Quick overview This workflow receives phone push notification through FlowTrigger mobile app, extracts the transaction amount and date, uses Google Gemini to categorize the expense and adds it to a Google Sheets transactions log. How it works Receives a POST webhook request containing a captured notification payload from FlowTrigger mobile app. Parses the notification data and skips the flow if no amount is detected in the notification payload. Sends the notification title and body to Google Gemini and parses a structured response with cleaned merchant name, expense category, reasoning, and ISO currency code. Appends the date, amount, category, currency, and merchant to a selected Google Sheets tab. Returns a success response with the saved fields, or an error response if the AI categorization or Google Sheets write fails. Setup Create and connect a Google Gemini API key credential for the Google Gemini Chat Model. Create and connect a Google Sheets OAuth2 credential, then set the Google Sheets Document ID and Sheet Tab Name in the Google Sheets append step.
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Google Sheets
Structured Output ParserRelated workflows
See all AI Automation→Extract Twilio voice donation details with Groq, Gemini, and Google Sheets
Quick overview This workflow receives Twilio call recording callbacks, transcribes the audio with Groq Whisper, uses Google Gemini/Groq LLMs to extract structured donation details, and appends the results (with transcript and review flag) to Google Sheets. How it works Receives a Twilio Recording Status Callback webhook and immediately responds with TwiML (``). Captures call metadata (CallSid, caller number, recording URL/SID, and duration) and continues only if the recording exists and is at least 2 seconds long. Waits briefly for Twilio to finalize the media, then downloads the recording MP3 using Twilio HTTP Basic Auth. Sends the audio file to Groq’s Whisper transcription endpoint to generate a text transcript. Uses a LangChain prompt with Google Gemini and Groq chat models to extract donation amount, fee (if mentioned), beneficiary name, currency, a needs-review flag, and a short summary from the transcript. Parses the model output as JSON and falls back to an error summary with needs_review=yes if parsing fails. Checks Google Sheets for an existing row matching the CallSid/RecordingUrl and, if not found, appends a new row with the extracted fields, transcript, and call details
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Force AI to use a specific output format
This workflow is for anyone looking to automatically fetch, validate, and parse complex language-based queries into a structured format. Its unique capability lies in not only processing language but also fixing invalid outputs before structuring them. Note that to use this template, you need to be on n8n version 1.19.4 or later.
Schedule weekly focus-time blocks with Google Calendar, OpenAI, and Slack
Quick overview This workflow runs every Sunday at 18:00 to scan your Google Calendar for next week, find free gaps of at least two hours within your working hours, auto-book them as “🧘 Focus Time” events, and then DM you a personalized deep-work plan in Slack using OpenAI. How it works Runs every Sunday at 18:00 on a schedule. Loads your working-hour preferences and fetches all events from your Google Calendar. Calculates weekday-only free gaps within your working hours and keeps only gaps that meet the minimum block length. If no qualifying gap exists, sends you a Slack DM warning that next week is too fragmented for a focus block. If gaps exist, limits the number of blocks for the week and creates “🧘 Focus Time (protected by n8n)” events in Google Calendar for each selected slot. Uses OpenAI to generate a short, personal Slack message that lists the protected blocks and suggests what kind of work fits each. Sends the generated deep-work plan to you as a Slack DM. Setup Add Google Calendar credentials, select the calendar to read from and the calendar to create “🧘 Focus Time” events in. Add Slack credentials and set your target Slack username in both the plan DM and warning mes