Nutrition tracker & meal logger with Telegram, Gemini AI and Google Sheets
π€π₯ Telegram Nutrition AI Assistant (Alternative to Cal AI App) > AI-powered nutrition assistant for Telegram β log meals, set goals, and get personalized daily reports with Google Sheets integration. π Description This n8n template creates a Telegram-based Nutrition AI Assistant π₯π₯ designed as an open-source alternative to the Cal AI mobile app. It allows users to interact with an AI agent via text, voice, or images to track meals, calculate macros, and monitor nutrition goals directly from Telegram. The system integrates Google Sheets as the database, handling both user profiles and meal logs, while leveraging Gemini AI for natural conversation, food recognition, and daily progress reports. β¨ Key Features π¬ Multi-input support: Text, voice messages (transcribed), and food images (AI analysis). π Macro calculation: Automatic estimation of calories, proteins, carbs, and fats. π User-friendly registration: Simple onboarding without storing personal health data (no weight/height required). π― Goal tracking: Users can set and update calorie and protein targets. π Daily reports: Personalized progress messages with visual progress bars. π Google Sheets integration: Profile table for user targets. Meals table for food logs. π Advanced n8n nodes: Includes use of Merge, Subworkflow, and Code nodes for data processing and report generation. π‘ Acknowledgment Inspired by the Cal AI concept π‘ β this template demonstrates how to reproduce its main functionality with n8n, Telegram, and AI agents as a flexible, open-source automation workflow. π· Tags telegram ai-assistant nutrition meal-tracking google-sheets food-logging voice-transcription image-analysis daily-reports n8n-template merge-node subworkflow-node code-node telegram-trigger google-gemini πΌ Use Case Use this template if you want to: π₯ Log meals using text, images, or voice messages. π Track nutrition goals (calories, proteins) with daily progress updates. π€ Provide a chat-based nutrition assistant without building a full app. π Store structured nutrition data in Google Sheets for easy access and analysis. π¬ Example User Interactions πΈ User sends a photo of a meal β AI analyzes the food and logs calories/macros. π€ User sends a voice message β AI transcribes and logs the meal. β¨οΈ User types βreportβ β AI returns a daily nutrition summary with progress bars. π₯ User says βupdate my protein goalβ β AI updates profile in Google Sheets. π Required Credentials Telegram Bot API (Bot Token) Google Sheets API credentials AI Provider API (Google Gemini or compatible LLM) βοΈ Setup Instructions π Create two Google Sheets tables: Profile: UserID, Name, Caloriestarget, Protein_target Meals: UserID, Date, Mealdescription, Calories, Proteins, Carbs, Fats π Configure the Telegram Trigger with your bot token. π€ Connect your AI provider credentials (Gemini recommended). π Connect Google Sheets with your credentials. βΆοΈ Deploy the workflow in n8n. π― Start interacting with your nutrition assistant via Telegram. π Extra Notes π© Green section: Handles Telegram trigger and user check. π₯ Red section: Registers new users and sets goals. π¦ Blue section: Processes text, voice, and images. π¨ Yellow section: Generates nutrition reports. πͺ Purple section: Main AI agent controlling tools and logic. --- π‘ Need Assistance? If youβd like help customizing or extending this workflow, feel free to reach out: π§ Email: johnsilva11031@gmail.com π LinkedIn: John Alejandro Silva RodrΓguez
By John Alejandro SIlvaStreamlining document automation with n8n and JSReport
Who is this template for? This workflow template is designed for accounting, human resources, and IT project management teams looking to automate the generation of PDF and Word documents. It can be particularly useful for: The accounting department: for generating invoices in PDF format, thus streamlining the invoicing process and payment tracking. The human resources department: for creating employment contracts in PDF, simplifying the administrative management of employees. IT project management teams: for producing Word documents, such as project specifications, to clearly define project requirements and objectives. Example result in mail This PDF and Word document generation workflow offers a practical and efficient solution for automating administrative and document-related tasks, allowing teams to focus on higher-value activities. How it works This workflow currently operates with an n8n form, but you can easily replace this form with a webhook triggered by an external application such as AirTable, SharePoint, DocuWare, etc. Once the configuration information is retrieved, we fill the API request body of JSReport. The body is defined at the time of template creation in JSReport (Example of JSReport usage). Then, in a straightforward manner, we fetch the PDF and send it via email. Here's a brief overview of this n8n workflow template: Link to n8n workflow template presentation To summarize This workflow integrates with an n8n form, but it's flexible to work with various triggering methods like webhooks from other applications such as AirTable, SharePoint, or DocuWare. After configuring the necessary information, it populates the API request body of JSReport, which defines the template in JSReport. Once the template is populated, it retrieves the PDF and sends it via email. In essence, it streamlines the process of generating PDF documents based on user input and distributing them via email. Instructions: Create a JSReport Account: Sign up for a JSReport account to create your PDF template model. Define PDF Template in JSReport: Use JSON data from your system to set up the content of your PDF template in JSReport. Configure HTTP Request in n8n: Use the HTTP Request node in n8n to send a request to JSReport. Set the node's body to the JSON data defining your PDF template. Watch the Video: For detailed setup guidance, watch the setup video. Remember, this template was created in n8n v1.38.2.
By NonoCodeScrape Google Maps data & discover email addresses with SerpAPI and EmailListVerify
This workflow allows to : scrape Google Maps data using SerpAPI discovery generic email addresses like contact@ using EmailListVerify API Whoβs it for This template is designed to prepare cold outreach for local businesses like restaurants or hotels (you need to target a type of business that is listed on Google Maps). This template will generate a list of leads with phone numbers and email addresses. The email addresses you will get are generic, like contact@. This isnβt a problem if you are targeting small businesses, as the owner will most likely monitor those emails. However, if your ideal customer profile has more than 20 employees, I do not recommend using those email addresses for cold outreach. Requirement This template uses: Google Sheet to handle input and output data SerpAPI to scrape Google Maps (250 searches/month in the free plan) EmailListVerify to discover email (from $0.05 per email) Notes This template is an extension of Lucas Perret template (adding email discovery module). If there is some interest in it, I can make a similar template using Apify as an alternative to SerpAPI for Google Map scraping.
By EmailListVerifyCheck for preview for a link
This workflow allows you to check for preview for a link and return the preview if it exists. Peekalink node: This node checks if a preview is available for a URL or not. If a preivew is available the node returns true, otherwise false. IF node: The IF node checks the output from the previous node. If the condition is true the node connected to the true branch is executed. If the condition is false the node connected to the false branch is executed. Peekalink1 node: This node will fetch the preview of the URL. Based on your use-case, you can connect the Slack node, Mattermost node etc. to get the response on these platforms. NoOp node: Adding this node here is optional, as the absence of this node won't make a difference to the functioning of the workflow. We've added this as it can sometimes help others with a better understanding of the workflow, visually.
By Harshil AgrawalAI-powered Upwork cover letter generator β Pinecone, Groq, Google Gemin, SerpAPI
[](https://www.youtube.com/watch?v=AqVSLj7qb2Q) π Automated Upwork Cover Letter Generator with n8n + MacOS Shortcut + Pinecone Context Retrieval This n8n automation is designed to streamline the Upwork proposal process by generating highly personalized, context-aware cover letters using your own skills and project data stored in a Pinecone vector store. With the help of an AI Agent powered by Groqβs Qwen LLM, and triggered instantly via a MacOS Shortcut, this system takes job descriptions from your clipboard and returns a ready-to-use HTML cover letterβright on your desktop. --- βοΈ Workflow Breakdown πΉ MacOS Shortcut β Trigger the Workflow Instantly The process begins with a MacOS Shortcut that captures job description text from your clipboard and sends it to a custom webhook in n8n. πΉ Webhook Node β Receive and Process Input The webhook node receives the clipboard data, along with the required credentials for authentication. This node serves as the entry point to the full automation. πΉ Field Mapping & Pre-Processing A series of basic logic nodes map and clean up the input fields. These are then passed to an LLM Chain to generate specific questions related to the job description. πΉ Question Answer Chain + Vector Search (Pinecone) Using your previously stored skills and project data in a Pinecone vector store, the system retrieves relevant information to answer the generated questions and builds a rich context around the job description. πΉ AI Agent Node β Generate Personalized Cover Letter With both the job post and contextual data, the AI Agent (powered by Groqβs Qwen LLM) creates a tailored cover letter. The agent is equipped with: π Google Search Tool π§ Vector Store Retriever Tool ποΈ Buffer Memory This ensures the generated proposal is insightful, relevant, and professional. πΉ Markdown to HTML β Clean Output Conversion The markdown output from the AI is converted into HTML using a Markdown node, making it easy to paste directly into Upwork or emails. πΉ Return to Shortcut β Display Final Result The final HTML response is sent back to the MacOS Shortcut, which displays it in a modal window for easy review and copy-paste. --- πΌ Use Case This automation is built specifically for freelancers on Upwork (or any freelance platform) who want to: β Save time on repetitive proposal writing β Create job-specific cover letters with context β Stand out with better personalization β Reduce manual effort with automation Whether youβre a beginner or a seasoned pro, this tool elevates your workflow while staying simple to use. --- π¦ Setup Instructions Import Workflow to your n8n instance Create and Configure MacOS Shortcut (drag-and-drop ready) Prepare and Embed Your Skills/Project Data into Pinecone Add API Credentials: Groq (for Qwen LLM) Pinecone n8n Webhook (Basic Auth if needed) Run the Workflow & Submit Smarter Proposals > Note: This workflow is designed for building and returning Upwork cover letters using job descriptions copied to your clipboard. All generation is context-aware and tailored per submission.
By Udit RawatCreate literary English/German to Chinese dictionary with GPT-4o-mini & Supabase
Description This workflow creates a sophisticated bilingual dictionary that provides literary-style definitions and examples for English and German words. The system automatically detects the input language, generates comprehensive definitions in Chinese, creates three literary-style example sentences with translations, and stores everything in a Supabase database for future reference. Who Is This For? Language Learners & Students: Perfect for those studying English or German who want to understand words in literary contexts with Chinese translations. Writers & Content Creators: Ideal for bilingual writers working with English, German, and Chinese who need rich, literary examples for their work. Educators & Translators: Excellent tool for language teachers and professional translators who need comprehensive word definitions with contextual examples. Literary Enthusiasts: Great for readers of literature who encounter unfamiliar words and want to understand their poetic or literary usage. What Problem Does This Workflow Solve? Traditional dictionaries often provide basic definitions without literary context or cross-language examples. This workflow addresses several key challenges: Limited Literary Context: Most dictionaries lack poetic, expressive, or literary-style examples that help understand how words are used in sophisticated writing. Cross-Language Learning: Provides seamless translation between English/German and Chinese with culturally appropriate examples. Data Persistence: Automatically saves all lookups to a database, creating a personalized vocabulary collection over time. API Accessibility: Provides a clean webhook interface that can be integrated into apps, websites, or other tools. How It Works Main Dictionary Lookup Flow Input Processing: Receives a word via webhook POST request and automatically detects if it's English or German AI Analysis: Uses OpenAI GPT-4o-mini to generate comprehensive definitions with literary context Response Formatting: Processes the AI response to extract structured data (word, meaning, examples) Quality Control: Validates the response and handles unclear or invalid inputs gracefully Database Storage: Saves the word, Chinese meaning, and examples to Supabase for future reference API Response: Returns formatted JSON with the complete dictionary entry Data Storage Flow Parallel Processing: Simultaneously returns the dictionary data to the user and saves it to the database Structured Storage: Organizes data in Supabase with fields for words, Chinese meanings, and example arrays Success Confirmation: Provides confirmation when data is successfully stored Setup Instructions Prerequisites & Accounts You'll need accounts and API access for: n8n (Cloud or self-hosted) OpenAI (API key required) Supabase (Database and API credentials) Webhook Configuration The workflow uses two webhook endpoints with the same path for different operations Note the webhook URL provided by n8n for API integration Test the webhook endpoints to ensure they're accessible approach Customization Options Extend to support additional input languages by modifying the AI prompt Add support for other target languages beyond Chinese Customize the literary style for different cultural contexts This workflow transforms simple word lookups into rich, contextual learning experiences while building a personalized vocabulary database over time.
By Xiaoyuan Zhang