Google Gemini Chat Model workflows
141 results — all source-linked n8n references
Archive and index legal PDFs from Gmail with Gemini, Sheets and Google Drive
Quick Overview This workflow monitors Gmail for unread emails with PDF attachments, uses Google Gemini to extract Japan Electronic Books Preservation Act filing metadata, logs a searchable index in Google Sheets, and archives documents into Google Drive folders while notifying Slack when extraction or classification fails. How it works Polls Gmail hourly for unread emails that contain attachments and downloads the attached files. Extracts text from the first PDF attachment. Sends the extracted text to Google Gemini to pull out transaction date, counterparty, amount, and document type, and alerts Slack if the document text cannot be read. Builds an Act-compliant PDF filename from the extracted fields and checks that date, counterparty, and amount are all present. If required metadata is missing, posts a warning to a Slack channel to handle the document manually. If metadata is complete, appends a row to a Google Sheets “Document Index”, marks the Gmail message as read to prevent reprocessing, and uploads the PDF to the matching Google Drive folder (invoice/receipt/contract) or flags it in Slack if unclassified. Setup Connect credentials for Gmail, Google Gemini (PaLM) API, Google Sh
Match Japanese jGrants subsidies to your company with Gemini, Slack and Gmail
Quick Overview This workflow runs weekly to search the public jGrants API for open Japanese subsidies, scores each subsidy’s fit for your company using Google Gemini, logs results to Google Sheets, and notifies a Slack channel (and drafts a Gmail kickoff email) for strong matches. How it works Runs weekly on a schedule and loads your company profile details (industry, headcount, prefecture, investment plan, and search keyword). Calls the public jGrants subsidies API to retrieve currently accepting programs sorted by newest first, and posts to Slack if the search fails. Processes each returned subsidy individually and asks Google Gemini to produce a fit score, verdict (strong/possible/no), reasons, next steps, and a short summary. Normalizes the Gemini response into consistent fields, and posts to Slack if scoring fails for a subsidy. Upserts each scored subsidy into a Google Sheets tracker (keyed by subsidy ID) to avoid duplicates across weekly runs. Routes results by verdict: sends a detailed Slack alert and creates a Gmail draft for strong matches, posts a lightweight Slack message for possible matches, and flags unclear verdicts in Slack. Setup Add credentials for Google Gemini
Monitor Japanese business partners for registry changes with gBizINFO and Gemini
Quick Overview This workflow runs weekly to check Japanese business partners listed in Google Sheets against the gBizINFO corporate registry API, uses Google Gemini to assess the risk impact of detected changes, updates the stored partner snapshot, and escalates findings to Slack and Gmail based on materiality. How it works Runs every week on a schedule. Reads the partner list (including corporate numbers and last-known name/address) from Google Sheets. Queries the gBizINFO corporate registry API for each partner and posts a Slack message if the lookup fails. Compares the latest registry data to the stored snapshot to detect name, address, or closure/dissolution changes and continues only when changes are found. Sends the detected changes to Google Gemini to classify materiality (high/medium/low) with a short summary and recommended action, and posts a Slack message if the assessment fails. Updates the Google Sheets partner snapshot with the latest registry details so the change is recorded. Routes by materiality to notify Slack (medium/other), and for high materiality also posts a Slack alert and creates a Gmail draft requesting a credit review. Setup Create a Google Sheets spread
Monitor overtime risk against Japanese labour caps with Gemini, Sheets, Slack & Gmail
Quick Overview This workflow runs weekly to read attendance overtime from Google Sheets, totals it per employee and month, uses Google Gemini to classify risk against Japanese labour-law limits, writes results back to Sheets, and escalates high-risk cases via Slack and a Gmail draft. How it works Runs every week on a schedule. Loads configured Japanese overtime limits and fetches raw attendance rows from a Google Sheets “Attendance” worksheet. Aggregates overtime hours per employee per month. Sends each employee-month total to Google Gemini, which returns a structured risk level (over/approaching/ok) plus a short summary and recommended manager actions. Stores or updates the assessment in a Google Sheets “Overtime Status” worksheet keyed by employee and month. Posts to Slack when overtime is over the cap (and drafts a manager notice in Gmail), posts an early-warning Slack message when approaching the cap, and flags unclear or failed assessments to Slack for manual review. Setup Add credentials for Google Sheets OAuth, Google Gemini (PaLM) API, Slack OAuth2, and Gmail OAuth2. Create a Google Sheets spreadsheet with an “Attendance” sheet containing Employee (or Name), Month (or Date)
Check Japanese ad copy compliance with Google Gemini, Sheets, Slack and Gmail
Quick Overview This workflow runs daily to review Japanese ad copy in Google Sheets using Google Gemini, writes compliance risk results back to the sheet, and alerts the right team in Slack (and drafts a Gmail revision request) based on high/medium/low risk. How it works Runs every day at 9:00 on a schedule. Reads ad copy rows from Google Sheets to find items that still need a compliance check. Sends each copy item to Google Gemini with the configured product category, target laws, and extra rules to generate a risk level, violations, and a compliant rewrite. Parses and normalizes the Gemini output into fields like risk level, violation count, and safe rewrite, and posts a Slack alert if the AI check fails. Updates the corresponding Google Sheets row with the compliance results to keep a record of the review. Routes the item by risk level and posts to Slack for legal blocking (high), marketing review (medium), publish-ready notification (low), or manual review when the result is inconclusive. For high-risk copy, also creates a Gmail draft requesting the author to revise the copy using the suggested compliant rewrite. Setup Add credentials for Google Sheets, Google Gemini (PaLM) API
Verify Japanese invoice registration numbers from Gmail using Gemini, NTA API, Sheets and Slack
Quick Overview This workflow monitors Gmail for unread invoice emails with PDF attachments, extracts invoice details with Google Gemini, verifies Japanese qualified invoice registration numbers against the National Tax Agency (NTA) Invoice Web-API, logs results to Google Sheets, and sends Slack alerts for invalid, missing, or inconclusive checks. How it works Polls Gmail hourly for unread emails matching “has:attachment invoice” and downloads the first attachment. Extracts text from the attached invoice PDF. Uses Google Gemini to parse the invoice text into structured fields such as the T-registration number, issuer name, invoice date, and amounts. Normalizes and validates the registration number to ensure it matches the required “T + 13 digits” format. If the format is valid, calls the NTA Invoice Web-API to verify the registration number and interprets the response as valid, invalid, or not found. Appends the invoice details and verification status to a Google Sheets worksheet. Routes the outcome by sending the appropriate Slack alert for invalid/not found/inconclusive results or marking the invoice email as read when the number is valid. Setup Connect your Gmail OAuth2 credentia
Generate weekly student progress reports with Gemini, Supabase, and WhatsApp
Quick overview This workflow runs weekly to pull student attendance and score data from Supabase, uses Google Gemini to generate per-student performance summaries and attention flags, sends immediate WhatsApp alerts for flagged students, then compiles all summaries into a PDF report, uploads it, and shares it with the coach via WhatsApp. How it works Runs weekly on a schedule. Fetches all student weekly metrics (attendance and scores) from Supabase. Uses Google Gemini to write a short performance summary per student and determine whether the student should be flagged for attention based on attendance and score-drop rules. If a student is flagged, sends a WhatsApp message to the coach and inserts a flag record into Supabase. Aggregates all students’ summaries into a single HTML weekly report. Converts the HTML report to a PDF via an HTTP-based HTML-to-PDF API, uploads the PDF to a file-hosting API, and sends the PDF link/document to the coach via WhatsApp. Logs the report URL to Supabase for recordkeeping. Setup Add Supabase credentials and create the required tables/columns (weekly_student_data, attention_flags, and weekly_reports) referenced by the workflow. Add a Google Gemini (P
Draft personalized cold emails from Google Sheets using Gemini and HubSpot
Quick overview This workflow batch-processes leads from Google Sheets, researches each person and company using Tavily plus Google Gemini, drafts a personalized cold email, then creates/updates the contact in HubSpot with a research note and a saved email draft before marking the lead as Done in the sheet. How it works Runs manually and sets a batch size that controls how many leads to process per run. Reads leads from Google Sheets, skips rows already marked as Done, and normalizes the selected batch into clean lead fields. Processes the batch one lead at a time and uses Tavily search (last 60 days) with Google Gemini to extract the most recent public activity, pain points, and a personalization hook. Cleans and parses the research JSON so it can be reused reliably downstream. Uses Google Gemini to draft a 90–120 word cold outreach email (subject and body) that incorporates the research and offers a free “Automated LinkedIn Post Creator” n8n workflow. Creates or reuses the HubSpot contact, logs a HubSpot note with the research and drafted email, and saves the email as a HubSpot engagement in DRAFT status. Updates the matching row in Google Sheets (by Email) to set Status to “Done
Send and track Slack invoice requests with Gemini, Google Sheets and Gmail
Quick overview Youtube Video: https://youtu.be/42-oHh9w9Eo This workflow listens for Slack @mentions, uses Google Gemini to classify the request and extract invoice details, then reads and updates Google Sheets, generates invoice PDFs with PdfBro, sends invoices or reminders via Gmail, and posts confirmations or errors back to Slack. How it works Triggers when the workflow’s Slack app is mentioned in a specified Slack channel. Uses Google Gemini to classify the message intent (send invoice, remind invoice, or check status) and extract the recipient email and invoice due date. Routes the request based on the extracted intent and stops if the intent cannot be determined. For SEND_INVOICE, looks up the client in a Google Sheets “Client Bill” spreadsheet and posts a Slack error if no matching email is found. If a client is found, generates an invoice PDF with PdfBro, emails it to the client via Gmail, appends/updates the invoice record in a Google Sheets “Client Invoices” spreadsheet, and posts a Slack confirmation. For REMIND_INVOICE, finds an UNPAID invoice for the email in the “Client Invoices” Google Sheet, regenerates the invoice PDF with PdfBro, emails a reminder via Gmail, and p
Handle WhatsApp customer service chats with Google Gemini and Google Sheets
Quick Overview This workflow handles WhatsApp customer service via OpenWA, using Google Gemini and a Google Sheets knowledge base to answer personal chats, while routing conversations to a human queue in Google Sheets when escalation is needed. How it works Triggers on OpenWA WhatsApp events and ignores message reactions except for specific ✅/☑ reactions used to re-enable AI handling. Normalizes incoming event fields and processes only personal chats (IDs ending with @c.us) that are not sent by your own WhatsApp account. Checks a Google Sheets “Session Chat” list to decide whether the conversation is currently handled by a human, and only continues to AI when no active human session is found. Uses a Google Gemini chat model with short-term memory and a Google Sheets “Database Company” tool to draft a friendly Indonesian response based only on the sheet data. If the AI response does not contain the #admin escalation token, it sends the reply back to the customer via OpenWA. If the AI response contains #admin, it appends the chat to the Google Sheets “Session Chat” sheet to flag it for human follow-up. When a ✅/☑ reaction is received for a chat, it finds and deletes the corresponding
Create a Gmail morning audio briefing with Google Gemini and Google Drive
Quick Overview This workflow runs every weekday at 7 AM to fetch up to 10 unread Gmail messages from the last day, summarize them into a narrated script with Google Gemini, convert the script to an MP3 using Smallest.ai, upload it to Google Drive, and email you a public listening link. How it works Runs on a schedule every weekday at 7:00 AM. Pulls up to 10 unread Gmail emails from the last 24 hours. Cleans and categorizes the emails into URGENT, NEWSLETTERS, and OTHER sections while skipping common job-alert style messages. Uses a LangChain AI Agent powered by Google Gemini to turn the digest into a plain-text morning briefing script. Truncates the script to a safe character limit and converts it to speech as an MP3 with Smallest.ai. Uploads the MP3 to Google Drive, makes the file publicly readable, and sends a Gmail message with the listening link and the script text. Setup Connect your Gmail credentials for both reading unread emails and sending the briefing email, and update the recipient address in the outgoing email step. Add Google Gemini credentials in the Google Gemini Chat Model used by the AI Agent. Add your Smallest.ai API credentials for text-to-speech generation. Conn
Create narrated blog audio from RSS with Google Gemini, Smallest.ai and WordPress
Quick Overview This workflow polls a blog RSS feed, rewrites new posts into a spoken-word script using Google Gemini, generates an MP3 with Smallest.ai, uploads it to Google Drive, and updates the matching WordPress post to embed a public audio player. How it works Polls an RSS feed every minute to detect newly published or updated blog items. Extracts the post body and strips HTML, scripts, styles, and common entities to produce clean plain text. Uses Google Gemini to rewrite the text into a single, conversational narration script with an intro/outro and length limits. Sends the rewritten script to Smallest.ai to synthesize an English MP3 audio file. Uploads the MP3 to Google Drive and updates sharing so anyone with the link can play it. Updates the corresponding WordPress post to embed an HTML5 audio player pointing to the Google Drive link and includes the article text below it. Setup Set the RSS feed URL in the RSS Feed Trigger node and confirm the feed provides the fields used for the post content and GUID. Add credentials for Google Gemini (Google AI / Gemini) and select that connection in the chat model used by the rewrite step. Add your Smallest.ai API credentials and verif
Qualify leads and send personalized audio follow-ups with Gemini and Smallest.ai
Quick Overview This workflow receives lead submissions via a webhook, uses Google Gemini to qualify the lead and write a personalized spoken follow-up script, and for qualified leads generates an MP3 with Smallest.ai, shares it from Google Drive, emails it via Gmail, logs outcomes to Google Sheets, and alerts sales in Slack. How it works Receives a POST webhook request containing a lead’s name, email, and message. Sends the lead details to a Google Gemini–powered AI agent to determine whether the lead is qualified and, if so, generate a short personalized audio script. Parses the agent’s JSON response and routes the workflow based on the qualified flag. If the lead is qualified, Smallest.ai synthesizes the script into an MP3 and uploads it to Google Drive. Shares the Google Drive audio file publicly and sends the lead a Gmail message with a link to listen. Appends the qualified lead record (including the audio link and timestamp) to Google Sheets and posts a notification to a Slack channel. If the lead is unqualified, appends the lead details and timestamp to Google Sheets without generating audio or sending email. Setup Enable the webhook and copy the generated /lead-capture URL i
Transcribe and summarize Twilio calls with Smallest.ai, Gemini, Slack, and GoHighLevel
Quick Overview This workflow listens for completed Twilio call recordings, downloads and transcribes the audio with Smallest.ai, summarizes the transcript with Google Gemini, then notifies a Slack user and creates a new opportunity in GoHighLevel. How it works Triggers when Twilio Voice Insights reports a call summary as complete. Downloads the call recording audio from Twilio using the provided recording URL. Sends the audio file to Smallest.ai to generate a speech-to-text transcription. Uses a Google Gemini-powered AI agent to produce a short call summary, caller sentiment, and a suggested next step from the transcript and call metadata. Sends the generated summary to a specified Slack user. Creates a new opportunity in GoHighLevel that includes the caller number and AI summary. Setup Connect your Twilio credentials and ensure Twilio Voice Insights call summary events are enabled for your account. Add your Smallest.ai API credentials for the transcription step. Configure Google Gemini credentials in the LangChain Google Gemini chat model used by the AI agent. Connect your Slack credentials and set the target user (or change to a channel) for notifications. Connect your GoHighLeve
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
Create TikTok carousel posts with Upload Post, Google Sheets, Gemini, GPT-4.1
Quick overview This workflow runs daily to pull TikTok post and profile analytics from Upload Post, updates a Google Sheets performance log, uses Google Gemini and OpenAI to generate a new carousel concept and caption, creates four images via fal.ai, publishes to TikTok, and updates a persistent “Agent Skill” sheet. How it works Runs on a daily schedule (or manually) and loads product, Upload Post, and Google Sheets configuration values. Reads the Google Sheets “Performance Log,” selects posts missing stats or posted recently, fetches TikTok post analytics from the Upload Post API, and writes updated metrics back to the sheet. Aggregates the refreshed history, fetches TikTok profile analytics from Upload Post, reads the “Agent Skill” sheet, and compiles a single context summary. Uses Google Gemini (via a structured JSON output) to generate a TikTok carousel plan including caption, strategy notes, four slide prompts, hashtags, and an engagement question. Sends the four prompts to fal.ai to generate four 9:16 PNG carousel images and collects their hosted image URLs. Uses OpenAI (GPT-4.1) to write a short TikTok photo-post description, publishes the carousel to TikTok via Upload Post
Send prescription PDFs to patients via WhatsApp with Google Gemini and Supabase
Quick overview This workflow listens for incoming WhatsApp messages from clinic staff, uses Google Gemini to extract prescription details, generates a prescription PDF via an HTML-to-PDF API, uploads it to a public URL, sends the document back over WhatsApp, and logs outcomes to Supabase. How it works Triggers whenever a new WhatsApp message is received on your WhatsApp Business Cloud number. Captures configuration values and the incoming message text and sender number. Uses Google Gemini to extract patient name, doctor name, and medication details into structured data and flags any missing required fields. If required details are missing, replies to staff on WhatsApp with what to fix and inserts a needs_review record into Supabase. If details are complete, renders a prescription HTML document, converts it to a PDF via an external HTML-to-PDF API, and uploads the PDF to an external file-hosting API. Sends the prescription PDF to the sender on WhatsApp and inserts a “sent” log record (including the PDF URL) into Supabase. Setup Connect WhatsApp Business Cloud credentials for the WhatsApp trigger and the WhatsApp send steps, and configure the workflow’s webhook in Meta/WhatsApp so in
Answer support FAQs with Google Gemini, Supabase, Google Sheets and WhatsApp
Quick overview This workflow ingests FAQs from Google Sheets into a Supabase vector table using Google Gemini embeddings, then serves a webhook-based support chatbot that answers only from that FAQ knowledge base and escalates unanswered questions to a human via UltraMsg WhatsApp. How it works Runs manually to pull FAQ rows (Question/Answer) from a Google Sheets spreadsheet. Formats each row into a single text document (for example, Q: … A: …), generates embeddings with Google Gemini, and inserts the documents into a Supabase vector store table. Receives incoming chat messages via a POST webhook that includes message and sessionId. Uses a Google Gemini chat model with session-based memory to query the Supabase vector store for the most relevant FAQ matches and generates a reply strictly from the retrieved content. If the agent output indicates escalation to a human, sends the full message content to UltraMsg via an HTTP request to alert a WhatsApp number. Returns a JSON response to the webhook caller with either the FAQ-based answer or a confirmation that a human agent has been notified. Setup Add credentials for Google Gemini (PaLM) API, Supabase, and Google Sheets OAuth2. In Supa
Qualify WhatsApp real estate leads with Gemini and Supabase
Quick overview This workflow triggers on incoming WhatsApp messages, uses Google Gemini to extract and score real estate lead details, stores each lead in Supabase, and sends a WhatsApp alert to the agent only for high-intent inquiries based on configurable score thresholds. How it works Triggers when a new WhatsApp message is received via the WhatsApp Business Cloud API. Pulls the sender name, phone number, and message text and applies your configured scoring thresholds and agent contact number. Sends the message to Google Gemini to extract structured lead details (budget range, property type, location preference, timeline, and intent score). Inserts the extracted lead data into a Supabase leads table for tracking. Routes the lead based on the intent score and sends a formatted WhatsApp message to the agent for high-intent leads. Leaves medium- and low-intent leads logged in Supabase without sending an agent alert. Setup Connect WhatsApp Business Cloud API credentials for both the incoming-message trigger and the WhatsApp send action, and activate the workflow to generate the webhook for your WhatsApp app. Add a Google Gemini (PaLM) API credential for the Gemini chat model. Add a
Schedule YouTube Shorts to Pinterest with Apify, Gemini, and an OpenAI model
Quick overview This workflow receives YouTube Shorts webhook events, downloads the video via Apify, uses Google Gemini and an OpenAI-compatible chat model to generate Pinterest SEO metadata and choose a board, then schedules a Pinterest video pin through Zernio (Late) for publishing. How it works Receives a webhook request for YouTube PubSubHubBub verification and responds with the provided hub challenge. Receives a POST webhook event for a new YouTube video and extracts the title, video ID, channel ID, and video URL from the feed payload. Uses Apify to fetch and process the YouTube Short and returns a downloadable MP4 URL. Sends the video to the Google Generative Language (Gemini) API to generate an analysis used for Pinterest-focused metadata. Uses a LangChain LLM chain (with structured output validation) to produce a Pinterest-ready title, description, hashtags, and a board selection from a fixed list. Maps the selected board name to a Pinterest board ID and schedules the video post to Pinterest via the Zernio (Late) API. Setup Create the YouTube webhook/PubSubHubbub subscription and configure it to call this workflow’s webhook URL at the manga-monarch-webhook path for both veri
Handle real estate SMS inquiries with Twilio, Google Sheets, Gemini, and Calendar
Quick overview Youtube Explanation: https://youtu.be/e_07nGFmVs0 This workflow replies to inbound Twilio SMS messages with property details and viewing scheduling help by looking up leads and properties in Google Sheets, using a Google Gemini agent with Redis chat memory, and checking/booking appointments in Google Calendar. How it works Receives an inbound SMS via Twilio. Looks up the sender’s mobile number in a Google Sheets “leads_info” spreadsheet and appends/updates the lead record if it does not exist, extracting a 4-digit property code from the message when available. Splits any saved semicolon-separated property IDs into individual lookups, fetches matching property rows from a Google Sheets “Property details” spreadsheet, and compiles a summary of found vs. missing property codes. Sends the user message, lead context (saved property IDs and email), current time, and the property-lookup results to a Google Gemini chat agent with Redis-backed conversation memory. Lets the agent optionally use tools to fetch additional property info from Google Sheets, update the lead’s email or interested property IDs in Google Sheets, and check or create viewing events in Google Calendar. S
Vet community membership applications with Google Gemini, Telegram, and Sheets
Quick overview This workflow collects community membership applications via an n8n Form, vets each candidate with Google Gemini using Tavily web search and an Apify LinkedIn lookup, requests human approval in Telegram when needed, sends invite or rejection emails via Gmail, and logs outcomes to Google Sheets. How it works Receives a submission from an n8n Form that captures applicant details such as name, email, company, role, birthday, and additional notes. Normalizes the submitted fields and passes the candidate profile to a Google Gemini-powered AI Agent that can use Tavily web search, an Apify LinkedIn search actor, a calculator, and short-term memory. Produces a structured vetting result (including summary, decision status, and a community-fit score) using a structured output schema. If the AI decision is “Immediate approval”, sends the candidate summary to Telegram and waits for a response before continuing. If the AI decision is not “Immediate approval”, sends the summary to Telegram and asks the reviewer to reply with 1 (approve), 2 (reject), or 3 (do nothing). Sends an approval/invite email or a rejection email via Gmail based on the Telegram response, or stops without act
Run Bunker Guard NPC chat and RAG lore checks with Google Gemini and Google Drive
Quick overview This workflow powers dynamic character interactions for investigative games. It ingests lore from Google Drive into a vector database, using Google Gemini agents to generate daily briefings, spawn NPCs, and roleplay interrogations via a webhook. How it works Runs on a manual trigger to download a lore PDF from Google Drive, split it into chunks, create Google Gemini embeddings, and store them in an in-memory vector store for retrieval. Receives a POST webhook request from the game client containing game state and an action value (briefing, init, or chat). Routes the request based on action to either generate a morale-based daily intel briefing, create a new NPC profile for the day, or generate an in-character reply to the player’s interrogation message. When factual lore is needed (routes, locations, prices, rules, professions), the Gemini agent queries the Database_Bunker vector-search tool to ground the response in the ingested PDF. Maintains short conversation context per player using a buffer memory keyed by playerId for ongoing chat and NPC interactions. Returns the agent output to the caller as clean JSON via the webhook response. Optionally, triggers on an n8n
Track meal nutrition from photos with LINE, Google Gemini and Google Sheets
Quick Overview This workflow receives meal photos via LINE, uses Google Gemini to estimate nutrition facts and generate advice, stores the photo in Google Drive, logs the results to Google Sheets, and replies to the user in LINE with a formatted analysis. How it works Receives a POST webhook event from LINE when a user sends a message. Checks whether the incoming LINE message contains an image and stops processing if it does not. Downloads the image content from the LINE Messaging API and sends it to Google Gemini to identify foods, estimate nutrition values, and generate health guidance. If the AI response indicates the image is not food, sends a LINE push message asking the user to submit a clearer meal photo. If the AI response is valid, parses the returned text into structured fields (food items, macros, calories, score, and advice) and calculates remaining calories based on a daily goal. Uploads the meal photo to Google Drive, appends the nutrition log (including the Drive image URL) to Google Sheets, and sends the formatted nutrition summary back to the user via LINE. Setup Create a LINE Messaging API channel, enable the webhook, and add the workflow’s webhook URL (the /MealT