Workflow Templates

This n8n template allows you to perform real-time currency conversions by simply sending a webhook request. By integrating with the ExchangeRate.host API, you can get up-to-date exchange rates for over 170 world currencies, making it an incredibly useful tool for financial tracking, e-commerce, international business, and personal budgeting. 🔧 How it works Receive Conversion Request Webhook: This node acts as the entry point for the workflow, listening for incoming POST requests. It's configured to expect a JSON body containing: from: The 3-letter ISO 4217 currency code for the source currency (e.g., USD, PHP). to: The 3-letter ISO 4217 currency code for the target currency (e.g., EUR, JPY). amount: The numeric value you want to convert. Important: The ExchangeRate.host API access_key is handled securely by n8n's credential system and should not be included in the webhook body or headers. Convert Currency: This node makes an HTTP GET request to the ExchangeRate.host API (api.exchangerate.host). It dynamically constructs the URL using the from, to, and amount from the webhook body. Your API access key is securely retrieved from n8n's pre-configured credentials (HTTP Query Auth type) and automatically added as a query parameter (access_key). The API then performs the conversion and returns a JSON object with the conversion details. Respond with Converted Amount: This node sends the full currency conversion result received from ExchangeRate.host back to the service that initiated the webhook. 👤 Who is it for? This workflow is ideal for: E-commerce Platforms: Display prices in local currencies on the fly for international customers. Convert incoming international payments to your local currency for accounting. Calculate shipping costs in different currencies. Financial Tracking & Budgeting Apps: Update personal or business budgets with converted values. Track expenses incurred in foreign currencies. Automate portfolio value conversion for multi-currency investments. International Business & Freelancers: Generate invoices in a client's local currency based on your preferred currency. Quickly estimate project costs or earnings in different currencies. Automate reconciliation of international transactions. Travel Planning: Convert travel expenses from one currency to another while abroad. Build simple tools to estimate costs for trips in different countries. Data Analysis & Reporting: Standardize financial data from various sources into a single currency for unified reporting. Build dashboards that display converted financial metrics. Custom Integrations: Connect to CRMs, accounting software, or internal tools to automate currency-related tasks. Build chatbots that can answer currency conversion queries. 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "from": "USD", "to": "PHP", "amount": 100 } The workflow will return a JSON response similar to this (results will vary based on currencies and amount): { "date": "2025-06-03", "historical": false, "info": { "rate": 58.749501, "timestamp": 1717398188 }, "query": { "amount": 100, "from": "USD", "to": "PHP" }, "result": 5874.9501, "success": true } ⚙️ Setup Instructions Get an ExchangeRate.host Access Key: Go to https://exchangerate.host/ and sign up for a free API key. Create an n8n Credential for ExchangeRate.host: In your n8n instance, go to Credentials. Click "New Credential" and search for "HTTP Query Auth". Set the Name (e.g., ExchangeRate.host API Key). Set API Key to your ExchangeRate.host access key. Set Parameter Name to access_key. Set Parameter Position to Query. Save the credential. Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure ExchangeRate.host API Node: Double-click the Convert Currency node. Under "Authentication", select "Generic Credential Type". Choose "HTTP Query Auth" as the Generic Auth Type. Select the credential you created (e.g., "ExchangeRate.host API Key") from the dropdown. Configure Webhook Path: Double-click the Receive Conversion Request Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /convert-currency). Activate Workflow: Save and activate the workflow. 📝 Tips This workflow is a powerful starting point. Here's how you can make it even more robust and integrated: Robust Error Handling: Add an IF node after Convert Currency to check {{ $json.success }}. If false, branch to an Error Trigger node or send an alert (e.g., Slack, Email) with {{ $json.error.info }} to notify you of API issues or invalid inputs. Include a Try/Catch block to gracefully handle network issues or malformed responses. Input Validation & Defaults: Add a Function node after the webhook to validate if from, to, and amount are present and in the correct format. If not, return a clear error message to the user. Set default from or to currencies if they are not provided in the webhook, making the API more flexible. Logging & Auditing: After a successful conversion, use a Google Sheets, Airtable, or database node (e.g., PostgreSQL, MongoDB) to log every conversion request, including the input currencies, amount, converted result, date, and possibly the calling IP (from the webhook headers). This is crucial for financial auditing and analysis. Rate Limits & Caching: If you anticipate many requests, be mindful of ExchangeRate.host's API rate limits. You can introduce a Cache node to store recent conversion results for a short period, reducing redundant API calls for common conversions. Alternatively, add a Delay node to space out requests if you're hitting limits. Format & Rounding: Use a Function node or Set node to format the result to a specific number of decimal places (e.g., {{ $json.result.toFixed(2) }}). Add currency symbols or full currency names to the output for better readability. Alerting on Significant Changes: Chain this workflow with a Cron or Schedule node to periodically fetch exchange rates for a pair you care about (e.g., USD to EUR). Use an IF node to compare the current rate with a previously stored rate. If the change exceeds a certain percentage, send an alert via Slack, Email, or Telegram to notify you of significant market shifts. Integration with Payment Gateways: For e-commerce, combine this with nodes for payment gateways (e.g., Stripe, PayPal) to automatically convert customer payments received in foreign currencies to your base currency before recording. Multi-currency Pricing for Products: Use this workflow in conjunction with your product database. When a user selects a different country/currency, trigger this webhook to dynamically convert product prices and display them instantly.

Automate expense reviews with AI-powered CFO-level analysis. This workflow monitors Airtable expense submissions, uses GPT-4 to analyze expenses like an experienced CFO, flags suspicious expenses with detailed reasoning, and maintains comprehensive audit trails in Pinecone vector database. 🚀 What It Does Smart Monitoring**: Watches Airtable for new expense submissions AI CFO Analysis**: GPT-4 applies financial expertise to review amounts, categories, and descriptions Intelligent Flagging**: Automatically identifies policy violations and suspicious patterns Audit Trail**: Stores all decisions in Pinecone for compliance and searchability Auto Updates**: Updates Airtable records with AI decisions and detailed reasoning 🎯 Perfect For Finance teams needing intelligent expense oversight CFOs wanting to automate expense policy enforcement Growing companies scaling expense management Businesses requiring compliance documentation ⚙️ Key Benefits ✅ 99% faster expense processing vs manual review ✅ CFO-level intelligence applied to every expense ✅ Complete audit trail for compliance ✅ Real-time fraud detection and policy enforcement ✅ Detailed explanations for every decision 🔧 What You Need Airtable base with expense data (template included) OpenAI API for GPT-4 analysis Pinecone account for audit trail storage Basic expense submission process 📊 Sample Results Input: $4,500 business class flight to Tokyo AI Decision: "Flagged - Amount exceeds typical travel thresholds. Requires verification against travel policies and client justification for premium travel." 🛠️ Setup & Support Quick Setup: Deploy in 60 minutes with included templates and documentation YouTube: https://www.youtube.com/@YaronBeen/videos 💼 Expert Support LinkedIn: https://www.linkedin.com/in/yaronbeen/ 📧 Direct Help Email: Yaron@nofluff.online Transform expense management from manual bottleneck to intelligent automation. Let AI handle policy compliance while your finance team focuses on strategy.

Analyze and Explore your ZenDesk Support Requests using AI-Powered Knowledge Graph This template helps you create an interactive InfraNodus knowledge graph for your ZenDesk tickets using any search criteria (e.g. after a certain date, specific status, sender, keyword) that will automatically be sent to a selected Slack channel. Here's an example of the InfraNodus graph that shows the main topics and gaps in ZenDesk support tickets: You can use the workflow to: Get an instant overview of the main topics your customers are talking about Generate business and product ideas based on the blind spots identified using the InfraNodus AI See which topics correlate to the negative / positive sentiment understanding the weak and strong sides of your product and support Receive daily notifications on the main topics your customers are talking about via Slack / Telegram / Email and other channels Perform detailed search using a password-protected web form for tickets filtered by a certain date, status, tag, sender, keyword. Use the interactive graph to explore specific topics and concepts your customers are talking about — a great way to engage with their concerns in a non-linear way, bypassing the boring tabular interface Use the graph to explore the support requests by specific segments — e.g. status, priority, sentiment, tags, urgency. Use the graph generated as an AI expert available to your AI agents in other n8n workflows via InfraNodus GraphRAG. For instance, you could connect your knowledge base to the support tickets graph and let the agent discover possible solutions to your customers' most typical problems. See an sample template here. How it works You can start this workflow manually, with a daily / weekly trigger, or via a password-protected web form, where you can provide search requests. Once started, it will perform a ZenDesk tickets search with the default or your custom criteria. Then it will use the search results to generate an InfraNodus graph (or add the new data to an existing one), and — finally — use the InfraNodus AI endpoints to generate a topical summary and a product business idea based on the blind spots identified. The results are delivered a channel of your choice. Here's a description step by step: Start the workflow (manually or on schedule) Assign values to variables (search criteria, graph name) Perform ZenDesk support tickets search Convert the data received and submit it to InfraNodus to generate a knowledge graph Generate topical summary with InfraNodus Generate a business idea with InfraNodus (you can also change the setting to generate a question instead) Send a notification via Slack / Telegram / Email or back to the webform How to use You need an InfraNodus API account and key to use this workflow. You also need a ZenDesk account. It takes about 5 minutes to set everything up. Create an InfraNodus account. Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Add the authorization key to all the InfraNodus HTTP nodes in the template (Steps 3, 5, and 6). Generate a ZenDesk authorization token following the instructions in n8n's ZenDesk node (Step 3). Optionally: connect your Slack or Telegram or Gmail account to receive automated notifications with the link to the graph, once the workflow is ready (it takes about 30 seconds to run). Run it with using the form to play around with the search criteria that works best for you (you can leave everything empty at first), then choose the parameters you like and activate the Daily Trigger node to receive executive summaries to a channel of your choice. Open the graph in InfraNodus and use our customer feedback analysis guide to explore the graph and generate new insights. Requirements An InfraNodus account and API key A ZenDesk API key (Optional) — a Slack / Telegram / Gmail connection for notifications FAQ 1. What are the best use cases to try? I love to set the graph to deliver me a daily visual briefing of what's happening in my support portal. It shows me the main topics and gaps and generates product ideas based on them. Great to keep the pulse on the business. I also really like generating a graph for the past week manually, using the form, and then exploring the graph in InfraNodus directly using the customer feedback analysis workflow to: discover main topics my customers are talking about? understand the topics that have the most negative connotation for them (using the sentiment filter)? discover some support tickets that need more attention or that talk about the topics I'm personally interested in and engage with the client identify the gaps in your customers' discourse based on the blind spots — useful for generating ideas, see the graph below with a demo of how it works: 2. Why use the graph and not just AI summary? AI summary will just give you generic results. You'll see what you already know. Using the graph helps you deconstruct the discourse and get a much more nuanced understanding of the main pain points and interests of your customers. The auto-generated InfraNodus summary and business ideas have a direct explainable connection to the discourse, so you can always see where they are coming from and maintain the focus on all the topics, rather than the most prominent ones. Additionally, having an interactive graph opens a possibility to explore your customers' concerns in a more engaging way, finding the topics and concepts that are relevant to your interests or to your agents' expertise, helping you find the conversations that you'd otherwise have missed. 3. Is my customers' data safe? Absolutely. InfraNodus' terms of use and privacy policy state that the customers' data and text graphs are not used in AI training and are not offered to any third parties. Its underlying API system uses the Open API which explicitly states that data is not used for training either. So all the customers' data are private and safe. As an extra precaution, you can always delete the graphs after you analyzed them, in which case there is no trace of this data left on the servers. Customizing this workflow Check out the complete setup guide for this workflow at https://support.noduslabs.com/hc/en-us/articles/20447530961308-Zendesk-Tickets-Summarization-Sentiment-Analysis-and-Slack-Integration-with-n8n-and-InfraNodus For support with this template, please, contact https://support.noduslabs.com For more InfraNodus n8n workflows, please, see our creators page: https://n8n.io/creators/infranodus/ To learn more about InfraNodus, GraphRAG, and knowledge graph analysis: https://infranodus.com

Use Case: This n8n workflow automates the process of extracting information from emails. It uses OpenAI to summarize sales emails and adds this information in Odoo. How it works: When an email is received with a certain label, it sends the email to OpenAI for summarization A sales opportunity is created in Odoo with the email subject as title and the email summary as internal note Set up steps: Configure Google Cloud credentials with Gmail access In the Gmail node, choose an email label in the filter section Configure OpenAI credentials Configure Odoo credentials

This n8n template provides a simple yet powerful utility for validating if a given string input is a valid JSON format. You can use this to pre-validate data received from external sources, ensure data integrity before further processing, or provide immediate feedback to users submitting JSON strings. 🔧 How it works Webhook: This node acts as the entry point for the workflow, listening for incoming POST requests. It expects a JSON body with a single property: jsonString: The string that you want to validate as JSON. Code (JSON Validator): This node contains custom JavaScript code that attempts to parse the jsonString provided in the webhook body. If the jsonString can be successfully parsed, it means it's valid JSON, and the node returns an item with valid: true. If parsing fails, it catches the error and returns an item with valid: false and the specific error message. This logic is applied to each item passed through the node, ensuring all inputs are validated. Respond to Webhook: This node sends the validation result (either valid: true or valid: false with an error message) back to the service that initiated the webhook request. 👤 Who is it for? This workflow is ideal for: Developers & Integrators: Pre-validate JSON payloads from external systems (APIs, webhooks) before processing them in your workflows, preventing errors. Data Engineers: Ensure the integrity of JSON data before storing it in databases or data lakes. API Builders: Offer a dedicated endpoint for clients to test their JSON strings for validity. Customer Support Teams: Quickly check user-provided JSON configurations for errors. Anyone handling JSON data: A quick and easy way to programmatically check JSON string correctness without writing custom code in every application. 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "jsonString": "{\"name\": \"n8n\", \"type\": \"workflow\"}" } Example of an invalid JSON string: { "jsonString": "{name: \"n8n\"}" // Missing quotes around 'name' } The workflow will return a JSON response indicating validity: For a valid JSON string: { "valid": true } For an invalid JSON string: { "valid": false, "error": "Unexpected token 'n', \"{name: \"n8n\"}\" is not valid JSON" } ⚙️ Setup Instructions Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure Webhook Path: Double-click the Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /validate-json). Activate Workflow: Save and activate the workflow. 📝 Tips This JSON validator workflow is a solid starting point. Consider these enhancements: Enhanced Error Feedback: Upgrade: Add a Set node after the Code node to format the error message into a more user-friendly string before responding. Leverage: Make it easier for the caller to understand the issue. Logging Invalid Inputs: Upgrade: After the Code node, add an IF node to check if valid is false. If so, branch to a node that logs the invalid jsonString and error to a Google Sheet, database, or a logging service. Leverage: Track common invalid inputs for debugging or improvement. Transforming Valid JSON: Upgrade: If the JSON is valid, you could add another Function node to parse the jsonString and then operate on the parsed JSON data directly within the workflow. Leverage: Use this validator as the first step in a larger workflow that processes JSON data. Asynchronous Validation: Upgrade: For very large JSON strings or high-volume requests, consider using a separate queueing mechanism (e.g., RabbitMQ, SQS) and an asynchronous response pattern. Leverage: Prevent webhook timeouts and improve system responsiveness.

This n8n workflow integrates Shopify order management with Telegram, allowing you to query open orders and order details directly through Telegram chat commands. It provides an interactive way to monitor your Shopify store orders using Telegram as an interface. Key Features Telegram Trigger: Listens for messages and callback queries from your Telegram bot. Switch Node: Routes incoming Telegram messages to different flows based on message content: /orders command to fetch all open orders Callback queries starting with /order_ to fetch details of a specific order Shopify Get Orders: Retrieves all open orders from your Shopify store using your Shopify API credentials. Conditional Check (If Node): Determines if there are any open orders; branches accordingly: If orders exist, prepare an interactive Telegram message with a list of orders.1 If no orders exist, send a “No Order” message. Orders Code Node: Formats the list of open orders into a Telegram message with inline buttons. Each button corresponds to an order and sends a callback data containing the order ID. Get Order Details: When a user selects an order button, the workflow extracts the order ID from the callback data, fetches detailed order information from Shopify, and formats the order items into a readable message. Send Messages to Telegram: Sends formatted messages back to Telegram: The list of open orders with clickable buttons. Detailed information about a selected order. “No Order” notification if there are no open orders. How It Works A Telegram user sends /orders to the bot. The workflow fetches open orders from Shopify and sends a message with buttons listing each order. When a user clicks an order button, the workflow fetches and displays detailed information about that specific order in Telegram. If there are no open orders, the bot replies accordingly. Setup Instructions Create a Telegram Bot: Use @BotFather on Telegram to create a bot and get the bot token. Obtain Shopify API Credentials: Create a private app in your Shopify admin dashboard with permission to read orders. Obtain the API key and access token. Configure n8n Credentials: Add your Telegram bot token as Telegram API credentials in n8n. Add your Shopify API credentials in n8n Shopify credentials. Import the Workflow: Import this workflow into your n8n instance. Update the Telegram and Shopify credential nodes to use your credentials. Set Webhook URLs: Ensure your Telegram bot webhook is set correctly to receive messages. n8n webhook URLs should be publicly accessible. Test the Workflow: Send /orders to your Telegram bot to verify it retrieves and lists open orders. Customization Guidance Modify Commands: Update the Switch node to add more Telegram commands or change existing ones. Change Message Formats: Edit the Code nodes to customize how order lists and details appear. Expand Shopify Integration: Add nodes to handle other Shopify operations like updating orders, managing products, etc. Multi-User Support: Adapt the workflow to handle multiple Telegram chat IDs dynamically. Security and Implementation Notes The native Telegram node in n8n has limitations: it does not support sending dynamic inline keyboard arrays in JSON format, which is essential for displaying a variable number of buttons depending on how many orders are retrieved from Shopify. To overcome this, this workflow uses the HTTP Request node to call Telegram’s API directly, allowing full flexibility to send dynamic inline keyboards as JSON objects. (I will make an update once Telegram Node support dynamic inline keyboards). Security Considerations:** Always store your Telegram bot token securely in n8n credentials and never expose it in the HTTP Request node’s URL or body directly. Use environment variables or n8n credentials to inject tokens safely. Be mindful of Telegram API rate limits and add error handling in your workflow. While using HTTP Request nodes increases flexibility, it also requires careful management of request payloads and authentication, as opposed to the built-in Telegram node which abstracts much of this complexity. Benefits Quickly access Shopify order data without leaving Telegram. Interactive inline buttons improve user experience. Automated, real-time integration between Shopify and Telegram.

This automated n8n workflow checks daily class schedules, syncs upcoming classes to Google Calendar, and sends reminder notifications to students via email or SMS. Perfect for educational institutions to keep students informed about their daily classes and schedule changes. What This Workflow Does: Automatically checks class schedules every day Identifies today's classes and upcoming sessions Syncs class information to Google Calendar Sends personalized reminders to enrolled students Tracks reminder delivery status and logs activities Handles both email and SMS notification preferences Main Components Daily Schedule Check** - Triggers daily to check class schedules Read Class Schedule** - Retrieves today's class schedule from database/Excel Filter Today's Classes** - Identifies classes happening today Has Classes Today?** - Checks if there are any classes scheduled Read Student Contacts** - Gets student contact information for enrolled classes Sync to Google Calendar** - Creates/updates events in Google Calendar Create Student Reminders** - Generates personalized reminder messages Split Into Batches** - Processes reminders in manageable batches Email or SMS?** - Routes based on student communication preferences Prepare Email Reminders** - Creates email reminder content Prepare SMS Reminders** - Creates SMS reminder content Read Reminder Log** - Checks previous reminder history Update Reminder Log** - Records sent reminders Save Reminder Log** - Saves updated log data Essential Prerequisites Class schedule database/Excel file with student enrollments Student contact database with email and phone numbers Google Calendar API access and credentials SMTP server for email notifications SMS service provider (Twilio, etc.) for text reminders Reminder log file for tracking sent notifications Required Data Files: class_schedule.xlsx: Class ID | Class Name | Date | Time | Duration Instructor | Room | Students Enrolled | Status student_contacts.xlsx: Student ID | Name | Email | Phone | Preferred Contact Program | Class IDs | Active Status reminder_log.xlsx: Log ID | Date | Student ID | Class ID | Contact Method Status | Sent Time | Response Key Features ⏰ Daily Automation:** Runs automatically every day 📅 Calendar Sync:** Syncs classes to Google Calendar 📧 Smart Reminders:** Sends email or SMS based on preference 👥 Batch Processing:** Handles multiple students efficiently 📊 Activity Logging:** Tracks all reminder activities 🔄 Duplicate Prevention:** Avoids sending multiple reminders 📱 Multi-Channel:** Supports both email and SMS notifications Quick Setup Import workflow JSON into n8n Configure daily trigger schedule Set up class schedule and student contact files Connect Google Calendar API credentials Configure SMTP server for emails Set up SMS service provider (Twilio) Test with sample class data Activate workflow Parameters to Configure schedule_file_path: Path to class schedule file contacts_file_path: Path to student contacts file google_calendar_id: Google Calendar ID for syncing google_api_credentials: Google Calendar API credentials smtp_host: Email server settings smtp_user: Email username smtp_password: Email password sms_api_key: SMS service API key sms_phone_number: SMS sender phone number Sample Reminder Messages Email:** "Hi [Name], reminder: [Class Name] starts at [Time] in [Room]. See you there!" SMS:** "[Name], your [Class Name] class starts at [Time] in [Room]. Don't miss it!" Use Cases Daily class reminders for students Schedule change notifications Exam and assignment deadline alerts Teacher absence notifications Room change announcements

A short-term technical analysis agent for 15-minute candles on Binance Spot Market pairs. Calculates and interprets key trading indicators (RSI, MACD, BBANDS, ADX, SMA/EMA) and returns structured summaries, optimized for Telegram or downstream AI trading agents. This tool is designed to be triggered by another workflow (such as the Binance SM Financial Analyst Tool or Binance Quant AI Agent) and is not intended for standalone use. 🔧 Key Features ⏱️ Uses 15-minute kline data (last 100 candles) 📈 Calculates: RSI, MACD, Bollinger Bands, SMA/EMA, ADX 🧠 Interprets numeric data using GPT-4.1-mini 📤 Outputs concise, formatted analysis like: • RSI: 72 → Overbought • MACD: Cross Up • BB: Expanding • ADX: 34 → Strong Trend 🧠 AI Agent Purpose > You are a short-term analysis tool for spotting volatility, early breakouts, and scalping setups. Used by higher agents to determine: Entry/exit precision Momentum shifts Scalping opportunities ⚙️ How it Works Triggered externally by another workflow Accepts input: { "message": "BTCUSDT", "sessionId": "123456789" } Sends POST request to backend endpoint: https://treasurium.app.n8n.cloud/webhook/15m-indicators Fetches last 100 candles and calculates indicators Passes data to GPT for interpretation Returns summary with indicator tags for human readability 🔗 Dependencies This tool is triggered by: ✅ Binance SM Financial Analyst Tool ✅ Binance Spot Market Quant AI Agent 🚀 Setup Instructions Import into your n8n instance Make sure /15m-indicators webhook is active and calculates indicators correctly Connect your OpenAI GPT-4.1-mini credentials Trigger from upstream agent with Binance symbol and session ID Ensure all external calls (to Binance + webhook) are working 🧪 Example Use Cases | Use Case | Result | | ------------------------------------- | --------------------------------------- | | Short-term trade decision for ETHUSDT | Receives 15m signal indicators summary | | Input from Financial Analyst Tool | Returns real-time volatility snapshot | | Telegram bot asks for “DOGE update” | Returns momentum indicators in 15m view | 🎥 Watch Tutorial: 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding or resale permitted. 🔗 For support: Don Jayamaha – LinkedIn

A medium-term trend analyzer for the Binance Spot Market that leverages core technical indicators across 4-hour candle data to provide human-readable swing-trade signals via AI. 🎥 Watch Tutorial: 🎯 What It Does Accepts a Binance trading pair (e.g., AVAXUSDT) Sends the symbol to an internal webhook for technical indicator calculation Computes 4h RSI, MACD, Bollinger Bands, SMA, EMA, ADX Returns structured, GPT-analyzed signals ready for Telegram delivery 🧠 AI Agent Details Model:** GPT-4.1-mini (OpenAI Chat) Agent Role:** Translates raw indicator values into sentiment-labeled signals Memory:** Tracks session + symbol context for cleaner multi-turn logic 🔗 Required Backend Workflow To calculate indicators, this tool depends on: POST https://treasurium.app.n8n.cloud/webhook/4h-indicators { "symbol": "AVAXUSDT" } Returns a JSON object with the latest 40×4h candle-based calculations. 📥 Input Format { "message": "AVAXUSDT", "sessionId": "telegram_chat_id" } 📊 Sample Output 🕓 4h Technical Signals – AVAXUSDT • RSI: 64 → Slightly Bullish • MACD: Bullish Cross above baseline • BB: Upper band touch – volatility expanding • EMA > SMA → Confirmed Upside Momentum • ADX: 31 → Strengthening Trend 📚 Use Case Scenarios | Use Case | Result | | ----------------------------- | ---------------------------------------------------- | | Swing trend confirmation | Uses 4h indicators to validate or reject setups | | Breakout signal confluence | Helps assess if momentum is real or noise | | Inputs to Quant AI or Analyst | Supports higher-frame trade recommendation synthesis | 🛠️ Setup Instructions Import the JSON template into your n8n workspace. Set your OpenAI API credentials for the GPT node. Ensure the /webhook/4h-indicators backend tool is live and accessible. Connect this to your Binance Financial Analyst Tool or master Quant AI orchestrator. 🤖 Parent Workflows That Use This Tool Binance SM Financial Analyst Tool Binance Spot Market Quant AI Agent 📎 Sticky Notes & Annotations This workflow includes internal sticky notes describing: Node roles (GPT, webhook, memory) System behavior (reasoning agent logic) Telegram formatting guidance 🔐 Licensing & Attribution © 2025 Treasurium Capital Limited Company All architecture, prompt logic, and signal formatting are proprietary. Redistribution or rebranding is prohibited. 🔗 Connect with the creator: Don Jayamaha – LinkedIn

Set up a chat with your documents without the complex vector store setup. This templates helps you ingest** your PDF / text / MD documents into a knowledge graph use the graph as the knowledge base for your AI chatbots (and other workflows) visualize the main topics* and *gaps** in your documents (good for observability and research) The knowledge base is provided using the InfraNodus GraphRAG with the knowledge graphs offering high-quality responses without the need to set up complex RAG vector store workflows. The advantages of using GraphRAG instead of the standard vector stores for knowledge are: Easy and quick to set up and update** — no complex data import workflows needed A knowledge graph offers a holistic and interactive view of your knowledge base (accessible via our API or a web interface — also shareable) Better retrieval of relations** between the document chunks = higher quality responses How it works This template uses the InfraNodus knowledge graph as a knowledge base for your n8n AI agent node. The knowledge graph contains the documents you can upload using this template from your Google Drive. When the user asks a question via the chat interface, the agent forwards this question to the InfraNodus knowledge graph, retrieves a response, a summary, and a list of matching statements (based advanced Graph RAG), then delivers the final response back the user. Here's a description step by step: Step 1: Upload your documents Put the PDF / text / MD files you want to chat with into a folder on your Google drive Authorize access to that folder using the Google drive node in the template. Add the InfraNodus API key to the InfraNodus Save to Graph HTTP node Optional: change the name of the graph you want to save the data to in the InfraNodus HTTP node (in the name field of the HTTP post request). Run the workflow to ingest all the files and save them into the graph Optional: check the link provided in the Step 1 workflow description to see the visualization of your knowledge base. It will look something like that: Note:* you can replace the PDF to Text convertor node with a better quality *PDF convertor* from ConvertAPI which respects the original file layout and doesn't split text into small chunks Step 2: Chat with your documents Deactive the trigger in the Step 1 Activate the chat trigger in the Step 2 Add your InfraNodus API credentials to Knowledge Base GraphRAG InfraNodus node Optional: change the graph name in the Knowledge Base node to match the name you provided in the step 1 above Run the chat and ask the question Watch the magic How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Requirements An InfraNodus account and API key An OpenAI (or any other LLM) API key A Google Drive OAuth access (follow the n8n instructions) Optional: ConvertAPI API key for better quality PDF conversion Customizing this workflow You can customize this workflow by adding several experts to your AI agent. Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20174217658396-Using-InfraNodus-Knowledge-Graphs-as-Experts-for-AI-Chatbot-Agents-in-n8n Also check out the video tutorial with a demo: For support and feedback, please, contact us at https://support.noduslabs.com To learn more about InfraNodus: https://infranodus.com

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Fetch SEO and traffic information from ahref for a list of domains in a Google Sheet. This is great for marketing research and SEO workflow optimizations and saves tons of time. How it works We'll import domains from the Google sheet We use an SEO MCP server to fetch data from ahref free tooling The fetched data is stored in the Google sheet Set up steps Copy Google Sheet template and add it in all Google Sheet nodes Make sure that n8n has read & write permissions for your Google sheet. Add your list of domains in the first column in the Google sheet Add MCP credentials for seo-mcp

🚀 How it works (Fonctionnement résumé) : Ce template permet de transformer un document (PDF, TXT, DocX...) en post LinkedIn engageant, prêt à être publié ou validé par email, le tout avec l’aide d’une IA spécialisée en copywriting LinkedIn. Voici les étapes clés : Formulaire de dépôt : L'utilisateur charge un fichier ou colle un texte. Détection du type de contenu : Un Switch analyse le type de fichier (PDF, DOCX, TXT, ou texte brut). Attention pour DocX nécessite un compte Make pour transformer le doc (mais cela fonctionne aussi sans docX) Extraction du contenu : Selon le format, le bon module d'extraction est utilisé. Génération d’un post LinkedIn : L'IA transforme le contenu en post LinkedIn selon une méthodologie de copywriting optimisée. Validation par email : Un email est envoyé à l’utilisateur pour approbation avec possibilité d’ajouter une image. Publication automatique : Si l'utilisateur valide, le post est publié sur LinkedIn. ⚙️ Setup Steps : Connecte tes comptes : Google Docs OAuth LinkedIn OAuth OpenAI (via gpt-4.1-mini ou un autre modèle) SMTP + IMAP pour l'envoi et la lecture d'emails Configure les champs du formulaire dans le nœud Form Trigger selon ton usage. Personnalise le prompt IA dans le nœud AI Agent si tu veux adapter le ton ou la méthodologie. Vérifie les emails dans le nœud d'envoi (Send Email) et de lecture (Email Trigger (IMAP)), pour que la validation fonctionne. Teste le workflow avec différents fichiers pour t'assurer que tous les types sont bien traités (PDF, DOCX, TXT, etc.). 🧩 Cas d’usage typiques : Créer des posts à partir de notes de réunion ou de rapports. Valoriser un article ou une publication professionnelle sous forme de contenu LinkedIn. Déléguer à l'IA le premier jet de ton contenu réseau. Bonus surveille une newsletter de ta messagerie pour proposer un post pertinent sur LinkedIn (vous pouvez supprimer il fonctionne en parallèle)