HumationHuman + Automation
Back to Catalog

Generate AI-powered lease renewal offers with Ollama LLM, Supabase and Gmail

Lakindu SiriwardanaLakindu Siriwardana
316 views
2/3/2026
File MonitoringScheduled TriggerEmail NotificationGoogle DriveAutomation
Official Page

📄 Automated Lease Renewal Offer by Email

✅ Features

  • Automated Lease Offer Generation using AI (Ollama model).
  • Duplicate File Check to avoid reprocessing the same customer.
  • Personalized Offer Letter creation based on customer details from Supabase.
  • PDF/Text File Conversion for formatted output.
  • Automatic Google Drive Management for storing and retrieving files.
  • Email Sending with generated offer letter attached.
  • Seamless Integration with Supabase, Google Drive, Gmail, and AI LLM.

⚙️ How It Works

  1. Trigger: Workflow starts on form submission with customer details.

  2. Customer Lookup:

  • Searches Supabase for customer data.
  • Updates customer information if needed.
  1. File Search & Duplication Check:

  • Looks for existing lease offer files in Google Drive.

  • If duplicate found, deletes old file before proceeding.

  1. AI Lease Offer Creation:
  • Uses the LLM Chain (offerLetter) to generate a customized lease renewal letter.
  1. File Conversion:
  • Converts AI-generated text into a downloadable file format.
  1. Upload to Drive:
  • Saves the new lease offer in Google Drive.
  1. Email Preparation:

  • Uses Basic LLM Chain-email to draft the email body.

  • Downloads the offer file from Drive and attaches it.

  1. Email Sending:
  • Sends the renewal offer email via Gmail to the customer.

🛠 Setup Steps

  1. Supabase Connection:

  • Add Supabase credentials in n8n.

  • Ensure a customers table exists with relevant columns.

🔜Future Steps

  • Add specific letter template (organization template).
  • PDF offer letter

Generate AI-Powered Lease Renewal Offers with Ollama LLM, Supabase, and Gmail

This n8n workflow automates the process of generating personalized lease renewal offers using an AI Large Language Model (LLM) and then sending these offers via email. It leverages Supabase for data storage and Google Drive for document management.

What it does

This workflow streamlines the creation and distribution of lease renewal offers through the following steps:

  1. Triggers on Form Submission: The workflow starts when a new submission is received via an n8n form. This form likely captures details necessary for generating a lease renewal offer.
  2. Edits Fields: It processes and transforms the incoming data from the form submission, potentially cleaning or reformatting it for subsequent steps.
  3. Retrieves Data from Supabase: The workflow queries a Supabase database to fetch relevant information, which could include tenant details, property information, or current lease terms.
  4. Generates Lease Renewal Offer with Ollama LLM: It utilizes a Basic LLM Chain node, specifically configured with an Ollama Chat Model, to dynamically generate a personalized lease renewal offer. This step leverages AI to craft the offer content based on the data provided.
  5. Converts Offer to File: The generated lease renewal offer (likely text or structured data) is converted into a file format, suitable for attachment or storage.
  6. Uploads to Google Drive: The generated lease renewal offer file is uploaded to Google Drive, ensuring a centralized and accessible storage for all offers.
  7. Sends Email via Gmail: Finally, the workflow sends an email via Gmail, presumably to the tenant, containing the personalized lease renewal offer. It may include the Google Drive link or the attached file.
  8. Conditional Logic: An "If" node is present, suggesting that there might be conditional logic within the workflow to handle different scenarios or outcomes based on the data or the success of previous steps, though the specific conditions are not detailed in the provided JSON.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Supabase Account: Configured with a database containing relevant lease and tenant information.
  • Ollama LLM: An accessible Ollama instance or service configured as a credential in n8n for the LLM Chat Model.
  • Google Drive Account: Configured as a credential in n8n for file storage.
  • Gmail Account: Configured as a credential in n8n for sending emails.

Setup/Usage

  1. Import the workflow: Download the provided JSON and import it into your n8n instance.
  2. Configure Credentials:
    • Set up your Supabase credentials.
    • Set up your Ollama credentials for the Chat Model.
    • Set up your Google Drive credentials.
    • Set up your Gmail credentials.
  3. Configure the n8n Form Trigger: Customize the "On form submission" node to collect the necessary input for your lease renewal offers (e.g., tenant name, property address, current rent, desired new rent, lease term).
  4. Customize the "Edit Fields" node: Adjust this node to correctly map and transform the data from your form submission to the format expected by subsequent nodes.
  5. Configure the Supabase node: Specify the table and query parameters to retrieve the correct data from your Supabase database.
  6. Refine the "Basic LLM Chain" and "Ollama Chat Model": Adjust the prompt and model parameters to ensure the generated lease renewal offers are accurate, professional, and personalized to your needs.
  7. Configure the "Convert to File" node: Choose the desired output file format (e.g., PDF, DOCX) and ensure the content is correctly structured.
  8. Configure the "Google Drive" node: Specify the folder where the generated files should be uploaded.
  9. Configure the "Gmail" node: Define the recipient email address (dynamically from the form or Supabase data), subject, and email body. Ensure the generated file or its Google Drive link is included as an attachment or in the email content.
  10. Review and Activate: Test the workflow thoroughly with sample data to ensure all steps function as expected before activating it for production use.
  11. Conditional Logic (If node): If specific conditions are required, configure the "If" node to route the workflow based on criteria like successful offer generation, tenant type, or other business rules.

Related Templates

Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets

This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.

Ranjan DailataBy Ranjan Dailata
161

Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax

Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions

Daniel NkenchoBy Daniel Nkencho
601

Automate invoice processing with OCR, GPT-4 & Salesforce opportunity creation

PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive ➜ Download PDF ➜ OCR text ➜ AI normalize to JSON ➜ Upsert Buyer (Account) ➜ Create Opportunity ➜ Map Products ➜ Create OLI via Composite API ➜ Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content → the parsed JSON (ensure it’s an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id ➜ build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total ➜ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger → Download File From Google Download File From Google → Extract from File → Update File to One Drive Extract from File → Message a model Message a model → Create or update an account Create or update an account → Create an opportunity Create an opportunity → Build SOQL Build SOQL → Query PricebookEntries Query PricebookEntries → Code in JavaScript Code in JavaScript → Create Opportunity Line Items --- Quick setup checklist 🔐 Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. 📂 IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) 🧠 AI Prompt: Use the strict system prompt; jsonOutput = true. 🧾 Field mappings: Buyer tax id/name → Account upsert fields Invoice code/date/amount → Opportunity fields Product name must equal your Product2.ProductCode in SF. ✅ Test: Drop a sample PDF → verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep “Return only a JSON array” as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields don’t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your org’s domain or use the Salesforce node’s Bulk Upsert for simplicity.

Le NguyenBy Le Nguyen
942