powered chat interface allows users to ask questions about the tech radar. Customizable AI Agents:** AI Agent Router: Determines the query type and routes it to the appropriate agent. SQL Agent: Processes queries using SQL on structured data. RAG Agent: Performs vector-based searches on document-like data. Output Guardrail Agent: Validates queries and ensures that the responses remain on-topic and accurate. Usage Examples Tell me, is TechnologyABC adopted or on hold, and why? List all the tools that are considered part of the strategic direction for company3 but are not adopted. Project Links & Additional Details GitHub Repository (Frontend Interface Source Code):** github.com/dragonjump/techconstellation Try It:** https://scaler.my

AI Story Generator with GPT-4o and Google Drive Integration Automatically generate complete stories with GPT-4o and seamlessly save them to Google Drive. Who is this for? Creative writers and authors Marketing and sales professionals Educators and content creators Fan fiction enthusiasts Anyone interested in automating storytelling with AI What problem is this workflow solving? Manually creating engaging, structured narratives can be time-consuming. Writers and content creators often struggle to maintain consistency, depth, and engaging storytelling structure. This workflow solves these challenges by automating story creation using advanced AI (GPT-4o) and proven storytelling techniques. What this workflow does This n8n automation generates comprehensive stories through an iterative AI-driven process: Step 1: Provide Your Story Idea Users input a clear description and specify their desired story format (short story, fan fiction, sales email, etc.). Step 2: AI-Driven Analysis GPT-4o analyzes the provided idea, categorizes the story, selects relevant storytelling frameworks inspired by PipDeck Storyteller Tactics, and determines narrative tone and direction. Step 3: Story and Character FoundationEstablishes core themes, emotional hooks, and detailed character backgrounds. Step 4: Initial Story Development Creates a structured plot outline including engaging elements such as hooks, twists, and resolutions. Step 5: Iterative Enhancement Refines the story through multiple automated prompts, improving narrative depth, character development, dialogue, and realism. Step 6: Editorial Feedback Generates automated critiques highlighting clichés, weak dialogues, and areas for improvement. Step 7: Final Polished Version Incorporates editorial feedback to produce a complete, polished, ready-to-use narrative. Step 8: Instant Google Drive OrganizationAutomatically saves the final story directly to your specified Google Drive folder for easy access and management. Setup Instructions Prerequisites: n8n account (cloud or self-hosted) GPT-4o API access via OpenAI Google Drive account Configure OpenAI Node: Add your GPT-4o API key in the OpenAI node settings. Configure Google Drive Node: Connect your Google Drive account by authenticating with n8n. Specify the folder where generated stories should be saved. Test Workflow: Run the workflow with a simple story prompt to ensure proper setup. How to Customize this Workflow Adjust Prompt Details: Modify AI prompt instructions to suit your specific story style and audience. Expand or Narrow Iterations: Change the number of iterations to balance between speed and story complexity. Customize Feedback Level: Adjust the level of editorial feedback provided. Dependencies and Requirements GPT-4o API from OpenAI Google Drive integration enabled in n8n Get Started Download and deploy this template today to streamline your storytelling process and produce consistently engaging, high-quality content effortlessly.

Introduction The "Automatic Weekly Digital PR Stories Suggestions" workflow is a sophisticated automated system designed to identify trending news stories on Reddit, analyze public sentiment through comment analysis, extract key information from source articles, and generate strategic angles for potential digital PR campaigns. This workflow leverages the power of social media trends, natural language processing, and AI-driven analysis to deliver curated, sentiment-analyzed news opportunities for PR professionals. Operating on a weekly schedule, the workflow searches Reddit for posts related to specified topics, filters them based on engagement metrics, and performs a deep analysis of both the content and public reaction. It then generates comprehensive reports that include story opportunities, audience insights, and strategic recommendations. These reports are automatically compiled, stored in Google Drive, and shared with team members via Mattermost for immediate collaboration. This workflow solves the time-consuming process of manually monitoring social media for trending stories, analyzing public sentiment, and identifying PR opportunities. By automating these tasks, PR professionals can focus on strategy development and execution rather than spending hours on research and analysis. Who is this for? This workflow is designed for digital PR professionals, content marketers, communications teams, and media relations specialists who need to stay on top of trending stories and public sentiment to develop timely and effective PR campaigns. It's particularly valuable for: PR agencies managing multiple clients across different industries In-house PR teams needing to identify media opportunities quickly Content marketers looking for trending topics to create timely content Communications professionals monitoring public perception of industry news Users should have basic familiarity with n8n workflows and the PR strategy development process. While technical knowledge of the integrated APIs is not required to use the workflow, some understanding of Reddit, sentiment analysis, and PR campaign development would be beneficial for interpreting and acting on the generated reports. What problem is this workflow solving? Digital PR professionals face several challenges that this workflow addresses: Information Overload: Manually monitoring social media platforms for trending stories is time-consuming and often results in missed opportunities. Sentiment Analysis Complexity: Understanding public perception of news stories requires reading through hundreds of comments and identifying patterns, which is labor-intensive and subjective. Content Extraction: Visiting multiple news sources to read and analyze articles takes significant time. Strategic Angle Development: Identifying unique PR angles that leverage trending stories and public sentiment requires synthesizing large amounts of information. Team Collaboration: Sharing findings and insights with team members in a structured format can be cumbersome. By automating these processes, the workflow enables PR professionals to quickly identify trending stories with PR potential, understand public sentiment, and develop strategic angles based on comprehensive analysis, all while maintaining a structured approach to team collaboration. What this workflow does Overview The workflow automatically identifies trending posts on Reddit related to specified topics, analyzes both the content of linked articles and public sentiment from comments, and generates comprehensive PR strategy reports. These reports include story opportunities, audience insights, and strategic recommendations based on the analysis. The final reports are compiled, stored in Google Drive, and shared with team members via Mattermost. Process Topic Selection and Reddit Search: The workflow starts with a list of topics specified in the "Set Data" node It searches Reddit for posts related to these topics Posts are filtered based on upvotes and other criteria to focus on trending content Comment Analysis: For each post, the workflow retrieves comments It extracts the top 30 comments based on score Using Claude AI, it analyzes the comments to understand: Overall sentiment Dominant narratives Audience insights PR implications Content Analysis: The workflow extracts the content of the linked article using Jina AI It analyzes the content to identify: Core story elements Technical aspects Narrative opportunities Viral elements PR Strategy Development: Based on the combined analysis of comments and content, the workflow generates: First-mover story opportunities Trend-amplifier story ideas Priority rankings Execution roadmap Strategic recommendations Report Generation and Distribution: The workflow compiles comprehensive reports for each post Reports are converted to text files All files are compressed into a ZIP archive The archive is uploaded to Google Drive A link to the archive is shared with team members via Mattermost Setup To set up this workflow, follow these steps: Import the Workflow: Download the workflow JSON file Import it into your n8n instance Configure API Credentials: Reddit: Add a new credential "Reddit OAuth2 API" by following the guide at https://docs.n8n.io/integrations/builtin/credentials/reddit/ Anthropic: Add a new credential "Anthropic Account" by following the guide at https://docs.n8n.io/integrations/builtin/credentials/anthropic/ Google Drive: Add a new credential "Google Drive OAuth2 API" by following the guide at https://docs.n8n.io/integrations/builtin/credentials/google/oauth-single-service/ Configure the "Set Data" Node: Set your interested topics (one per line) Add your Jina API key (obtain from https://jina.ai/api-dashboard/key-manager) Configure the Mattermost Node: Update your Mattermost instance URL Set your Webhook ID and Channel Follow the guide at https://developers.mattermost.com/integrate/webhooks/incoming/ for webhook setup Adjust the Schedule (Optional): The workflow is set to run every Monday at 6am Modify the "Schedule Trigger" node if you need a different schedule Test the Workflow: Run the workflow manually to ensure all connections are working properly Check the output to verify the reports are being generated correctly How to customize this workflow to your needs This workflow can be customized in several ways to better suit your specific requirements: Topic Selection: Modify the topics in the "Set Data" node to focus on industries or subjects relevant to your PR strategy Add multiple topics to cover different client interests or market segments Filtering Criteria: Adjust the "Upvotes Requirement Filtering" node to change the minimum upvotes threshold Modify the filtering conditions to include or exclude certain types of posts Analysis Parameters: Customize the prompts in the "Comments Analysis," "News Analysis," and "Stories Report" nodes to focus on specific aspects of the content or comments Adjust the temperature settings in the Anthropic Chat Model nodes to control the creativity of the AI responses Report Format: Modify the "Set Final Report" node to change the structure or content of the final reports Add or remove sections based on your specific reporting needs Distribution Method: Replace or supplement the Mattermost notification with email notifications, Slack messages, or other communication channels Add additional storage options beyond Google Drive Schedule Frequency: Change the "Schedule Trigger" node to run the workflow more or less frequently Set up multiple triggers for different topics or clients Integration with Other Systems: Add nodes to integrate with your CRM, content management system, or project management tools Create connections to automatically populate content calendars or task management systems

This workflow automates the process of analyzing emails and their attachments (PDFs and images) using AI models (DeepSeek, Gemini, and OpenRouter). It extracts and summarizes the content of emails and attachments, saves the summaries to Google Sheets, and sends a final consolidated summary via Telegram. This is a powerful tool for automating email analysis and summarization, saving time and ensuring that important information is easily accessible and actionable. Below is a breakdown of the workflow: 1. How It Works The workflow is designed to process incoming emails, analyze their content and attachments, and generate summaries. Here's how it works: Email Trigger: The workflow starts with the Email Trigger (IMAP) node, which monitors an email inbox for new emails. If an email contains attachments, the workflow processes them. Check for Attachments: The Contain Attachments? node checks if the email has attachments. If attachments are present, the workflow proceeds to process them. Process Attachments: The Get PDF and Images Attachments node extracts PDF and image attachments from the email. The Switch node separates PDFs and images for further processing: PDFs: The Extract from PDF node extracts text from PDFs, and the PDF Analyzer node summarizes the content. Images: The Analyze Image node uses AI to describe the content of images. Summarize Email Content: The Convert Text node converts the email's HTML content to plain text. The Email Summarization Chain node uses AI to generate a summary of the email's text content. Save Summaries: The Save Summary PDF, Save Summary Image, and Save Summary Text nodes save the summaries of PDFs, images, and email text, respectively, to Google Sheets. Consolidate Summaries: The All Summaries node aggregates the summaries of the email text, PDFs, and images. The Create Final Summary node uses AI to generate a unified summary of all the content. Send Final Summary: The Send Final Summary node sends the consolidated summary via Telegram to a specified chat ID. 2. Set Up Steps To set up and use this workflow in n8n, follow these steps: IMAP Configuration: Set up IMAP credentials in n8n for the Email Trigger (IMAP) node. Ensure the email account is accessible via IMAP. AI Model Configuration: Configure the DeepSeek, Gemini, and OpenRouter credentials in n8n for the Email Summarization Chain, PDF Analyzer, and Create Final Summary nodes. Ensure the AI models are set up to generate summaries. Google Sheets Integration: Set up Google Sheets credentials in n8n for the Save Summary PDF, Save Summary Image, and Save Summary Text nodes. Specify the Google Sheet and worksheet where the summaries will be saved. Telegram Integration: Set up Telegram credentials in n8n for the Send Final Summary node. Insert your Chat ID in the Telegram node to receive the final summary. Test the Workflow: Send an email with attachments (PDFs and images) to the monitored email account. The workflow will: Extract and summarize the email content and attachments. Save the summaries to Google Sheets. Send a consolidated summary via Telegram. Optional Customization: replace IMAP trigger with Gmail or Outlook trigger Modify the workflow to include additional features, such as: Adding more AI models for different types of analysis. Sending notifications via other channels (e.g., Slack, email). Integrating with other storage services (e.g., Dropbox, AWS S3). Need help customizing? Contact me for consulting and support or add me on Linkedin.

Objective This workflow automatically imports product images from Google Drive and associates them with templates and products in Odoo.

Compare Local Ollama Vision Models for Image Analysis using Google Docs Process images using locally hosted Ollama Vision Models to extract detailed descriptions, contextual insights, and structured data. Save results directly to Google Docs for efficient collaboration. Who is this for? This workflow is ideal for developers, data analysts, marketers and AI enthusiasts who need to process and analyze images using locally hosted Ollama Vision Language Models. It’s particularly useful for tasks requiring detailed image descriptions, contextual analysis, and structured data extraction. What problem is this workflow solving? / Use Case The workflow solves the challenge of extracting meaningful insights from images in exhaustive detail, such as identifying objects, analyzing spatial relationships, extracting textual elements, and providing contextual information. This is especially helpful for applications in real estate, marketing, engineering, and research. What this workflow does This workflow: Downloads an image file from Google Drive. Processes the image using multiple Ollama Vision Models (e.g., Granite3.2-Vision, Gemma3, Llama3.2-Vision). Generates detailed markdown-based descriptions of the image. Saves the output to a Google Docs file for easy sharing and further analysis. Setup Ensure you have access to a local instance of Ollama. https://ollama.com/ Pull the Ollama vision models. Configure your Google Drive and Google Docs credentials in n8n. Provide the image file ID from Google Drive in the designated node. Update the list of Ollama vision models Test the workflow by clicking ‘Test Workflow’ to trigger the process. How to customize this workflow to your needs Replace the image source with another provider if needed (e.g., AWS S3 or Dropbox). Modify the prompts in the "General Image Prompt" node to suit specific analysis requirements. Add additional nodes for post-processing or integrating results into other platforms like Slack or HubSpot. Key Features: Detailed Image Analysis**: Extracts comprehensive details about objects, spatial relationships, text elements, and contextual settings. Multi-Model Support**: Utilizes multiple vision models dynamically for optimal performance. Markdown Output**: Formats results in markdown for easy readability and documentation. Google Drive Integration**: Seamlessly downloads images and saves results to Google Docs.

Overview This workflow automatically saves files received via LINE Messaging API into Google Drive and logs the file details into a Google Sheet. It checks the file type against allowed types, organizes files into date-based folders and (optionally) file type–specific subfolders, and sends a reply message back to the LINE user with the file URL or an error message if the file type is not permitted. Who is this for? Developers & IT Administrators: Looking to integrate LINE with Google Drive and Sheets for automated file management. Businesses & Marketing Teams: That want to automatically archive media files and documents received from users via LINE. Anyone Interested in No-Code Automation: Users who want to leverage n8n’s capabilities without heavy coding. What Problem Does This Workflow Solve? Automated File Organization: Files received from LINE are automatically checked for allowed file types, then stored in a structured folder hierarchy in Google Drive (by date and/or file type). Data Logging: Each file upload is recorded in a Google Sheet, providing an audit trail with file names, upload dates, URLs, and types. Instant Feedback: Users receive an immediate reply via LINE confirming the file upload, or an error message if the file type is not allowed. What This Workflow Does 1. Receives Incoming Requests: A webhook node ("LINE Webhook Listener") listens for POST requests from LINE, capturing file upload events and associated metadata. 2. Configuration Loading: A Google Sheets node ("Get Config") reads configuration data (e.g., parent folder ID, allowed file types, folder organization settings, and credentials) from a pre-defined sheet. Data Merging & Processing: The "Merge Event and Config Data" and "Process Event and Config Data" nodes merge and structure the event data with configuration settings. A "Determine Folder Info" node calculates folder names based on the configuration. If Store by Date is enabled, it uses the current date (or a specified date) as the folder name. If Store by File Type is also enabled, it uses the file’s type (e.g., image) for a subfolder. 4. Folder Search & Creation: The workflow searches for an existing date folder ("Search Date Folder"). If the date folder is not found, an IF node ("Check Existing Date Folder") routes to a "Create Date Folder" node. Similarly, for file type organization, the workflow uses a "Search FileType Folder" node (with appropriate conditions) to look for a subfolder, or creates it if not found. The "Set Date Folder ID" and "Set Image Folder ID" nodes capture and merge the resulting folder IDs. Finally, the "Config final ParentId" node sets the final target folder ID based on the configuration conditions: Store by Date: TRUE, Store by File Type: TRUE: Use the file type folder (inside the date folder). Store by Date: TRUE, Store by File Type: FALSE: Use the date folder. Store by Date: FALSE, Store by File Type: TRUE: Use the file type folder. Store by Date: FALSE, Store by File Type: FALSE: Use the Parent Folder ID from the configuration. 5. File Retrieval and Validation: A HTTP Request node ("Get File Binary Content") fetches the file’s binary data from the LINE API. A Function node ("Validate File Type") checks if the file’s MIME type is included in the allowed list (e.g., "audio|image|video"). If not, it throws an error that is captured for the reply. 6. File Upload and Logging: The "Upload File to Google Drive" node uploads the validated binary file to the final target folder. After a successful upload, the "Log File Details to Google Sheet" node logs details such as file name, upload date, Google Drive URL, and file type into a designated Google Sheet. 7. User Feedback: The "Check Reply Enabled Flag" node checks if the reply feature is enabled. Finally, the "Send LINE Reply Message" node sends a reply message back to the LINE user with either the file URL (if the upload was successful) or an error message (if the file type was not allowed). Setup Instructions 1. Google Sheets Setup: Create a Google Sheet with two sheets:** config: Include columns for Parent Folder Path, Parent Folder ID, Store by Date (boolean), Store by File Type (boolean), Allow File Types (e.g., “audio|image|video”), CurrentDate, Reply Enabled, and CHANNEL ACCESS TOKEN. fileList: Create headers for File Name, Date Uploaded, Google Drive URL, and File Type. For an example of the required format, check this Google Sheets template: Google Sheet Template 2. Google Drive Credentials: Set up and authorize your Google Drive credentials in n8n. 3. LINE Messaging API: Configure your LINE Developer Console webhook to point to the n8n Webhook URL ("Line Chat Bot" node). Ensure you have the proper Channel Access Token stored in your Google Sheet. 4. n8n Workflow Import: Import the provided JSON file into your n8n instance. Verify node connections and update any credential references as needed. 5. Test the Workflow: Send a test message via LINE to confirm that files are properly validated, uploaded, logged, and that reply messages are sent. How to Customize This Workflow Allowed File Types: Adjust the "Validate File Type" field in your config sheet to control which file types are accepted. Folder Structure: Modify the logic in the "Determine Folder Info" and subsequent folder nodes to change how folders are structured (e.g., use different date formats or add additional categorization). Logging: Update the "Log File Details to Google Sheet" node if you wish to log additional file metadata. Reply Messages: Customize the reply text in the "Send LINE Reply Message" node to include more detailed information or instructions.

This n8n template empowers IT support teams by automating document ingestion and instant query resolution through a conversational AI. It integrates Google Drive, Pinecone, and a Chat AI agent (using Google Gemini/OpenRouter) to transform static support documents into an interactive, searchable knowledge base. With two interlinked workflows—one for processing support documents and one for handling chat queries—employees receive fast, context-aware answers directly from your support documentation. Overview Document Ingestion Workflow Google Drive Trigger:** Monitors a specified folder for new file uploads (e.g., updated support documents). File Download & Extraction:** Automatically downloads new files and extracts text content. Data Cleaning & Text Splitting:** Utilizes a Code node to remove line breaks, trim extra spaces, and strip special characters, while a text splitter segments the content into manageable chunks. Embedding & Storage:** Generates text embeddings using Google Gemini and stores them in a Pinecone vector store for rapid similarity search. Chat Query Workflow Chat Trigger:** Initiates when an employee sends a support query. Vector Search & Context Retrieval:** Retrieves the top relevant document segments from Pinecone based on similarity scores. Prompt Construction:** A Code node combines the retrieved document snippets with the user’s query into a detailed prompt. AI Agent Response:** The constructed prompt is sent to an AI agent (using OpenRouter Chat Model) to generate a clear, step-by-step solution. Key Benefits & Use Case Imagine a large organization where every IT support document—from troubleshooting guides to system configurations—is stored in a single Google Drive folder. When an employee encounters an issue (e.g., “How do I reset my VPN credentials?”), they simply type the query into a chat interface. Instantly, the workflow retrieves the most relevant context from the ingested documents and provides a detailed, actionable answer. This process reduces resolution times, enhances support consistency, and significantly lightens the load on IT staff. Prerequisites A valid Google Drive account with access to the designated folder. A Pinecone account for storing and retrieving text embeddings. Google Gemini* (or *OpenRouter**) credentials to power the Chat AI agent. An operational n8n instance configured with the necessary nodes and credentials. Workflow Details 1 Document Ingestion Workflow Google Drive Trigger Node:** Listens for file creation events in the specified folder. Google Drive Download Node:** Downloads the newly added file. Extract from File Node:** Extracts text content from the downloaded file. Code Node (Data Cleaning):** Cleans the extracted text by removing line breaks, trimming spaces, and eliminating special characters. Recursive Text Splitter Node:** Segments the cleaned text into manageable chunks. Pinecone Vector Store Node:** Generates embeddings (via Google Gemini) and uploads the chunks to Pinecone. 2 Chat Query Workflow Chat Trigger Node:** Receives incoming user queries. Pinecone Vector Store Node (Query):** Searches for relevant document chunks based on the query. Code Node (Context Builder):** Sorts the retrieved documents by relevance and constructs a prompt merging the context with the query. AI Agent Node:** Sends the prompt to the Chat AI agent, which returns a detailed answer. How to Use Import the Template: Import the template into your n8n instance. Configure the Google Drive Trigger: Set the folder ID (e.g., 1RQvAHIw8cQbtwI9ZvdVV0k0x6TM6H12P) and connect your Google Drive credentials. Set Up Pinecone Nodes: Enter your Pinecone index details and credentials. Configure the Chat AI Agent: Provide your Google Gemini (or OpenRouter) API credentials. Test the Workflows: Validate the document ingestion workflow by uploading a sample support document. Validate the chat query workflow by sending a test query and verifying the returned support information. Additional Notes Ensure all credentials (Google Drive, Pinecone, and Chat AI) are correctly set up and tested before deploying the workflows in production. The template is fully customizable. Adjust the text cleaning, splitting parameters, or the number of document chunks retrieved based on your support documentation's size and structure. This template not only enhances IT support efficiency but also offers a scalable solution for managing and leveraging growing volumes of support content.

Context Hey! I'm Samir, a Supply Chain Data Scientist from Paris who spent six years in China studying and working while struggling to learn Mandarin. I know the challenges of mastering a complex language like Chinese and my greatest support was flash cards. Therefore, I designed this workflow to support fellow Mandarin learners by automating flashcard creation using n8n, so they can focus more on learning and less on manual data entry. Who is this template for? This workflow template is designed for language learners and educators who want to automate the creation of flashcards for Mandarin (or any other language) using Google Translate API, an AI agent for phonetic transcription and generating an illustrative sentence and a free image retrieval API. Why? If you use the open-source application Anki, this workflow will help you automatically generate personalized study materials. How? Let us imagine you want to learn how to say the word Contract in Mandarin. The workflow will automatically Translate the word in Simplified Mandarin (Mandarin: 合同). Provide the phonetic transcription (Pinyin: Hétóng) Generate an example sentence (Example: 我们签订了一份合同.) Download an illustrative picture (For example, a picture of a contract signature) All these fields are automatically recorded in a Google Sheet, making it easy to import into Anki and generate flashcards instantly What do I need to start? This workflow can be used with the free tier plans of the services used. It does not require any advanced programming skills. Prerequisite A Google Drive Account with a folder including a Google Sheet API Credentials: Google Drive API, Google Sheets API and Google Translate API activated with OAuth2 credentials A free API key of pexels.com A google sheet with the columns Next Follow the sticky notes to set up the parameters inside each node and get ready to pump your learning skills. I have detailed the steps in a short tutorial 👇 🎥 Check My Tutorial Notes This workflow can be used for any language. In the AI Agent prompt, you just need to replace the word pinyin with phonetic transcription. You can adapt the trigger to operate the workflow in the way you want. These operations can be performed by batch or triggered by Telegram, email, or webhook. If you want to learn more about how I used Anki flash cards to learn mandarin: 🈷️ Blog Article about Anki Flash Cards This workflow has been created with N8N 1.82.1 Submitted: March 17th, 2025

Tags: Supply Chain Management, Logistics, Transportation Context Hey! I'm Samir, a Supply Chain Engineer and Data Scientist from Paris founder of LogiGreen Consulting We design tools to help small and medium businesses in improving their logistics processes using data analytics and automation. > Let's use N8N to make supply chains more efficient and sustainable Supply Chains! Who is this template for? This workflow template is designed for logistics operations that cannot rely on a Transportation Management System to record proofs of deliveries. What is a delivery confirmation? This workflow uses a Telegram bot to automatically notify logistics teams by email when a shipment is delivered. Drivers (equipped with their smartphones) can record their arrival with all the necessary information for accurate distribution planning. How do we notify the delivery? Let us imagine a truck driver arriving at the destination; he can contact the bot to be guided on how to record the delivery. User Guide: the first bot's message is a brief explanation of the process Record Shipment Number: the bot asks the driver to share the shipment number and record it Collect GPS Location: the bot asks the driver to share its GPS location and record them Picture of the Shipment: the bot asks for a picture of the shipment and saves it in Google Drive Send Confirmation: after data collection, the bot proposes to send a confirmation to the logistics management team An email is then automatically sent by the N8N workflow including all the information recorded by the flow and a picture of the shipment. Prerequisite This workflow does not require any additional paying subscription. A Google Drive Account with a folder including a Google Sheet API Credentials: Google Drive API, Google Sheets API and Gmail API A Telegram Bot with its API token from BotFather A Google sheet to store the shipment records with these five columns prepared: shipmentNumber, recordTime, gpsLattitude, gpsLongitude, cargoPicture, deliveryTime Next Steps Follow the sticky notes to set up the parameters inside each node and get ready to improve your logistics operations! I have detailed the steps in a short tutorial 👇 🎥 Check My Tutorial 🚀 Interested in applications of N8N for Logistics & Supply Chain Management? Let's connect on Linkedin Notes This workflow can be adapted to add more functionalities. I explain how in the video. The bot can handle multiple drivers at the same time. If you want to learn more about the original tool designed with Python: 🚚 Blog Article about Telegram Shipment Tracking Bot This workflow has been created with N8N 1.82.1 Submitted: March 17th, 2025

This n8n workflow automates the process of converting a newly stored PDF file from Google Drive into an HTML file and saving it back to Google Drive. The workflow is triggered whenever a new PDF is uploaded to a specific folder, ensuring seamless conversion and storage without any manual intervention. This workflow provides an efficient, automated solution for converting PDFs to HTML, eliminating the need for manual file handling and ensuring a smooth document transformation process. It is particularly useful for scenarios where PDFs need to be dynamically converted and stored in an organised manner for web usage, archiving, or further processing. Prerequisites : Before setting up this workflow, ensure the following: PDF.co API Key: Sign up at PDF.co and obtain an API key for PDF to HTML conversion. Proper Authentication: Ensure authentication is configured for Google Drive in n8n. Customisation Options : Modify the API request to convert PDFs to other formats like Text, CSV, or XML. Extend the IF Node to reject files based on size or other properties. Send a notification once the conversion is complete using an Email or Telegram Node. Steps : Step 1: Google Drive Trigger Node (Watch for New Files) Click "Add Node" and search for Google Drive. Select "Google Drive Trigger" and add it to the workflow. Authenticate with your Google Account. Select the folder to monitor. Set the trigger to activate whenever a new file is added. Click "Execute Node" to test. Click "Save". Step 2: IF Node (Check if File is a PDF) Click "Add Node" and search for IF. Add a condition to check if the file extension is .pdf If true → Send the file to the next step. If false → Stop the workflow. Click "Execute Node" to test. Click "Save". Step 3: HTTP Request Node (Convert PDF to HTML) Click "Add Node" and search for HTTP Request. Set the Method to POST. Enter the PDF.co API endpoint for PDF to HTML conversion. In the Headers, add API key which we have get from pdf.co Send the binary PDF data as the request body. Click "Execute Node" to test. Click "Save". Step 4: Function Node (Convert Response to Binary) Click "Add Node" and search for Function. Write a JavaScript function to transform the API response into a binary file. Click "Execute Node" to test. Click "Save". Step 5: Google Drive Node (Save Converted HTML File) Click "Add Node" and search for Google Drive. Select "Upload File" as the action. Authenticate with your Google Account. Set the destination folder for storing the HTML file. Map the binary data from the Function Node. Click "Execute Node" to test. Click "Save". Step 6: Connect & Test the Workflow Link the nodes in this order (Google Drive Trigger → IF Node → HTTP Request → Function Node → Google Drive Upload) Run the workflow manually. Upload a test PDF to Google Drive. Check Google Drive for the converted HTML file. Who’s behind this? WeblineIndia’s AI development team. We've delivered 3500+ software projects across 25+ countries since 1999. From no-code automations to complex AI systems — our AI team builds tools that drive results. Looking to hire AI developers? Start with us.

This workflow automates the process of converting images from JPG/PNG format to WEBP using the APYHub API. It retrieves image URLs from a Google Sheet, converts the images, and uploads the converted files to Google Drive. This workflow is a powerful tool for automating image conversion tasks, saving time and ensuring that images are efficiently converted and stored in the desired format. Using WebP images on a website provides several SEO benefits: Faster Loading Speed – WebP files are smaller than JPG and PNG, reducing page load times and improving user experience. Better Core Web Vitals – Google prioritizes websites with good performance metrics like LCP (Largest Contentful Paint). Improved Mobile Performance – Smaller images consume less bandwidth, enhancing mobile usability. Higher Search Rankings – Faster sites tend to rank better on Google due to improved user experience. Reduced Server Load – Lighter images lower hosting and CDN costs while improving site efficiency. Below is a breakdown of the workflow: 1. How It Works The workflow is designed to convert images from JPG/PNG to WEBP format and manage the converted files. Here's how it works: Manual Trigger: The workflow starts with a Manual Trigger node, which initiates the process when the user clicks "Test workflow." Set API Key: The Set API KEY node defines the API key required to access the APYHub API. Get Images: The Get Images node retrieves a list of image URLs from a Google Sheet. The sheet contains columns for the original image URL (FROM), the converted image URL (TO), and a status flag (DONE). Get Extension: The Get Extension node extracts the file extension (JPG, JPEG, or PNG) from the image URL and adds it to the JSON data. Determine Image Type: The JPG or PNG? node checks the file extension and routes the workflow to the appropriate conversion node: JPG/JPEG: Routes to the From JPG to WEBP node. PNG: Routes to the PNG to WEBP node. Convert Image: The From JPG to WEBP and PNG to WEBP nodes send POST requests to the APYHub API to convert the images to WEBP format. The API returns the URL of the converted image. Update Google Sheet: The Update Sheet node updates the Google Sheet with the URL of the converted image and marks the row as done (DONE). Get Converted Image: The Get File Image node downloads the converted WEBP image from the URL provided by the APYHub API. Upload to Google Drive: The Upload Image node uploads the converted WEBP image to a specified folder in Google Drive. 2. Set Up Steps To set up and use this workflow in n8n, follow these steps: APYHub API Key: Obtain an API Key from APYHub. In the Set API KEY node, define the API key. Google Sheets Integration: Set up Google Sheets credentials in n8n for the Get Images and Update Sheet nodes. Create a Google Sheet with columns for FROM (original image URL), TO (converted image URL), and DONE (status flag). Provide the Document ID and Sheet Name in the Get Images node. Google Drive Integration: Set up Google Drive credentials in n8n for the Upload Image node. Specify the folder ID in Google Drive where the converted images will be uploaded. Test the Workflow: Click the "Test workflow" button in n8n to trigger the workflow. The workflow will: Retrieve image URLs from the Google Sheet. Convert the images to WEBP format using the APYHub API. Update the Google Sheet with the converted image URLs. Upload the converted images to Google Drive. Optional Customization: Modify the workflow to include additional features, such as: Adding more image formats for conversion. Sending notifications when the conversion is complete. Integrating with other storage services (e.g., Dropbox, AWS S3).

🎥 Analyze YouTube Video for Summaries, Transcripts & Content + Google Gemini Who is this for? This workflow is ideal for content creators, video marketers, and research professionals who need to extract actionable insights, detailed transcripts, or metadata from YouTube videos efficiently. It is particularly useful for those leveraging AI tools to analyze video content and optimize audience engagement. What problem does this workflow solve? / Use case Analyzing video content manually can be time-consuming and prone to errors. This workflow automates the process by extracting key metadata, generating summaries, and providing structured transcripts tailored to specific use cases. It helps users save time and ensures accurate data extraction for content optimization. What this workflow does Extracts audience-specific metadata (e.g., video type, tone, key topics, engagement drivers). Generates customized outputs based on six prompt types: Default: Actionable insights and strategies. Transcribe: Verbatim transcription. Timestamps: Timestamped dialogue. Summary: Concise bullet-point summary. Scene: Visual descriptions of settings and techniques. Clips: High-engagement video segments with timestamps. Saves extracted data as a text file in Google Drive. Sends analyzed outputs via Gmail or provides them in a completion form. Setup Configure API keys: Add your Google API key as an environment variable. Input requirements: Provide the YouTube video ID (e.g., wBuULAoJxok). Select a prompt type from the dropdown menu. Connect credentials: Set up Google Drive and Gmail integrations in n8n. How to customize this workflow to your needs Modify the metadata prompt to extract additional fields relevant to your use case. Adjust the output format for summaries or transcripts based on your preferences (e.g., structured bullets or plain text). Add nodes to integrate with other platforms like Slack or Notion for further collaboration. Example Usage Input: YouTube video ID (wBuULAoJxok) and prompt type (summary). Output: A concise summary highlighting actionable insights, tools, and resources mentioned in the video.

This n8n workflow automates the transformation of press releases into polished articles. It converts the content of an email and its attachments (PDF or Word documents) into an AI-written article/blog post. What does it do? This workflow assists editors and journalists in managing incoming press-releases from governments, companies, NGOs, or individuals. The result is a draft article that can easily be reviewed by the editor, who receives it in a reply email containing both the original input and the output, plus an AI-generated self-assessment. This self-assessment represents an additional feedback loop where the AI compares the input with the output to evaluate the quality and accuracy of its transformation. How does it work? Triggered by incoming emails in Google, it first filters attachments, retaining only Word and PDF files while removing other formats like JPGs. The workflow then follows one of three paths: If no attachments remain, it processes the inline email message directly. For PDF attachments, it uses an extractor to obtain the document content. For Word attachments, it extracts the text content by a http request. In each case, the extracted content is then passed to an AI agent that converts the press release into a well-structured article according to predefined prompts. A separate AI evaluation step provides a self-assessment by comparing the output with the original input to ensure quality and accuracy. Finally, the workflow generates a reply email to the sender containing three components: the original input, the AI-generated article, and the self-assessment. This streamlined process helps editors and journalists efficiently manage incoming press releases, delivering draft articles that require minimal additional editing." How to set it up 1. Configure Gmail Connection: Create or use an existing Gmail address Connect it through the n8n credentials manager Configure polling frequency according to your needs Set the trigger event to "Message Received" Optional: Filter incoming emails by specifying authorized senders Enable the "Download Attachments" option 2. Set Up AI Integration: Create an OpenAI account if you don't have one Create a new AI assistant or use an existing one Customize the assistant with specific instructions, style guidelines, or response templates Configure your API credentials in n8n to enable the connection 3. Configure Google Drive Integration: Connect your Google Drive credentials in n8n Set the operation mode to "Upload" Configure the input data field name as "data" -Set the file naming format to dynamic: {{ $json.fileName }} 4. Configure HTTP Request Node: Set request method to "POST" Enter the appropriate Google API endpoint URL Include all required authorization headers Structure the request body according to API specifications Ensure proper error handling for API responses 5. Configure HTTP Request Node 2: Set request method to "GET" Enter the appropriate Google API endpoint URL Include all required authorization headers Configure query parameters as needed Implement response validation and error handling 6. Configure Self-Assessment Node: Set operation to "Message a Model" Select an appropriate AI model (e.g., GPT-4, Claude) Configure the following prompt in the Message field: Please analyze and compare the following input and output content: (for example) Original Input: {{ $('HTTP Request3').item.json.data }} {{ $('Gmail Trigger').item.json.text }} Generated Output: {{ $json.output }} Provide a detailed self-assessment that evaluates: Content accuracy and completeness Structure and readability improvements Tone and style appropriateness Any information that may have been omitted or misrepresented Overall quality of the transformation 7. Configure Reply Email Node: Set operation to "Send" and select your Gmail account Configure the "To" field to respond to the original sender: {{ $('Gmail Trigger').item.json.from }} Set an appropriate subject line: RE: {{ $('Gmail Trigger').item.json.subject }} Structure the email body with clear sections using the following template: handlebars EDITED ARTICLE* {{ $('AI Article Writer 2').item.json.output }} SELF-ASSESSMENT* Rating: 1 (poor) to 5 (excellent) {{ $json.message.content }} ORIGINAL MESSAGE* {{ $('Gmail Trigger').item.json.text }} ATTACHMENT CONTENT* {{ $('HTTP Request3').item.json.data }} Note: Adjust the template fields according to the input source (PDF, Word document, or inline message). For inline messages, you may not need the "ATTACHMENT CONTENT" section.

Capture URL Screenshots Automatically from Google Sheets & Drive with ScreenshotOne & Gmail Alerts Summary This automation template streamlines the process of capturing screenshots for multiple URLs. Instead of manually visiting each URL, taking a screenshot, and organizing the results, this workflow automates everything. When a spreadsheet is added to a designated Google Drive folder, the template extracts URLs from the column named "Url." These URLs are then processed through ScreenshotOne to capture screenshots, which are saved back to the same folder. Finally, an email notification is sent via Gmail with a link to the folder containing the screenshots. Problem Solved This template addresses the challenge of manual screenshot capture for multiple URLs. Without this automation, a user would need to: Open each URL from a spreadsheet. Take a screenshot manually. Save each screenshot with an appropriate name. Organize the screenshots in a folder. Notify stakeholders when the process is complete. These steps are not only time-consuming but also repetitive, especially when handling a large number of URLs. Who Can Benefit: Digital Marketers:** Monitor website appearances for competitive analysis or to track campaign landing pages. Web Developers/Designers:** Capture screenshots of multiple websites for inspiration or reference. QA Teams:** Document the visual state of web pages during various stages of development. SEO Specialists:** Track visual changes to websites they are optimizing. Content Managers:** Monitor how content appears across various web properties. Prerequisites Google Drive Node:** Must have appropriate permissions to create and access folders. Connected Google Sheets Node:** To extract URLs from the spreadsheet. Authenticated Gmail Node:** For sending notifications. ScreenshotOne Account:* Either a free or paid plan depending on volume needs, along with an *Access key**. Ensure you replace the placeholder --YOUR ACCESS KEY-- with your generated access key in the "Get Screenshots" node. Workflow Details Step 1: Google Drive Integration Trigger Node:** Monitors a specific folder in Google Drive. When a spreadsheet is added, the workflow is initiated. Step 2: Google Sheets Processing Google Sheets Node:** Extracts URLs from the column named "Url." Step 3: Screenshot Capture Get Screenshots Node:** Sends each extracted URL to ScreenshotOne to capture screenshots. Step 4: Saving Screenshots and Notifications Google Drive Node:** Saves the captured screenshots back into the same folder. Gmail Node:** Sends an email notification with a link to the folder, alerting stakeholders that the screenshots are ready. Customization Guidance Folder Monitoring: The workflow is set to monitor a specific Google Drive folder. It can be customized by selecting a different folder in the node settings. Spreadsheet Structure: While the template expects a spreadsheet with a column named "Url." for extracting URLs, users can add additional columns (e.g., titles, categories, or tags) and modify the workflow to utilize them as needed. Email Settings: Customize the recipient, subject, and body of the notification email to suit your needs. If required, enable optional notifications for different stakeholders. ScreenshotOne Access Key & Configurations: A valid ScreenshotOne Access key is required to capture screenshots. Users can further refine screenshot settings (e.g., viewport size, device emulation, or delay timing) by exploring the available options in the ScreenshotOne API documentation.