Arkadiusz
Templates by Arkadiusz
Voice & text control for Home Assistant using Telegram, Whisper & Gemini
📝 Workflow Description This workflow creates a conversational bridge between Telegram / n8n Chat and Home Assistant. It allows users to control smart home devices or request information using natural language (text or voice). ⸻ 🔑 Key Features Multi-channel input: Works with both Telegram and n8n’s chat interface. Voice support: Telegram voice messages are transcribed to text using OpenAI Whisper. AI-driven assistant: Google Gemini processes queries in natural language. Home Assistant integration: Uses MCP client tools to execute actions like turning devices on/off, adjusting lights, or broadcasting messages. Memory management: Short-term memory keeps context within conversations. Smart reply routing: Responses are automatically sent back to the correct channel (Telegram or chat). Message formatting: Telegram replies are beautified (bold, bullet points, inline code, links). ⸻ 📌 Node Overview Telegram Trigger: Captures incoming Telegram messages (text or voice). Bot Is Typing: Sends a “typing…” action to indicate the bot is working. Voice or Text: Separates voice and text inputs. Get Voice File → Speech to Text → Transcription to ChatInput: Handles Telegram voice notes by downloading the file, transcribing it, and preparing it for the chat pipeline. When Chat Message Received: Captures messages from n8n’s built-in chat interface. Process Messages: Normalizes incoming data (input text, source, session ID, voice flag). Home Agent: Main AI agent that processes queries. Google Gemini Chat Model: Language model for intent understanding and conversation. Simple Memory & Simple Memory1: Buffer memories to preserve conversation context. Home Assistant Connector: MCP client node that executes smart home actions (turn on/off devices, adjust lights, etc.). Reply Router: Routes the assistant’s response either to Telegram or to the n8n chat webhook. Telegram Message Beautifier → Telegram Send: Formats and sends responses back to Telegram. Respond to Webhook: Sends responses to n8n chat. ⸻ 🚀 Example Use Cases Send “Turn on the living room lights” via Telegram → Bot triggers Home Assistant action. Ask “What’s the temperature in the bedroom?” → Response comes back formatted in Telegram. Record a voice note “Goodnight mode” → Automatically transcribed and executed by Home Assistant. Use n8n chat to quickly trigger automations or check device statuses. ⸻ ⚡️ Benefits Unified chat & voice control for Home Assistant. AI-powered natural language understanding. Works seamlessly across platforms (Telegram & n8n chat). Extensible: new tools or intents can be added easily.
By ArkadiuszExtract text from receipts with OCR.space table recognition
📝 Description This workflow automates the process of extracting text from receipt or document images using OCR.space and presenting the results in a clean, styled form. It’s especially useful for cases like receipt digitization, invoice parsing, table recognition, or quick OCR text extraction directly inside n8n without third-party dashboards. The workflow is lightweight and self-contained - all you need is an OCR.space API key. --- 🔄 How it works Form Trigger – Upload File A simple form collects the image (max 1 MB) and asks whether the file contains a table. Normalize Inputs Converts the “Yes/No” response into a boolean flag isTable and keeps the uploaded file attached. OCR.space API Call Sends the uploaded image to the OCR.space API with the correct parameters: language=pol (Polish by default, can be changed) OCREngine=2 isTable flag Display Results The parsed text (ParsedResults[0].ParsedText) is rendered in a styled card with monospace formatting for easier reading and copy-paste. --- 🎯 Use cases Receipt OCR for expense tracking Invoice or document text digitization Table parsing from scanned files Quick OCR text preview in n8n flows --- ⚙️ Requirements OCR.space API key (Header Authentication) n8n instance running ≥ v1.20 --- 📌 Notes & Customization Language: change language parameter (eng, deu, etc.) to match your input. Validation: add a file size check if you expect larger files. Error handling: add an Error Trigger if you anticipate API rate limits. Table vs Text: enabling isTable improves structured data parsing. --- 🔑 Keywords OCR, receipt parsing, document OCR, invoice automation, text extraction, table recognition, AI OCR, OCR.space, workflow automation
By ArkadiuszGenerate sprint review summaries from transcripts with OpenAI and Google Sheets
What this workflow does This template automates the entire process of documenting Sprint Reviews in Scrum: Input Collection – Through a friendly form, users upload the transcript file (meeting notes, sprint review transcript, or VTT captions) and specify the sprint name and domain. Transcript Parsing – A Code node formats the transcript into clean [HH:MM:SS] Speaker: text lines, supporting VTT, Zoom, or custom timestamp formats used in Scrum events. AI-Driven Summary – The AI Agent (LangChain + OpenAI) produces a well-structured AI summarization in Markdown, including: A 3–5 bullet Executive Summary of sprint review highlights A Presentation Recap table (Timestamp | Presenter | Topics) A list of Action Items with owners (if recognizable from the transcript) Preview – The summary renders as a styled card with custom CSS for easy readability in n8n. Archive – Automatically appends a record to Google Sheets, saving the date, domain, sprint, transcript file name, and the AI-generated sprint review summary. Why it’s useful Zero manual summarizing – AI extracts key insights from transcript files into Markdown you can instantly share with your Scrum team and stakeholders. Easy setup – drag-and-drop import, plus form-based input for non-technical users during sprint reviews. Centralized tracking – all past sprint summaries live in one spreadsheet for retrospectives, audits, and continuous improvement. Flexible and extendable – you can switch to Airtable, Slack, or Notion, or refine the summary template to match your Scrum workflow. Ideal for Scrum Masters wanting quick sprint review summaries for stakeholders Agile Coaches analyzing sprint review transcripts, presentation patterns, and follow-up tasks Product Owners keeping a searchable log of sprint outcomes and action items Prerequisites / Credentials OpenAI API Key — required for the AI Agent node (or any other Agent for summarization) Google Sheets OAuth2 credentials — required for saving sprint review data to Sheets (Optional) Ensure LangChain / AI Agent nodes are installed in your n8n instance How to Use This Template Import the workflow JSON into your n8n instance. Set up credentials: For the OpenAI LLM node, provide your OpenAI API key In Google Sheets, configure OAuth2 and specify your spreadsheet ID (replace YOURSHEETID) Create a new sheet with the following columns: Date Domain Sprint name Content VTT file Transcript Enable and run the workflow. Fill out the form: upload transcript file, enter sprint & domain, click Create Summary. View the AI-generated Markdown sprint review summary in the preview card. Verify the new entry appears in your Google Sheet with all sprint details.
By ArkadiuszGenerate custom icons with OpenAI GPT image & Google Drive auto-storage
Workflow Description: Turn a simple text idea into production-ready icons in seconds. With this workflow, you input a subject (e.g., “Copy”, “Banana”, “Slack Mute”), select a style (Flat, 3D, Cartoon, etc.), and off it goes. Here’s what happens: A form trigger collects your icon subject, style and optional background. The workflow uses an LLM to construct an optimised prompt. An image-generation model (OpenAI image API) renders a transparent-background, 400×400 px PNG icon. The icon is automatically uploaded to Google Drive, and both a download link and thumbnail are generated. A styled completion card displays the result and gives you a “One More Time” option. Perfect for designers, developers, no-code creators, UI builders and even home-automation geeks (yes, you can integrate it with Home Assistant or Stream Deck!). It saves you the manual icon-hunt grind and gives consistent visual output across style variants. 🔧 Setup Requirements: n8n instance (self-hosted or cloud) OpenAI API access (image generation enabled) Google Drive credentials (write access to a folder) (Optional) Modify to integrate Slack, Teams or other file-storage destinations ✅ Highlights & Benefits: Fully automated prompt creation → consistent icon quality Transparent background PNGs size-ready for UI use Saves icons to Drive + gives immediate link/thumbnail Minimal setup, high value for creative/automation workflows Easily extendable (add extra sizes, style presets, share via chat/bot) ⚠️ Notes & Best-Practices: Check your OpenAI image quota and costs - image generation may incur usage. Confirm Google Drive folder permissions to avoid upload failures. If you wish a different resolution or format (e.g., SVG), clone the image node and adjust parameters.
By Arkadiusz