Google Sheets workflow'ları
248 sonuç — tümü kaynağa bağlı n8n referansı
Screen candidate CVs with Google Gemini, Google Sheets, and Gmail
Quick overview This workflow collects candidate applications via an n8n form, extracts text from uploaded PDF CVs, compares each CV to a job description stored in Google Sheets using Google Gemini (via OpenRouter), logs screening results back to Google Sheets, and creates a Gmail draft email for HR review. How it works Candidate submits the n8n-hosted form with their details and a PDF CV. Two operations run in parallel: CV text is extracted from the uploaded PDF, and the matching Job Description is fetched from Google Sheets using the role the candidate entered. Gemini Flash evaluates the CV against the JD and returns a structured recommendation: Strong Interview, Interview, Borderline, or Do Not Proceed, along with a score, matched skills, gaps, and a plain-text summary. The full screening record is logged to a Screening Results tab in Google Sheets. A Gmail draft is created for HR to review and send: a shortlist notification for Interview and above, a rejection for Borderline and below. Setup Open the Config node and fill in spreadsheet_id, jd_sheet_gid, results_sheet_gid, and company_name. Create two tabs in your Google Sheet: Job Description (columns: job_id, title, department,
Triage PubMed clinical literature with Gemini and Google Sheets and Docs
Quick overview Automatically retrieve recent PubMed articles, identify the three papers most worth reading first using AI, and generate structured clinical literature triage reports in Google Sheets and Google Docs. How it works Reads the first pending literature request from the Google Sheets "Search Requests" tab. Marks the request as “processing” in Google Sheets and builds the PubMed query parameters (keyword, max results, specialty, clinical question, and output language). Searches PubMed via the NCBI E-utilities API (esearch) and fetches the corresponding article abstracts and metadata as XML (efetch). Parses and normalizes the XML into a structured list of candidate articles including title, abstract, journal, publication year, DOI, and PubMed URL. Sends the aggregated candidate articles to Google Gemini to select and rank the best three papers and generate a structured clinical evaluation for each. Appends the three ranked papers with summaries and triage fields to a Google Sheets “Triage Results” tab. Generates a formatted triage report in Google Docs and updates the original request status to “completed” in Google Sheets. Setup Create a Google Sheets OAuth connection and
WAnalyse tender PDFs with LlamaParse, Gemini, Supabase and WhatsApp chat
Quick overview This workflow lets you upload a tender/RFT PDF via an n8n form, extracts key fields into Google Sheets using LlamaParse, and makes the document chat-searchable by embedding section chunks with Google Gemini and storing them in Supabase for WhatsApp-based Q&A with Anthropic/DeepSeek. How it works Receives a tender PDF when a user submits the n8n form. Generates a normalized document ID from the uploaded filename and sends the PDF to LlamaParse to parse the full text, split it into predefined tender sections, and extract structured tender metadata. Normalizes the extracted fields, calculates days-until-deadline and a bid score/recommendation, and appends or updates a row in a Google Sheets tender tracker. Combines the parsed full text with the section/page mapping, then carves each section into paragraph-aligned text chunks with page references. Creates an embedding for each chunk using the Google Gemini Embeddings API and inserts the chunk text and vectors into a Supabase table for retrieval. Triggers on an incoming WhatsApp message, embeds the user’s question with Google Gemini, runs a Supabase RPC vector search scoped to a single doc_id, and builds a context payload
Screen and route candidate CVs with OpenRouter, Google Drive, Sheets, and Gmail
Quick overview This workflow receives candidate CVs via a webhook, extracts text from PDF, DOCX files, looks up the matching job description in Google Sheets, runs a three-agent evaluation using OpenRouter models, then uploads the CV to Google Drive, logs results to Google Sheets, and sends or drafts emails in Gmail. How it works Receives a CV submission via a POST webhook that includes candidate details, an applied job ID, and a CV file. Normalizes the intake data, timestamps the submission, and fetches the matching job description from Google Sheets using the applied job ID. Extracts CV text by either parsing the PDF directly or converting a DOCX/DOC to a Google Doc in Google Drive and exporting it as plain text. Detects whether the CV is Vietnamese or not and uses OpenRouter (Qwen for Vietnamese or Google Gemini for others) to parse the CV into a structured Candidate Profile JSON. Uses OpenRouter (Anthropic Claude Sonnet) to compare the Candidate Profile against the job description, then generates a hiring-manager style review and recommendation based on the ATS evaluation. Uploads the original CV to a recommendation-based Google Drive folder, logs the full screening record (inc
Process prescription orders and refills with Telegram, Google Gemini and Sheets
Quick overview This workflow lets customers order and refill prescriptions via Telegram by extracting medicines from prescription images with Google Gemini, checking and updating inventory in Google Sheets, and sending order summaries and status updates, with delivery updates handled by a webhook and error alerts posted to Slack. How it works Triggers when a Telegram message is received, normalizes it, and routes it based on whether it contains a prescription image/document or the REFILL, STATUS, or CONFIRM command. For prescription images/documents, it downloads the file from Telegram and uses Google Gemini vision to extract medicines, dosages, and quantities from the prescription. It looks up each extracted medicine in a Google Sheets Inventory tab, deducts stock for items that are available, and aggregates the priced order lines. It creates a new pending order in a Google Sheets Orders tab and sends the customer a Telegram order summary with the total and a prompt to reply CONFIRM. For STATUS/REFILL/CONFIRM messages, it reads the relevant order from Google Sheets, sends the current status via Telegram, creates a new pending refill order, or updates the pending order status to co
Manage restaurant orders, upsells, and payments with Telegram, OpenAI, Razorpay, and Google Sheets
Quick overview This workflow runs a Telegram restaurant ordering flow that uses OpenAI to parse orders and suggest an upsell, sends a Razorpay payment link, confirms paid orders via a Razorpay webhook, logs orders and feedback in Google Sheets, notifies the kitchen, sends delivery updates, and posts error alerts to Slack. How it works Receives a customer’s order message in Telegram and sends it to OpenAI to extract items, quantities, subtotal, and a suggested upsell. Replies in Telegram with an order summary and upsell prompt, then waits for the customer to respond. When the customer replies, calculates the final total (including the upsell when accepted) and sends a Razorpay payment link in Telegram. Receives the Razorpay payment.captured webhook, extracts payment details, confirms payment to the customer in Telegram, and posts a kitchen ticket to a dedicated Telegram chat. Appends the paid order to an Orders tab in Google Sheets and calculates ingredient deductions to update the same sheet against the order. Waits through prep and delivery windows and then sends delivery tracking followed by a Telegram feedback request. Captures the customer’s rating in Telegram, calculates loyal
Triage Typeform survey feedback with GPT-4o-mini, Slack, Gmail, and Sheets
Quick overview This workflow triggers on new Typeform survey responses, uses OpenAI GPT-4o-mini to classify sentiment and draft reply emails, routes negative feedback through a Slack human-approval loop with revisions, sends emails via Gmail, and logs outcomes to a Google Sheets CRM. How it works Triggers when a new Typeform survey response is submitted. Extracts the respondent’s name, email, rating, and free-text feedback and sends it to OpenAI GPT-4o-mini to classify the response as positive or negative. If the response is negative, OpenAI GPT-4o-mini drafts an empathetic follow-up email, posts a Slack alert to the team, and sends the draft to a Slack review channel that waits for a reply. If the reviewer replies with “approved”, the workflow sends the approved draft to the respondent via Gmail and appends a “Sent” record to Google Sheets. If the reviewer requests changes, OpenAI GPT-4o-mini revises the email based on the Slack feedback and the workflow loops back to Slack for another review. If the response is not negative, OpenAI GPT-4o-mini drafts a thank-you email, sends it automatically via Gmail, and logs the sent email to Google Sheets. Setup Connect credentials for Typefo
Draft personalized cold emails from Google Sheets with Apify and GPT-4o mini
Quick overview This workflow reads pending medical or dental practice leads from Google Sheets, scrapes each practice website with Apify, uses OpenAI (gpt-4o-mini) to identify conversion gaps, and drafts a short personalized cold email, then writes the analysis and draft back to the sheet. How it works Manually starts the workflow and reads leads from a Google Sheets worksheet. Filters the rows to only those with Status set to "pending" and processes them one at a time. Uses Apify Website Content Crawler to scrape up to a few pages of each lead’s WebsiteURL and compiles the extracted text into a trimmed site summary. If enough website text is available, sends it to OpenAI (gpt-4o-mini) to produce a strict-JSON analysis of 2–3 concrete booking/chatbot/after-hours/intake gaps and a best outreach angle. Alternates between “soft” and “direct” framing and asks OpenAI (gpt-4o-mini) to generate a short JSON email draft (subject and body) tailored to the selected gap. Updates the matching row in Google Sheets with ScrapedNotes, WeakPoints, DraftEmail, and sets Status to "drafted", then waits briefly before moving to the next lead. If the scrape returns insufficient content, updates the lea
CResearch Reddit trends and publish LinkedIn posts with Gemini and PostPeer
Quick overview This workflow runs daily, scrapes a selected subreddit with Apify, researches sources via Brave Search and Jina Reader, and uses Eden AI (DeepSeek) plus Google Gemini to draft a LinkedIn post with an image. It logs state in Google Sheets/Drive, sends approval emails, and publishes via PostPeer. How it works Runs daily on a schedule, loads Global Constants, and picks an ACTIVE subreddit row from Google Sheets using a random ID. Scrapes recent posts from that subreddit using an Apify Reddit scraper, then normalizes, scores, and deduplicates candidates. Uses an Eden AI (DeepSeek) agent to vet the candidates and either selects one post idea or stops and records a NO_VIABLE_IDEA entry in Google Sheets and emails the rationale. For a selected idea, a second Eden AI (DeepSeek) agent generates a research brief and up to five Brave Search queries, then Brave Search and Jina Reader collect and extract a small set of non-social sources. A third Eden AI (DeepSeek) agent writes the LinkedIn draft and an accompanying image prompt, then Google Gemini generates the image. Uploads the image to Google Drive, writes the draft and metadata to a Google Sheets post log, and emails a two-s
Monitor AI search citations and competitors with OpenAI, Google Sheets, and Gmail
Quick overview This workflow runs weekly to test whether fairyfrills.in is cited in OpenAI answers to 15 shopping queries, logs citation details to Google Sheets, and emails a weekly HTML visibility report via Gmail, with optional Slack alerts on workflow errors. How it works Runs once a week on a schedule and generates 15 predefined shopping queries along with the target domain, brand name, and competitor domains. Sends each query to two OpenAI models in parallel: gpt-4o-mini (no browsing) and gpt-4o-search-preview (web search with URLs). Splits the two AI answers into separate items per platform and uses OpenAI to extract citation data (target-domain URLs, competitor citations, citation position, and totals) as structured JSON. Parses the extracted citation JSON, formats key fields (including URL lists, counts, and a response preview), and appends one log row per query and platform to a Google Sheets “Citation Log” sheet. After the final query (ID 15) completes, fetches the logged results from Google Sheets, calculates weekly citation metrics and breakdowns, and generates an HTML report. Sends the weekly citation report email through Gmail to the configured recipient. If any node
Audit website SEO with Groq, Google PageSpeed and Google Sheets
Quick overview This workflow audits a submitted website URL by extracting on-page SEO signals from the HTML, pulling Google PageSpeed Insights scores, and using Groq (Llama 3.3 70B) to generate a scored SEO report, then logs the results to Google Sheets and returns the audit via webhook. How it works Receives a POST webhook request containing a JSON body with a target url to audit. Fetches the page HTML for the provided URL and stops with an error response if no HTML is returned. Extracts on-page SEO signals from the HTML (title, meta description/keywords, headings, image alt coverage, links, canonical, robots, viewport, Open Graph/Twitter tags, schema, word count, and language). Calls the Google PageSpeed Insights API for mobile to retrieve performance, accessibility, SEO, and best-practices results. Combines the extracted on-page data with the PageSpeed results and sends it to Groq via a LangChain agent to produce a strict, structured JSON audit with scores, findings, fixes, and top priorities. Parses and validates the AI JSON output, appends/updates the audit record in Google Sheets, and returns the final audit JSON to the webhook caller (or returns a 400 error if parsing fails)
Generate personalized cold email drafts from Google Sheets with Groq and Tavily
Quick overview This scheduled workflow reads leads from Google Sheets, researches each company with Tavily Search, uses Groq (Llama 3.3 70B) to generate a short personalized cold email, and saves the result as a Gmail draft while updating the lead status back in the sheet. How it works Runs on an hourly schedule trigger. Reads lead rows from Google Sheets and keeps only rows that have an email address and are not marked with status "sent". Processes leads one at a time and uses the Tavily Search API to fetch a brief company overview based on the lead’s company name. Sends the lead details plus the Tavily research summary to Groq (Llama 3.3 70B) to generate a JSON-formatted email subject, body, and personalization hook. Parses and validates the AI output to ensure a subject and body are present, and routes failures to an error log. Creates a Gmail draft with the generated subject and body, updates the corresponding row in Google Sheets with the new status and generated fields, and waits briefly before continuing to the next lead. Setup Create and connect a Google Sheets OAuth2 credential, then select the target spreadsheet and sheet in both the Google Sheets read and update steps. C
Nurture leads from Google Sheets with Gmail, SMS, and OpenRouter AI
Quick overview Automatically nurture leads with AI-personalized email follow-ups (plus optional SMS) across 3 stages triggered hourly, respecting business hours, and fully tracked in Google Sheets. How it works Runs every hour, filtered to a business-hours window (default 9am–6pm, timezone configurable). Reads all leads from Google Sheets and filters those due for follow-up skipping replies, unsubscribes, and completed leads. Routes by stage Stage 1 (Welcome), Stage 2 (Check-in), or Stage 3 (Final nudge). AI writes the email an LLM (via OpenRouter) generates a personalized subject + body using the lead's name, source, and service of interest. Sends via Gmail, and optionally an SMS via Seven/Twilio (Day 1 and Day 4, with consent and dedupe checks). Updates Google Sheets advances the lead's stage, sets the next follow-up timestamp, and marks SMS sent. Setup Import all 4 workflows they share one Google Sheet. Paste your Sheet ID/tab name into each 🔧 CONFIG node (same Sheet ID throughout). Connect Google Sheets, Gmail, and OpenRouter credentials. Edit the 3 LLM prompt nodes to replace "YOUR NAME/company" with your actual brand name. (Optional) Connect Seven/Twilio for SMS, and adjust
Run a hotel WhatsApp concierge using Google Gemini and Google Sheets
Quick overview Youtube Video: https://youtu.be/q2vPN9eub1o?si=lSo4c0kQMNQd_Aad This workflow acts as a WhatsApp hotel concierge that looks up guest profiles, reservations, and open service requests in Google Sheets, consults a Google Docs amenities guide, and uses Google Gemini with Redis memory to reply and optionally create or update reservations and service requests. How it works Triggers when a WhatsApp message is received and continues only if the incoming message contains text. Looks up the guest by WhatsApp number in a Google Sheets “Guest Details” spreadsheet and checks whether Do Not Disturb (DND) is enabled. If the guest is not in DND, fetches the guest’s reservations and any incomplete service requests from Google Sheets. Determines whether the guest is new, currently checked in (based on today’s date between check-in and check-out), and whether any requests are pending, then packages this context for the assistant. Uses Google Gemini with Redis chat memory to generate a WhatsApp-ready reply, calling a Google Docs amenities document when answering policy/pricing/amenity questions. When appropriate, the assistant writes back to Google Sheets to create or update guest prof
Send multi-carrier shipping quotes via WhatsApp with Gemini and ShipEngine
Quick overview Youtube Video: https://youtu.be/jIGBUW_1Sx0?si=BNXzk95soO0Nefan This workflow responds to incoming WhatsApp messages, validates the sender in HighLevel, uses Google Gemini with Redis memory to collect shipment details, fetches multi-carrier rates from ShipEngine, applies a commission markup, logs the quote to Google Sheets, and sends the best options back via WhatsApp. How it works Triggers when a new WhatsApp message is received. Looks up the sender’s phone number in HighLevel and stops outreach if the contact is marked Do Not Disturb. Uses a Google Gemini-powered agent with Redis chat memory to collect and confirm shipment details, creating the contact in HighLevel if needed or marking them DND if they opt out. If shipment data collection is complete, requests shipping rates from the ShipEngine Rates API for the configured carriers. Calculates a commission markup, filters for valid rates, and selects the cheapest and fastest options to format a quote message. Appends the quote text and metadata to a Google Sheets spreadsheet and sends the quote back to the customer via WhatsApp. Setup Connect WhatsApp Business credentials for both the WhatsApp trigger and send acti
Generate English–Polish vocabulary quizzes with Google Sheets and Groq
Quick overview Tool useful for any language exams. It is a chat-based workflow that uses Google Sheets in Structure English|your language that using free Groq model (Llama 3.3) generate lists of 10 words that you need to provide answer based on your while model helps How it works Receives a chat message as the trigger input. Checks whether the message contains the word “generate” to decide if it should create a new quiz set or continue the current session. When “generate” is included, reads vocabulary rows (English and your language columns) from a specified Google Sheets range. Randomly shuffles the rows, selects 10 pairs, and formats them as a clean list of {english, your-language} objects. Sends the user message and the selected word pairs to a Groq Llama 3.3 chat model that runs the quiz conversation. Uses a buffer memory window to keep recent chat context so the agent can track which words are answered and which still need guesses. Setup Connect Google Sheets OAuth credentials and set the correct spreadsheet URL, sheet name, and range that contains “English word” and “your language words” columns. Add Groq API credentials and confirm the selected model (llama-3.3-70b-versatile
Score LinkedIn leads in Google Sheets with Bright Data and Claude
Quick overview This workflow watches a Google Sheets leads sheet, enriches each new lead with LinkedIn person and company data from Bright Data, then uses Anthropic Claude to generate a 0–100 lead score and reason and updates the sheet status to HOT or DONE. How it works Triggers when a new row is added to a Google Sheets worksheet. Reads the leads from the sheet and iterates through the rows that match the configured Status filter. For each lead, uses Bright Data to fetch structured data from the lead’s LinkedIn person profile, then waits briefly to respect rate limits. Uses Bright Data to fetch structured data from the lead’s current company LinkedIn page, then waits briefly to respect rate limits. Sends the person and company details to Anthropic Claude to return a JSON score (0–100) and a one-sentence reason. Parses the JSON response, flags leads with scores ≥ 70 as HOT 🔥 and others as DONE, and writes the enriched fields (title, company, size, location, connections, score, reason) back to Google Sheets. Setup Connect Google Sheets OAuth credentials (Trigger and Google Sheets) and replace YOUR_GOOGLE_SHEET_ID with your spreadsheet ID. Add a Bright Data API credential and ensur
Create blog drafts, images, and LinkedIn posts with Tavily, Gemini, and OpenAI
Quick overview This workflow receives a blog request via webhook, researches the topic with Tavily, generates a long-form HTML article using Google Gemini, creates two images via the kie.ai API, stores assets in Google Drive, updates a Google Sheets tracker, and notifies a Slack user with links. How it works Receives a POST webhook request containing a Google Sheets row payload with an “AI Blog Title” and related metadata. Searches the web for supporting sources using Tavily and passes the research plus the title to Google Gemini to generate the full article as HTML. Converts the generated content to HTML, creates a temporary HTML file in Google Drive, downloads it to set the correct text/html MIME type, re-uploads it as the final Drive file, and deletes the temporary file. Sends the finished article to OpenAI to generate a short LinkedIn post, then updates the matching row in Google Sheets with a Done flag, the article folder/link value, and the LinkedIn post text. Creates a cover image and an in-article infographic by submitting two text-to-image jobs to the kie.ai API, polling until each job succeeds, downloading each resulting image, and uploading both images to Google Drive. W
Qualify open house leads and send AI follow-ups with Google Sheets and Gmail
Quick overview When a visitor signs in at your open house, this workflow instantly scores their buying intent using Gemini AI, sends a personalized follow-up email via Gmail, logs every visitor to Google Sheets, and alerts the agent for hot leads only. How it works A visitor signs in via your Google Form at the open house. Their details — name, email, phone, budget, timeline, and buying intent — are captured automatically. AI (Gemini) scores them as Hot, Warm, or Cold based on their responses and drafts a personalized follow-up email in the same step. A tailored thank-you and next-step email sends immediately via Gmail. Every visitor is logged to Google Sheets with their score, reasoning, and message sent. If a lead scores Hot, the agent receives an instant notification email — and optionally a Slack alert — so they can prioritize personal outreach right away. Setup Connect credentials for Google Sheets (trigger and append), Google Gemini (PaLM API), and Gmail (to send visitor follow-ups and agent notifications). Set the Google Sheets Trigger document and sheet to your sign-in responses sheet, and map the expected column headers (Full Name, Email Address, Phone Number, property, bu
Generate digital product launch content with OpenAI GPT-4o-mini and Google Sheets
Quick overview This workflow generates a multi-channel digital product launch content pack from product details, using OpenAI to create a blog intro, LinkedIn post, X post, Instagram caption, and launch email, and can optionally append the results to Google Sheets. How it works Runs manually when you execute the workflow. Loads sample product details such as name, tagline, price, URL, target audience, and brand tone. Sends the product details to OpenAI (GPT-4o-mini) with instructions to return a JSON content pack for blog, LinkedIn, X, Instagram, and email. Normalizes and validates the returned JSON, ensuring all five content fields are present and formatted as plain text. Optionally appends the generated content fields as a new row in Google Sheets (when the Google Sheets step is enabled). Setup Add an OpenAI API credential and select it in the OpenAI Chat Model configuration. Replace the sample product fields (especially productURL and brandTone) with your own product data or connect a real data source. (Optional) Enable the Google Sheets step, add Google Sheets OAuth2 credentials, and set the target spreadsheet ID and sheet name. Requirements n8n instance (cloud or self-hosted)
Monitor AI search visibility with Talordata SERP, OpenAI, and Google Sheets
Quick overview This workflow runs on demand to crawl Google SERP pages via Talordata, aggregates organic results and related searches, uses OpenAI to produce a structured AI Search Visibility report with GEO recommendations and a score, and appends or updates the results in Google Sheets. How it works Starts when you manually execute the workflow and sets the target query, search engine (Google), and initial page. Calls the Talordata MCP Search API to fetch the first SERP page, then extracts pagination metadata and builds a list of pages to crawl. Loops through each SERP page and requests additional results from Talordata using the corresponding page/start value. Normalizes each page into structured datasets for organic results and related searches, and aggregates all page data into a single consolidated SERP payload. Sends the consolidated SERP dataset to OpenAI to generate a structured AI Search Visibility report (metrics, domain categorization, opportunities, recommendations, executive summary, and score). Parses the model output into JSON and appends or updates a matching row in Google Sheets keyed by the SERP link. Setup Add a Talordata Bearer Auth credential and confirm acces
Create SEO blog posts from YouTube videos with Gemini and Google Docs
Quick overview Submit a YouTube URL and get a publish-ready SEO blog post. Three Gemini agents research the video, write the article, and score it. Articles scoring 7+ auto-publish to Google Docs. Lower scores route to Telegram for review. How it works The workflow starts when a POST request hits the webhook with a YouTube URL, optional target keyword, and tone. A Code node extracts the video ID and validates the URL format, then an HTTP Request node calls YouTube Data API v3 to pull the video title, description, channel name, and tags. Three Basic LLM Chain nodes run in sequence, each powered by a Google Gemini Flash sub-node connected via the native ai_languageModel port. The first chain (Research Agent) receives the video context and returns a structured JSON brief containing an SEO title, four H2 headings, primary keyword, secondary keywords, key insights, target audience, and a content angle. A Code node parses this output with a JSON fallback in case Gemini adds unexpected formatting. The second chain (Writer Agent) takes the research brief and writes a complete 1,000–1,400 word blog post following strict rules: flowing paragraphs over bullet lists, primary keyword used 3–5 t
Detect visual regressions with Apify, Google Gemini, Sheets and Linear
Quick overview This workflow generates baseline website screenshots with Apify, stores them in Google Drive, and logs the file IDs in Google Sheets, then runs scheduled visual regression checks by comparing new screenshots against the baselines with Google Gemini Vision and creating a consolidated Linear issue when changes are detected. How it works Manually starts to backfill missing baselines by reading URLs from Google Sheets that do not yet have a stored base image. For each missing baseline URL, calls Apify’s screenshot actor, downloads the rendered image, uploads it to Google Drive, and updates the matching Google Sheets row with the Drive file ID. Runs weekly on a schedule and reads the list of webpages to test from Google Sheets. For each webpage, downloads the baseline image from Google Drive and captures a fresh screenshot via Apify. Sends both images to Google Gemini (vision) to detect visual differences and returns a structured list of regressions (text, number, image, color, or position). Filters out pages with no detected changes, aggregates the remaining results, and creates a Linear issue containing the regression report. Setup Add an Apify API token as HTTP Query A
Sync Google Drive documents to Pinecone RAG with Google Gemini embeddings
Quick overview This workflow runs on a schedule to sync files from a Google Drive folder into a Pinecone vector index for RAG, extracting text from PDFs, XLSX, Google Docs, and spreadsheets, generating embeddings with Google Gemini, and tracking file state in a Google Sheets log to handle updates and deletions. How it works Runs on a schedule and fetches the current file list from a target Google Drive folder and the existing file log from Google Sheets. Compares Google Drive files with the Google Sheets log to detect new/updated files to ingest and files that were deleted from Drive. For new or updated files, deletes any existing vectors in Pinecone for the file ID, downloads the file from Google Drive, and routes it by MIME type. Extracts text from PDFs, XLSX/Google Sheets, and plain text/Google Docs files and maps the extracted content with file metadata (file ID, name, modified time, and MIME type). Chunks the document text, generates embeddings with Google Gemini, and inserts the resulting vectors and metadata into a Pinecone index. Appends or updates the Google Sheets log with the latest file metadata, and for deleted Drive files it deletes matching vectors in Pinecone and re