Integrate Telegram with 500+ apps and services

Do you want to check the SSL certificate expiration dates of your customers or servers? This workflow gets information of an SSL certificate using the uProc Get Certificate by domain tool. You can use this workflow to query SSL certificates in bulk and send alarms when any certificate has expired. You need to add your credentials (Email and API Key - real -) located at Integration section to n8n. You can replace "Create Domain Item" with any integration containing a domain, like Google Sheets, MySQL, or Zabbix server. Every "uProc" node returns the next fields per every analyzed SSL certificate: issuer: Contains the issuer. provider: Contains the provider. valid_from: Contains the start date. valid_to: Contains the end date. serial_number: Contains the serial number. type: Contains if supports one or multiple domains. protocol: Contains the protocol. valid: Contains its validity. domains: Contains all domains and subdomains supported. An "IF" node detects if the certificate is valid or not. Finally, the workflow sends an alarm to a Telegram channel to know if the certificate has expired.

The Telegram API has a limitation to send only 30 messages per second. Use this workflow to send messages to more than 30 chats in Telegram.

This workflow posts a poem translated into English every day in a Telegram chat. Cron node: triggers the workflow every day at 10:00. You can change the time and interval based on your use case. HTTP Request node: makes an HTTP request to the Poemist API that returns a random poem. LingvaNex node: translates the returned poems into English. Telegram node: takes in the translated poem and posts it in the chat.

A workflow which allows you to receive daily affirmations via Telegram by querying a REST API triggered by a Cron node. I used the affirmations.dev API

A workflow to receive weather updates on demand using a Telegram bot. The workflow is triggered using the Telegram Trigger node by issuing a message to the Telegram bot. The OpenWeatherMap node queries the weather API and returns the result using the Telegram node.

Executes schedule routines, and triggers alerts via telegram

rss-telegramBot 1min refreash choose send message or one photo 0.1 beater code 2019/11/30 0.2 bug fix add instagram rss

Gets triggered by Telegram once a user sends a message Checks if the message contains a sticker If a sticker got found it sends a message with its ID else it informs the user that no sticker was found in message

This workflow allows you to create a screenshot of a website and send it to a telegram channel.

Automatically adding expense receipts to Google Sheets with Telegram, Mindee API, Twilio, and n8n.

Ok google download "movie name" I develop this automation to improve my quality of life in handling torrents in my media-center. Goal Automate the search operations of a movie based on its name and trigger a download using your transmission-daemon. Setup Prerequisite Transmission daemon up and running and its authentication method N8N configured self-hosted or with the possibility to add npm package better with docker-compose.yaml Telegram bot credential [optional] Configuration Create a folder where your docker-compose.yaml belongs n8n_dir and proceed in installing the node package. cd ~/n8n_dir npm i torrent-search-api Configuring your docker-compose.yaml file this way. You must include all the dependencies of torrent-search-api. This will let you run the new torrent search node presented in this workflow. version: '3.3' services: n8n: container_name: n8n ports: '5678:5678' restart: always volumes: '~/n8n_dir/.n8n:/home/node/.n8n' '~/n8n_dir/node_modules/@tootallnate:/usr/local/lib/node_modules/@tootallnate' '~/n8n_dir/node_modules/accepts:/usr/local/lib/node_modules/accepts' '~/n8n_dir/node_modules/agent-base:/usr/local/lib/node_modules/agent-base' '~/n8n_dir/node_modules/ajv:/usr/local/lib/node_modules/ajv' '~/n8n_dir/node_modules/ansi-styles:/usr/local/lib/node_modules/ansi-styles' '~/n8n_dir/node_modules/asn1:/usr/local/lib/node_modules/asn1' '~/n8n_dir/node_modules/assert:/usr/local/lib/node_modules/assert' '~/n8n_dir/node_modules/assert-plus:/usr/local/lib/node_modules/assert-plus' '~/n8n_dir/node_modules/ast-types:/usr/local/lib/node_modules/ast-types' '~/n8n_dir/node_modules/asynckit:/usr/local/lib/node_modules/asynckit' '~/n8n_dir/node_modules/aws-sign2:/usr/local/lib/node_modules/aws-sign2' '~/n8n_dir/node_modules/aws4:/usr/local/lib/node_modules/aws4' '~/n8n_dir/node_modules/base64-js:/usr/local/lib/node_modules/base64-js' '~/n8n_dir/node_modules/batch:/usr/local/lib/node_modules/batch' '~/n8n_dir/node_modules/bcrypt-pbkdf:/usr/local/lib/node_modules/bcrypt-pbkdf' '~/n8n_dir/node_modules/bluebird:/usr/local/lib/node_modules/bluebird' '~/n8n_dir/node_modules/boolbase:/usr/local/lib/node_modules/boolbase' '~/n8n_dir/node_modules/brotli:/usr/local/lib/node_modules/brotli' '~/n8n_dir/node_modules/bytes:/usr/local/lib/node_modules/bytes' '~/n8n_dir/node_modules/caseless:/usr/local/lib/node_modules/caseless' '~/n8n_dir/node_modules/chalk:/usr/local/lib/node_modules/chalk' '~/n8n_dir/node_modules/cheerio:/usr/local/lib/node_modules/cheerio' '~/n8n_dir/node_modules/cloudscraper:/usr/local/lib/node_modules/cloudscraper' '~/n8n_dir/node_modules/co:/usr/local/lib/node_modules/co' '~/n8n_dir/node_modules/color-convert:/usr/local/lib/node_modules/color-convert' '~/n8n_dir/node_modules/color-name:/usr/local/lib/node_modules/color-name' '~/n8n_dir/node_modules/combined-stream:/usr/local/lib/node_modules/combined-stream' '~/n8n_dir/node_modules/component-emitter:/usr/local/lib/node_modules/component-emitter' '~/n8n_dir/node_modules/content-disposition:/usr/local/lib/node_modules/content-disposition' '~/n8n_dir/node_modules/content-type:/usr/local/lib/node_modules/content-type' '~/n8n_dir/node_modules/cookiejar:/usr/local/lib/node_modules/cookiejar' '~/n8n_dir/node_modules/core-util-is:/usr/local/lib/node_modules/core-util-is' '~/n8n_dir/node_modules/css-select:/usr/local/lib/node_modules/css-select' '~/n8n_dir/node_modules/css-what:/usr/local/lib/node_modules/css-what' '~/n8n_dir/node_modules/dashdash:/usr/local/lib/node_modules/dashdash' '~/n8n_dir/node_modules/data-uri-to-buffer:/usr/local/lib/node_modules/data-uri-to-buffer' '~/n8n_dir/node_modules/debug:/usr/local/lib/node_modules/debug' '~/n8n_dir/node_modules/deep-is:/usr/local/lib/node_modules/deep-is' '~/n8n_dir/node_modules/degenerator:/usr/local/lib/node_modules/degenerator' '~/n8n_dir/node_modules/delayed-stream:/usr/local/lib/node_modules/delayed-stream' '~/n8n_dir/node_modules/delegates:/usr/local/lib/node_modules/delegates' '~/n8n_dir/node_modules/depd:/usr/local/lib/node_modules/depd' '~/n8n_dir/node_modules/destroy:/usr/local/lib/node_modules/destroy' '~/n8n_dir/node_modules/dom-serializer:/usr/local/lib/node_modules/dom-serializer' '~/n8n_dir/node_modules/domelementtype:/usr/local/lib/node_modules/domelementtype' '~/n8n_dir/node_modules/domhandler:/usr/local/lib/node_modules/domhandler' '~/n8n_dir/node_modules/domutils:/usr/local/lib/node_modules/domutils' '~/n8n_dir/node_modules/ecc-jsbn:/usr/local/lib/node_modules/ecc-jsbn' '~/n8n_dir/node_modules/ee-first:/usr/local/lib/node_modules/ee-first' '~/n8n_dir/node_modules/emitter-component:/usr/local/lib/node_modules/emitter-component' '~/n8n_dir/node_modules/enqueue:/usr/local/lib/node_modules/enqueue' '~/n8n_dir/node_modules/enstore:/usr/local/lib/node_modules/enstore' '~/n8n_dir/node_modules/entities:/usr/local/lib/node_modules/entities' '~/n8n_dir/node_modules/error-inject:/usr/local/lib/node_modules/error-inject' '~/n8n_dir/node_modules/escape-html:/usr/local/lib/node_modules/escape-html' '~/n8n_dir/node_modules/escape-string-regexp:/usr/local/lib/node_modules/escape-string-regexp' '~/n8n_dir/node_modules/escodegen:/usr/local/lib/node_modules/escodegen' '~/n8n_dir/node_modules/esprima:/usr/local/lib/node_modules/esprima' '~/n8n_dir/node_modules/estraverse:/usr/local/lib/node_modules/estraverse' '~/n8n_dir/node_modules/esutils:/usr/local/lib/node_modules/esutils' '~/n8n_dir/node_modules/extend:/usr/local/lib/node_modules/extend' '~/n8n_dir/node_modules/extsprintf:/usr/local/lib/node_modules/extsprintf' '~/n8n_dir/node_modules/fast-deep-equal:/usr/local/lib/node_modules/fast-deep-equal' '~/n8n_dir/node_modules/fast-json-stable-stringify:/usr/local/lib/node_modules/fast-json-stable-stringify' '~/n8n_dir/node_modules/fast-levenshtein:/usr/local/lib/node_modules/fast-levenshtein' '~/n8n_dir/node_modules/file-uri-to-path:/usr/local/lib/node_modules/file-uri-to-path' '~/n8n_dir/node_modules/forever-agent:/usr/local/lib/node_modules/forever-agent' '~/n8n_dir/node_modules/form-data:/usr/local/lib/node_modules/form-data' '~/n8n_dir/node_modules/format-parser:/usr/local/lib/node_modules/format-parser' '~/n8n_dir/node_modules/formidable:/usr/local/lib/node_modules/formidable' '~/n8n_dir/node_modules/fs-extra:/usr/local/lib/node_modules/fs-extra' '~/n8n_dir/node_modules/ftp:/usr/local/lib/node_modules/ftp' '~/n8n_dir/node_modules/get-uri:/usr/local/lib/node_modules/get-uri' '~/n8n_dir/node_modules/getpass:/usr/local/lib/node_modules/getpass' '~/n8n_dir/node_modules/graceful-fs:/usr/local/lib/node_modules/graceful-fs' '~/n8n_dir/node_modules/har-schema:/usr/local/lib/node_modules/har-schema' '~/n8n_dir/node_modules/har-validator:/usr/local/lib/node_modules/har-validator' '~/n8n_dir/node_modules/has-flag:/usr/local/lib/node_modules/has-flag' '~/n8n_dir/node_modules/htmlparser2:/usr/local/lib/node_modules/htmlparser2' '~/n8n_dir/node_modules/http-context:/usr/local/lib/node_modules/http-context' '~/n8n_dir/node_modules/http-errors:/usr/local/lib/node_modules/http-errors' '~/n8n_dir/node_modules/http-incoming:/usr/local/lib/node_modules/http-incoming' '~/n8n_dir/node_modules/http-outgoing:/usr/local/lib/node_modules/http-outgoing' '~/n8n_dir/node_modules/http-proxy-agent:/usr/local/lib/node_modules/http-proxy-agent' '~/n8n_dir/node_modules/http-signature:/usr/local/lib/node_modules/http-signature' '~/n8n_dir/node_modules/https-proxy-agent:/usr/local/lib/node_modules/https-proxy-agent' '~/n8n_dir/node_modules/iconv-lite:/usr/local/lib/node_modules/iconv-lite' '~/n8n_dir/node_modules/inherits:/usr/local/lib/node_modules/inherits' '~/n8n_dir/node_modules/ip:/usr/local/lib/node_modules/ip' '~/n8n_dir/node_modules/is-browser:/usr/local/lib/node_modules/is-browser' '~/n8n_dir/node_modules/is-typedarray:/usr/local/lib/node_modules/is-typedarray' '~/n8n_dir/node_modules/is-url:/usr/local/lib/node_modules/is-url' '~/n8n_dir/node_modules/isarray:/usr/local/lib/node_modules/isarray' '~/n8n_dir/node_modules/isobject:/usr/local/lib/node_modules/isobject' '~/n8n_dir/node_modules/isstream:/usr/local/lib/node_modules/isstream' '~/n8n_dir/node_modules/jsbn:/usr/local/lib/node_modules/jsbn' '~/n8n_dir/node_modules/json-schema:/usr/local/lib/node_modules/json-schema' '~/n8n_dir/node_modules/json-schema-traverse:/usr/local/lib/node_modules/json-schema-traverse' '~/n8n_dir/node_modules/json-stringify-safe:/usr/local/lib/node_modules/json-stringify-safe' '~/n8n_dir/node_modules/jsonfile:/usr/local/lib/node_modules/jsonfile' '~/n8n_dir/node_modules/jsprim:/usr/local/lib/node_modules/jsprim' '~/n8n_dir/node_modules/koa-is-json:/usr/local/lib/node_modules/koa-is-json' '~/n8n_dir/node_modules/levn:/usr/local/lib/node_modules/levn' '~/n8n_dir/node_modules/lodash:/usr/local/lib/node_modules/lodash' '~/n8n_dir/node_modules/lodash.assignin:/usr/local/lib/node_modules/lodash.assignin' '~/n8n_dir/node_modules/lodash.bind:/usr/local/lib/node_modules/lodash.bind' '~/n8n_dir/node_modules/lodash.defaults:/usr/local/lib/node_modules/lodash.defaults' '~/n8n_dir/node_modules/lodash.filter:/usr/local/lib/node_modules/lodash.filter' '~/n8n_dir/node_modules/lodash.flatten:/usr/local/lib/node_modules/lodash.flatten' '~/n8n_dir/node_modules/lodash.foreach:/usr/local/lib/node_modules/lodash.foreach' '~/n8n_dir/node_modules/lodash.map:/usr/local/lib/node_modules/lodash.map' '~/n8n_dir/node_modules/lodash.merge:/usr/local/lib/node_modules/lodash.merge' '~/n8n_dir/node_modules/lodash.pick:/usr/local/lib/node_modules/lodash.pick' '~/n8n_dir/node_modules/lodash.reduce:/usr/local/lib/node_modules/lodash.reduce' '~/n8n_dir/node_modules/lodash.reject:/usr/local/lib/node_modules/lodash.reject' '~/n8n_dir/node_modules/lodash.some:/usr/local/lib/node_modules/lodash.some' '~/n8n_dir/node_modules/lru-cache:/usr/local/lib/node_modules/lru-cache' '~/n8n_dir/node_modules/media-typer:/usr/local/lib/node_modules/media-typer' '~/n8n_dir/node_modules/methods:/usr/local/lib/node_modules/methods' '~/n8n_dir/node_modules/mime:/usr/local/lib/node_modules/mime' '~/n8n_dir/node_modules/mime-db:/usr/local/lib/node_modules/mime-db' '~/n8n_dir/node_modules/mime-types:/usr/local/lib/node_modules/mime-types' '~/n8n_dir/node_modules/monotonic-timestamp:/usr/local/lib/node_modules/monotonic-timestamp' '~/n8n_dir/node_modules/ms:/usr/local/lib/node_modules/ms' '~/n8n_dir/node_modules/negotiator:/usr/local/lib/node_modules/negotiator' '~/n8n_dir/node_modules/netmask:/usr/local/lib/node_modules/netmask' '~/n8n_dir/node_modules/nth-check:/usr/local/lib/node_modules/nth-check' '~/n8n_dir/node_modules/oauth-sign:/usr/local/lib/node_modules/oauth-sign' '~/n8n_dir/node_modules/object-assign:/usr/local/lib/node_modules/object-assign' '~/n8n_dir/node_modules/on-finished:/usr/local/lib/node_modules/on-finished' '~/n8n_dir/node_modules/optionator:/usr/local/lib/node_modules/optionator' '~/n8n_dir/node_modules/pac-proxy-agent:/usr/local/lib/node_modules/pac-proxy-agent' '~/n8n_dir/node_modules/pac-resolver:/usr/local/lib/node_modules/pac-resolver' '~/n8n_dir/node_modules/parseurl:/usr/local/lib/node_modules/parseurl' '~/n8n_dir/node_modules/performance-now:/usr/local/lib/node_modules/performance-now' '~/n8n_dir/node_modules/prelude-ls:/usr/local/lib/node_modules/prelude-ls' '~/n8n_dir/node_modules/process-nextick-args:/usr/local/lib/node_modules/process-nextick-args' '~/n8n_dir/node_modules/promise-polyfill:/usr/local/lib/node_modules/promise-polyfill' '~/n8n_dir/node_modules/proxy-agent:/usr/local/lib/node_modules/proxy-agent' '~/n8n_dir/node_modules/proxy-from-env:/usr/local/lib/node_modules/proxy-from-env' '~/n8n_dir/node_modules/psl:/usr/local/lib/node_modules/psl' '~/n8n_dir/node_modules/punycode:/usr/local/lib/node_modules/punycode' '~/n8n_dir/node_modules/qs:/usr/local/lib/node_modules/qs' '~/n8n_dir/node_modules/querystring:/usr/local/lib/node_modules/querystring' '~/n8n_dir/node_modules/raw-body:/usr/local/lib/node_modules/raw-body' '~/n8n_dir/node_modules/readable-stream:/usr/local/lib/node_modules/readable-stream' '~/n8n_dir/node_modules/request:/usr/local/lib/node_modules/request' '~/n8n_dir/node_modules/request-promise:/usr/local/lib/node_modules/request-promise' '~/n8n_dir/node_modules/request-promise-core:/usr/local/lib/node_modules/request-promise-core' '~/n8n_dir/node_modules/request-x-ray:/usr/local/lib/node_modules/request-x-ray' '~/n8n_dir/node_modules/safe-buffer:/usr/local/lib/node_modules/safe-buffer' '~/n8n_dir/node_modules/safer-buffer:/usr/local/lib/node_modules/safer-buffer' '~/n8n_dir/node_modules/selectn:/usr/local/lib/node_modules/selectn' '~/n8n_dir/node_modules/setprototypeof:/usr/local/lib/node_modules/setprototypeof' '~/n8n_dir/node_modules/sliced:/usr/local/lib/node_modules/sliced' '~/n8n_dir/node_modules/smart-buffer:/usr/local/lib/node_modules/smart-buffer' '~/n8n_dir/node_modules/socks:/usr/local/lib/node_modules/socks' '~/n8n_dir/node_modules/socks-proxy-agent:/usr/local/lib/node_modules/socks-proxy-agent' '~/n8n_dir/node_modules/source-map:/usr/local/lib/node_modules/source-map' '~/n8n_dir/node_modules/sshpk:/usr/local/lib/node_modules/sshpk' '~/n8n_dir/node_modules/statuses:/usr/local/lib/node_modules/statuses' '~/n8n_dir/node_modules/stealthy-require:/usr/local/lib/node_modules/stealthy-require' '~/n8n_dir/node_modules/stream-to-string:/usr/local/lib/node_modules/stream-to-string' '~/n8n_dir/node_modules/string-format:/usr/local/lib/node_modules/string-format' '~/n8n_dir/node_modules/string_decoder:/usr/local/lib/node_modules/string_decoder' '~/n8n_dir/node_modules/superagent:/usr/local/lib/node_modules/superagent' '~/n8n_dir/node_modules/superagent-proxy:/usr/local/lib/node_modules/superagent-proxy' '~/n8n_dir/node_modules/supports-color:/usr/local/lib/node_modules/supports-color' '~/n8n_dir/node_modules/toidentifier:/usr/local/lib/node_modules/toidentifier' '~/n8n_dir/node_modules/torrent-search-api:/usr/local/lib/node_modules/torrent-search-api' '~/n8n_dir/node_modules/tough-cookie:/usr/local/lib/node_modules/tough-cookie' '~/n8n_dir/node_modules/tslib:/usr/local/lib/node_modules/tslib' '~/n8n_dir/node_modules/tunnel-agent:/usr/local/lib/node_modules/tunnel-agent' '~/n8n_dir/node_modules/tweetnacl:/usr/local/lib/node_modules/tweetnacl' '~/n8n_dir/node_modules/type-check:/usr/local/lib/node_modules/type-check' '~/n8n_dir/node_modules/type-is:/usr/local/lib/node_modules/type-is' '~/n8n_dir/node_modules/universalify:/usr/local/lib/node_modules/universalify' '~/n8n_dir/node_modules/unpipe:/usr/local/lib/node_modules/unpipe' '~/n8n_dir/node_modules/uri-js:/usr/local/lib/node_modules/uri-js' '~/n8n_dir/node_modules/util:/usr/local/lib/node_modules/util' '~/n8n_dir/node_modules/util-deprecate:/usr/local/lib/node_modules/util-deprecate' '~/n8n_dir/node_modules/uuid:/usr/local/lib/node_modules/uuid' '~/n8n_dir/node_modules/vary:/usr/local/lib/node_modules/vary' '~/n8n_dir/node_modules/verror:/usr/local/lib/node_modules/verror' '~/n8n_dir/node_modules/word-wrap:/usr/local/lib/node_modules/word-wrap' '~/n8n_dir/node_modules/wrap-fn:/usr/local/lib/node_modules/wrap-fn' '~/n8n_dir/node_modules/x-ray:/usr/local/lib/node_modules/x-ray' '~/n8n_dir/node_modules/x-ray-crawler:/usr/local/lib/node_modules/x-ray-crawler' '~/n8n_dir/node_modules/x-ray-parse:/usr/local/lib/node_modules/x-ray-parse' '~/n8n_dir/node_modules/x-ray-scraper:/usr/local/lib/node_modules/x-ray-scraper' '~/n8n_dir/node_modules/xregexp:/usr/local/lib/node_modules/xregexp' '~/n8n_dir/node_modules/yallist:/usr/local/lib/node_modules/yallist' '~/n8n_dir/node_modules/yieldly:/usr/local/lib/node_modules/yieldly' image: 'n8nio/n8n:latest-rpi' environment: N8N_BASIC_AUTH_ACTIVE=true N8N_BASIC_AUTH_USER=username N8N_BASIC_AUTH_PASSWORD=your_secret_n8n_password EXECUTIONS_DATA_PRUNE=true EXECUTIONS_DATA_MAX_AGE=120 EXECUTIONS_TIMEOUT=300 EXECUTIONS_TIMEOUT_MAX=500 GENERIC_TIMEZONE=Europe/Berlin NODE_FUNCTION_ALLOW_EXTERNAL=torrent-search-api Once configured this way run n8n and create a new workflow coping the one proposed. Configure workflow Transmission In order to send command to transmission you must validate the Basic Auth. To do so: open the Start download node and edit the Credentials. Perform the same operation choosing the new credentials also in node Start download new token. In this automation we call transmission twice due to a security protocol in transmission system that prevents single click commands to be triggered, performing the request twice bypasses this security mechanism. https://en.wikipedia.org/wiki/Cross-site_request_forgery We use the X-Transmission-Session-Id provided by the first request to authenticate the second request. Telegram In order to make the workflow work as expected you must create a telegram bot and configure the nodes (Torrent not found and Telegram1) to send your message once the workflow is complete. Here's an easy guide to follow https://docs.n8n.io/nodes/n8n-nodes-base.telegram/ In those nodes you also should configure the Chat ID, you may use your telegram username or use a bot to retrieve your id. You may chat with useridinfobot that sends you your id. Ok google automation Since right now we do not have a n8n client for mobile that can trigger automation using google assistant I decided to use an IFTTT automation to trigger the webhook. I connect my IFTTT account with google assistant and pick the trigger. Say a phrase with a text ingredient as in the picture below. And configure the trigger this way. scarica $ -> download $ or metti in download $ -> put in download $ or some other trigger you may want. Then configure your server to trigger the webhook of n8n. Conclusion In conclusion we provide a fully working automation that integrates in n8n a node library and provides an easy trigger to perform a complex operation. Security concern Giving the ability to trigger a download may be problematic for potential unwanted torrent malware download, so you may decide to authenticate the webhook request passing in the body another field with a shared token between the two endpoints. Moreover the torrent-search-api library and its dependencies have some vulnerability that you may want to avoid on your own media-center, this will hopefully be patched soon in a further release of the library. This is just an interesting proof of concept. Quality of the download You may want to introduce another block between torrent search and webhook trigger to search for a movie based on the words detected by google assistant, sometimes it misinterprets something and you may end up downloading potential copyrighted material. Please use this automation only for free and open source movies and music.

Ghost + Sendy Integration Está es una integración del CMS Ghost hacia Sendy Sendy ( www.sendy.co ) Ghost ( www.ghost.org ) Con esta integración podrás importar los miembros del CMS Ghost en su nueva versión que incluye la parte de Membresía hacía el Software de newsletter sendy. Está integración además nos avisa si se ha registrado un nuevo miembro via telegram. Para realizar esta customización es necesaria la creación de una custom integration en Ghost. Para ello desde el panel de Administración vamos a CUSTOM INTEGRATIONS / + Add custom Integration Una vez allí nos solicitará un nombre le ponemos el que queramos y añadimos un nuevo Hook: En Target URL debe ir La url que nos genera nuestro webhook dentro de n8n: Pegamos la URL y acamos de rellenar los datos del HTTP REQUEST1 con los datos de nuestra lista rellenando los campos. api_key list Que encontaras en tú instalación de Sendy Por último faltara añadir las credenciales de Telegram de Nuestro BOT ( https://docs.n8n.io/credentials/telegram/ ) e indicar el grupo o usuario donde queremos que notifique. Saludos,

This workflow detects toxic language (such as profanity, insults, threats) in messages sent via Telegram. This blog tutorial explains how to configure the workflow nodes step-by-step. Telegram Trigger: triggers the workflow when a new message is sent in a Telegram chat. Google Perspective: analyzes the text of the message and returns a probability value between 0 and 1 of how likely it is that the content is toxic. IF: filters messages with a toxic probability value above 0.7. Telegram: sends a message in the chat with the text "I don't tolerate toxic language" if the probability value is above 0.7. NoOp: takes no action if the probability value is below 0.7.

This workflow allows you to send a message in a Telegram chat via bash-dash. Example usage: - telegram I'll be late If you want to send a predefined message without typing it in the command line, you can replace the Text Expression in the Telegram node with a specific message. In this case, the dash command - telegram will send the predefined message to the chat. Example bash-dash config: commands[telegram]="http://localhost:5678/webhook/telegram"

This telegram bot is designed to send one random recipe a day. This specific bot has filtered out only vegan recipes, so you can choose your diet type and send only recipes for a specific diet. What credentials you need: Set up a telegram bot. Airtable for listing who has joined your bot. This is needed to send one random recipe a day. Recipe (or other) API. This one uses Spoonacular. I hope you enjoy your bot!

Unleashing Creativity: Transforming Children's English Storytelling with Automation and AI Check this example: https://t.me/st0ries95 Summary In the realm of children's storytelling, automation is revolutionizing the way captivating tales are created and shared. This article highlights the transformative power of setting up a workflow for AI-powered children's English storytelling on Telegram. By delving into the use cases and steps involved, we uncover how this innovative approach is inspiring young minds and fostering a love for storytelling in children. Usecase The workflow for children's stories is a game-changer for content creators, educators, and parents seeking to engage children through imaginative and educational storytelling. Here's how this workflow is making a difference: Streamlined Content Creation: By providing a structured framework and automation for story generation, audio creation, and image production, the workflow simplifies the process of crafting captivating children's stories. Enhanced Educational Resources: Teachers can leverage this workflow to develop interactive educational materials that incorporate storytelling, making learning more engaging for students. Personalized Parental Engagement: Parents can share personalized stories with their children, nurturing a passion for reading and creativity while strengthening family bonds through shared storytelling experiences. Community Connection: Organizations and community groups can use the workflow to connect with their audience and promote literacy and creativity by creating and sharing children's stories. Inspiring Imagination: Through automated creation and sharing of enchanting stories, the workflow aims to spark imagination, inspire young minds, and instill a love for storytelling in children. Node Explanation OpenAI Chat Model: Utilizes the OpenAI Chat Model to generate text for the children's stories. Schedule Trigger: Triggers the workflow at set intervals (every 12 hours) to generate new stories. Recursive Character Text Splitter: Splits text into smaller chunks for processing. OpenAI Chat Model2: Another OpenAI Chat Model node for generating prompts for image creation. Send Story Text: Sends the generated story text to a specified Telegram chat. Send Audio for the Story: Sends audio files of the stories to the Telegram chat. Send Story Picture: Shares images related to the stories on Telegram. Create a Kids Stories: Generates captivating short tales for kids using prompts provided. Generate Audio for the Story: Converts generated text into audio files for storytelling. Create a Prompt for DALL-E: Creates prompts for generating images related to the stories. Generate a Picture for the Story: Generates pictures based on the prompts for visual storytelling. By embracing automation in children's storytelling, we unleash creativity, inspire young minds, and create magical experiences that resonate with both storytellers and listeners alike.

Introduction The Traveler Co-Pilot empowers you to confidently traverse the world, connecting with ease and breaking language barriers: Engage in conversations with locals Navigate menus at foreign eateries Comprehend road signs effortlessly. Features Seamless Speech-to-Speech Translation** Communicate in any of the 55 supported languages, and witness the bot translate your words into another language in real-time, all through speech. Visual Translation Magic** Capture images containing text, and the bot will work its magic by recognizing and translating the text into the desired language, right before your eyes. Setup Steps Open the Settings node and specify the languages you would like to work with

This workflow automatically sends you a list of your daily meetings every morning via a Telegram bot. Use Cases: This workflow is useful for anyone who wants to be automatically informed of their daily meetings, especially for busy professionals, students, and anyone with a hectic schedule. Setup: Google Calendar connected to n8n A Telegram bot created and connected to n8n Your Telegram user ID specified Notes: You need to replace the placeholder in the Telegram node with your actual Telegram user ID. You can customize the formatting of the Telegram message in the JavaScript Code node.

Workflow Overview This workflow automates the process of forwarding e-book files to a Kindle device using a Telegram bot and Outlook email. Setup Steps: Telegram Bot Setup: Create a Telegram bot via BotFather and configure its credentials in the workflow. Outlook Email Configuration: Set up your Outlook email credentials. (Currently, only Outlook is supported, but you can modify the workflow to support other email providers.) Amazon Kindle Email Setup: Find your Kindle device's email address from your Amazon account. This will be the recipient address for the e-books. Allow Email Sending to Kindle: Ensure your Amazon account is configured to allow emails from your Outlook address to send files to your Kindle. Workflow Explanation: The workflow begins with a Telegram bot trigger node that listens for new chat messages. When a new message is received, the workflow checks if the message contains a file attachment. If no file is detected, the bot will send a warning reply to the user in the chat. If a file is found, it will be renamed to ensure it appears correctly on the Kindle device when sent. The workflow then composes an email with the file attached and sends it to the Kindle's receiving address. If the email is sent successfully, the bot will notify the user with a success message in the chat. Only Amazon-supported file types will be accepted by Kindle. If sending fails, you will receive a notification email from Amazon in your Outlook inbox. In case of delivery issues, retry sending the file as network issues may occasionally interfere with the process.

What this template does This template serves as a Chatbot that enables you to ask questions about the content of a PDF directly in Telegream. It checks incoming Telegram messages if they contain a document. If they do, it stores the PDF in a Pinecone Vector store. If there's no document, it will search the Vector Store for information and try to answer your question. Setup Open the Telegram app and search for the BotFather user (@BotFather) Start a chat with the BotFather Type /newbot to create a new bot Follow the prompts to name your bot and get a unique API token Save your access token and username Once you set your bot, you can send the pdf, and then ask questions about the content. How to adjust it to your needs You can exchange the Groq chat model with any model that you like Exchange Pinecone with any other vector store tool you like (e.g. Supabase, Postgres or QDrant) #Telegram, #Pinecone, #Openai, #GroQ

Free template for voice & text messages with short-term memory This n8n workflow template is a blueprint for an AI Telegram bot that processes both voice and text messages. Ready to use with minimal setup. The bot remembers the last several messages (10 by default), understands commands and provides responses in HTML. You can easily swap GPT-4 and Whisper for other language and speech-to-text models to suit your needs. Core Features Text: send or forward messages Voice: transcription via Whisper Extend this template by adding LangChain tools. Requirements Telegram Bot API OpenAI API (for GPT-4 and Whisper) 💡 New to Telegram bots? Check our step-by-step guide on creating your first bot and setting up OpenAI access. Use Cases Personal AI assistant Customer support automation Knowledge base interface Integration hub for services that you use: Connect to any API via HTTP Request Tool Trigger other n8n workflows with Workflow Tool

An example workflow for a multilanguage Telegram bot. It allows adding many new languages to the bot without editing the workflow. Important note! Due to some breaking API changes in NocoDB some of its node options are not working at the moment (MAY 2022). These two nodes were replaced by HTTP request nodes. Functionality is still the same.

How it works: This project creates a personal AI assistant named Angie that operates through Telegram. Angie can summarize daily emails, look up calendar entries, remind users of upcoming tasks, and retrieve contact information. The assistant can interact with users via both voice and text inputs. Step-by-step: Telegram Trigger: The workflow starts with a Telegram trigger that listens for incoming message events. The system determines if the incoming message is voice or text. If voice, the voice file is retrieved and transcribed to text using OpenAI's API Speech to Text AI Assistant: The telegram request is passed to the AI assistant (Angie). Tools Integration: The AI assistant is equipped with several tools: Get Email: Uses Gmail API to fetch recent emails, filtering by date. Get Calendar: Retrieves calendar entries for specified dates. Get Tasks: Connects to a Baserow (open-source Airtable alternative) database to fetch to-do list items. Get Contacts: Also uses Baserow to retrieve contact information. Response Generation: The AI formulates a response based on the gathered information and sends back to the user on Telegram

An innovative N8N workflow that monitors cryptocurrency prices on Binance, identifies significant market movements, and sends customized alerts through Telegram. Ideal for traders and enthusiasts seeking real-time market insights. How It Works Trigger Options: Choose between a manual trigger or a scheduled trigger to start the workflow. Fetch Market Data: The 'Binance 24h Price Change' node retrieves the latest 24-hour price changes for cryptocurrencies from Binance. Identify Significant Changes: The 'Filter by 10% Change rate' node filters out cryptocurrencies with price changes of 10% or more. Aggregate Data: The 'Aggregate' node combines all significant changes into a single dataset. Format Data for Telegram: The 'Split By 1K chars' node formats this data into chunks suitable for Telegram's message size limit. Send Telegram Message: The 'Send Telegram Message' node broadcasts the formatted message to a specified Telegram chat. Set Up Steps Estimated Time**: About 1-5 minutes for setup. Initial Configuration**: Set up a Binance API connection (Optional) and your Telegram bot credentials. Customization**: Adjust the trigger according to your preference (manual or scheduled) and update the Telegram chat ID. Create Telegram bot steps**:- Setting up a Telegram bot and obtaining its token involves several steps. Here's a detailed guide: Start a Chat with BotFather: Open Telegram and search for "BotFather". This is the official bot that allows you to create new bots. Start a chat with BotFather by clicking on the "Start" button at the bottom of the screen. Create a New Bot: In the chat with BotFather, type /newbot and send the message. BotFather will ask you to choose a name for your bot. This is a display name and can be anything you like. Next, you'll need to choose a username for your bot. This must be unique and end in bot. For example, my_crypto_alert_bot. Receive Your Token: After you've set the name and username, BotFather will provide you with a token. This token is like a password for your bot, so keep it secure. The message will look something like this: Done! Congratulations on your new bot. You will find it at t.me/my_crypto_alert_bot. You can now add a description, about section and profile picture for your bot, see /help for a list of commands. Use this token to access the HTTP API: 123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11 The token in this case is 123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11. Test Your Bot: You can find your bot by searching for its username in Telegram. Start a chat with your bot and try sending it a message. Although it won't respond yet, this step is essential to ensure it's set up correctly. Use the Token in n8n: In your n8n workflow, when setting up the Telegram node, you'll be prompted to enter credentials. Choose to add new credentials and paste the token you received from BotFather. Get Your Chat ID: To send messages to a specific chat, you need to know the chat ID. The easiest way to find this is to first message your bot, then use a bot like @userinfobot to get your chat ID. Once you have the chat ID, you can configure it in the Telegram node in your n8n workflow. Finalize Your Workflow: With the bot token and chat ID set up in n8n, your Telegram notifications should work as intended in your workflow. Remember, keep your bot token secure and never share it publicly. If your token is compromised, you can always generate a new one by chatting with BotFather and selecting /token. Example result Keywords: n8n workflow, cryptocurrency market, Binance API, Telegram bot, price alert system, automated trading signals, market analysis `

How it works Weekly triggered Fetches all previous executions of a given workflow Filter for failures and aggregate them into a single report Sends them to a given Telegram chat. Set up steps Create a new N8N api token in the settings panel. Add new N8N credentials in the credentials panel. Add new Telegram credentials in the credentials panel. Select N8N credentials and select the workflow ID in the "Get all previous executions" node. Select Telegram credentials and enter the chat-id in the "Telegram" node.

What this template does This template uses GROQ LLAVA V1.5 7B API that offers fast inference for multimodal models with vision capabilities for understanding and interpreting visual data from images. . The users send a image and get a description of the image from the model. Setup Open the Telegram app and search for the BotFather user (@BotFather) Start a chat with the BotFather Type /newbot to create a new bot Follow the prompts to name your bot and get a unique API token Save your access token and username Once you set your bot, you can send the image, and get the descriptions.

This is a workflow for a Telegram-echo bot. This bot is useful for debugging and learning purposes of the Telegram platform. Add your Telegram bot credentials for both nodes. Activate the workflow. Send data to the bot (i.e. a message, a forwarded message, sticker, emoji, voice, file, an image...). Second node will fetch the incoming JSON object, format it and send back.

What this workflow does This workflow allows you to monitor multiple Github repos simultaneously without polling due to use of Webhooks. It programmatically allows for adding and deleting of repos to your watchlist to make management convenient. Description Can monitor multiple repos simultaneously. Programmatically register or unregister repos from a list. No need for manual work. Webhook notification means no constant polling necessary. Setup 1. Creating Credentials on Github Generate a personal access token on github by following these esteps; Right hand side of page -> Settings -> scroll to bottom -> Developer Settings > Personal Access Token > Tokens (classic) > Generate New Token Give scopes: admin:repo_hook repo (if you want to use it for your own private repo) if you need more help, see here: https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens 2. Setting Credentials in n8n In Register Github Webhook Authenticaion > Generic Credential Type Generic Auth Type > Header Auth Header Auth > Create New Credential with Name set to 'Authorization' and Value set to 'Bearer '. (You can reuse this for Delete Github Webhook and Get Existing Webhooks). Now in Register Github Webhook, scroll down to Send Body > JSON and inside the JSON, change the value of "url" to the webhook address given as Production URL in the node Webhook Trigger. 3. Notification settings In the third row, link up the Webhook Trigger to any API of your choice. Slack and Telegram are given as examples. You can also format the notification message as you wish. Setup time: roughly 10 minutes. Instructions Video: https://vimeo.com/1013473758 Test 1. Register Webhooks In Repos to Monitor, add any repo you want to monitor changes for. Disable Webhook Trigger, Click Test Workflow and if your Github credentials were set correctly, it will automatically register the webhooks. - You can test this by running the single node Get Existing Webhook and confirming it outputs the repo addresses. 2. Handle Github Events Now that you have registered the webhooks, re-enable Webhook Trigger and activate the workflow. Make a commit to any of the registered repos. Confirm that the notification went through. That's it!

What is it This workflow aims to build a simple bot that will send a message to a telegram channel every time there is a new saved item to the Reader. This workflow can be easily modify to support other way of sending the notification, thanks to existing n8n nodes. Warning: This is only for folks who already have access to the Reader, it won't work if you don't Also, this workflow use a file to store the last update time in order to not sync everything everytime. Setup The config node : It contains the telegram channel id It also contains the file used as storage To get the header auth, you have to : Go to the reader Open the devtools, Option + ⌘ + J (on macOS), or Shift + CTRL + J (on Windows/Linux) Go to network and find a profile_details/ request, click on it Go to Request Headers Copy the value for "Cookie" In n8n, set the name of the Header auth account to Cookie and the value with the one you copied before

Template for Kids' Story in Arabic The n8n template for creating kids' stories in Arabic offers a versatile platform for storytellers to captivate young audiences with educational and interactive tales. It allows for customization to suit various use cases and can be set up effortlessly. Check this example: https://t.me/st0ries95 Use Cases Educational Platforms: Educational platforms can automate the creation and distribution of educational stories in Arabic for children using this template. By incorporating visual and auditory elements into the storytelling process, educational platforms can enhance learning experiences and engage young learners effectively. Children's Libraries: Children's libraries can utilize this template to curate and share a diverse collection of Arabic stories with young readers. The automated generation of visual content and audio files enhances the storytelling experience, encouraging children to immerse themselves in new worlds and characters through captivating narratives. Language Learning Apps: Language learning apps focused on Arabic can integrate this template to offer culturally rich storytelling experiences for children learning the language. By translating stories into Arabic and supplementing them with visual and auditory components, these apps can facilitate language acquisition in an enjoyable and interactive manner. Configuration Guide for Nodes OpenAI Chat Model Nodes: Functionality**: Allows interaction with the OpenAI GPT-4 Turbo model. Purpose**: Enables communication with advanced chat capabilities. Create a Prompt for DALL-E Node: Customization**: Tailor prompts for generating relevant visual content. Summarization**: Define prompts for visual content generation without text. Generate an Image for the Story Node: Resource Type**: Specifies image as the resource. Prompt Setup**: Configures prompt for textless image creation within the visual content. Generate Audio for the Story Node: Resource Type**: Chooses audio as the resource. Input Definition**: Sets input text for audio file generation. Translate the Story to Arabic Node: Chunking Mode Selection**: Allows advanced chunking mode choice. Summarization Configuration**: Sets method and prompts for story translation into Arabic. Send the Story To Channel Node: Channel ID**: Specifies the channel ID for sending the story text. Text Configuration**: Sets up the text to be sent to the channel. By following these node descriptions, users can effectively configure the n8n template for kids' stories in Arabic, tailoring it to specific use cases for a seamless and engaging storytelling experience for young audiences.

Telegram User Registration module Offers an efficient way to manage new and returning users in your Telegram bot workflow. It checks user data against a Google Sheets database, saving essential user information and ensuring personalized interactions. Key Features: User Lookup: Searches for users in a Google Sheets database based on their unique Telegram ID. New User Handling: Automatically registers new users, capturing details such as first name, last name, username, and language code. Returning User Recognition: Detects when an existing user returns and updates their status. Data Storage: Safely stores user information in a structured format, with fields for status and date of registration. Personalized Greetings: Delivers customized welcome messages for both new and returning users, promoting engagement. Setup Instructions: Copy this Telegram User Registration Workflow Follow the instructions inside: - Use Google Sheet template - Set up your credentials - Use example data to test workflow Customization: Adjust the status and messages for users based on your bot's needs. Connecting to the bot Workflow: Copy my Telegram bot starter template Copy Workflow ID of your Telegram User Registration Workflow Find the Register module in Telegram bot starter template and paste your Workflow ID Now the user's data is entered into the Register Workflow. This module provides a scalable foundation for managing user registration, whether your bot is for meal planning, customer support, or other interactive services. My easy to set up Telegram bot modules: 🏁 Telegram bot starter template 📝 Telegram callback menu (soon) Please reach out to Victor if you need further assistance with you n8n workflows and automations!

Use case Error workflows are an important part of running workflows in production. Make sure to set them up for all your important workflows. The message links directly to the execution. How to setup Add Telegram creds Set chat id in Telegram node Add this error workflow to other workflows https://docs.n8n.io/flow-logic/error-handling/#create-and-set-an-error-workflow

Use case This workflow enables a Telegram bot that can: Accept speech input in one of 55 supported languages Automatically detect the language spoken and translate the speech to another language Responds back with the translated speech output. This allows users to communicate across language barriers by simply speaking to the bot, which will handle the translation seamlessly. How does it work? Translation In the translation step the workflow converts the user's speech input to text and detects the language of the input text. If it's English, it will translate to French. If it's French, it will translate to English. To change the default translation languages, you can update the prompt in the AI node. Output In the output step, we provide the translated text output back to the user and speech output is generated in the translated language. Setup steps Obtain Telegram API Token Start a chat with the BotFather. Enter /newbot and reply with your new bot's display name and username. Copy the bot token and use it in the Telegram node credentials in n8n. Update the Settings node to customize the desired languages Activate the flow Full list of supported languages All supported languages:

Use case LLMs have provided a lot of value for several use cases. Especially some OpenAI models are proving to be quite valuable. However, it's sometimes not super accessible to chat with these models. This workflow enables you to chate directly with OpenAI's GPT-3.5 via Telegram. How it works A simple telegram bot that connects to your botfather bot to give AI responses, using OpenAI's GPT 3.5 model, to a user's messages with emojis. What to do Add your telegram API key and your OpenAI api key and have fun!

Search music and play to Spotify from Telegram This workflow is a simple demonstration on accessing a message model from Telegram and it makes searching for songs an easy task even if you can't remember the artist or song name. An OpenAI message model tries to figure out the song and sends it to an active Spotify device**. Use case Imagine an office where you play music in the background and the employees can control the music without having to login to the playing account. How it works You describe the song in Telegram. Telegram bot sends the text to n8n. An OpenAI message model tries to find the song. Spotify gets the search query string. First match is then added to queue. -- If there is no match a message is sent to Telegram and the process ends. We change to the next track in the list. We make sure the song starts playing by trying to resume. We fetch the currently playing track. We return "now playing" information to Telegram: Song Name - Artist Name - Album Name. Error handling Every Spotify step has it's on error handler under settings where we output the error. Message parser receives the error and sends it to Telegram. Requirements Active workflow* OpenAI API key Telegram bot Spotify account and Oauth2 API Spotify active on a device** .* The Telegram trigger is activated only if this workflow is active. You can however TEST the workflow in the editor by clicking "Test step" and then it waits for the Telegram event. When event is received, just step through all steps or just clicking "Test step" on the "Fetch Now Playing" node. .** You must have a Spotify device active when trying to communicate with a device. Open Spotify and play something - not it is active.

This workflow gets latest RSS from different RSS Sources and categorizes them with conditional. *Reference https://n8n.io/workflows/1507 https://n8n.io/workflows/617 https://n8n.io/workflows/199*

This workflow connects Telegram bots with LangChain nodes in n8n. The main AI Agent Node is configured as a Conversation Agent. It has a custom System Prompt which explains the reply formatting and provides some additional instructions. The AI Agent has several connections: OpenAI GPT-4 model is called to generate the replies Window Buffer Memory stores the history of conversation with each user separately There is an additional Custom n8n Workflow tool (Dall-E 3 Tool). AI Agent uses this tool when the user requests an image generation. In the lower part of the workflow, there is a series of nodes that call Dall-E 3 model with the user Telegram ID and a prompt for a new image. Once image is ready, it is sent back to the user. Finally, there is an extra Telegram node that masks HTML syntax for improved stability in case the AI Agent replies using the unsupported format.

Telegram Bot Starter template workflow provides a foundational setup for creating powerful Telegram bots with n8n. It handles incoming messages, photos, files, and voice notes, making it an excellent starting point for developers looking to create bots for customer engagement, support, or interactive services. Key Features: Dynamic Message Handling: Respond to text messages, photos, files, and more. Modular Design: Easily integrate additional workflows such as user registration, payment modules, or custom commands. Error Handling: Ensure the bot gracefully manages errors and user inputs. Who Can Use This Workflow? Developers looking for a quick way to build and customize Telegram bots. Businesses and service providers who need customer interaction automation. Setup Instructions: Replace Telegram credentials with your own API credentials. Customize responses for different message types (text, photo, file). If integrating with external services (like Google Sheets), update the necessary credentials and links. Extensibility: This workflow is the base for building any Telegram bot. Additional modules, such as a user registration module, payment integration, and user profile management, are available for easy connection to expand the bot’s functionality. ✍🏻Use the Telegram user registration workflow → 💵Use the Telegram Payment, Invoicing and Refund Workflow for Stars → UPDATES: 🔥 Get the most up-to-date and expanded version → Aug 24: Changed processing of system events: “new user” and ‘user who blocked bot’ events Sep 24: Improved message handler: Updated logic to handle various types of messages using Switch (text, photo, file, voice, and callback). Payment processing: Added new nodes for sending invoices and handling payments via Telegram Please reach out to Victor if you need further assistance with your n8n workflows and automations!

A simple node to send new YouTube videos from a channel to a Telegram chat (private, group or channel). CheckTime: set how often videos should be fetched from YouTube. Default is 30 minutes. GetVideosYT: this node will fetch the list of videos from a given channel. Here you need to specify on "Limit" the number of videos to fetch, and on "Channel ID" the ID of the desired channel (it should be the ending part of the URL). You need Google OAuth2 credentials to make it work. A guide is available here. (If you use n8n's tunneling, you may need to adjust the OAuth callback URL on Google Cloud Platform) Set: this node will set some variables to work easily with the next nodes. You shouldn't edit this. Function: this node checks if the video was seen previously by the workflow, so that it won't be published a second time on Telegram. You shouldn't edit this. SendVideo: this node sends the message to Telegram. You need to set your bot's credentials (guide here), specify the Chat ID to send the message (how to get) and personalize the Text of your message. This workflow works correctly only when it's activated. If you manually execute the workflow, it will send every time the latest videos.

Video Guide I prepared a detailed guide that showed the whole process of building an AI bot, from the simplest version to the most complex in a template. .png) Who is this for? This workflow is ideal for developers, chatbot enthusiasts, and businesses looking to build a dynamic Telegram bot with memory capabilities. The bot leverages OpenAI's assistant to interact with users and stores user data in Supabase for personalized conversations. What problem does this workflow solve? Many simple chatbots lack context awareness and user memory. This workflow solves that by integrating Supabase to keep track of user sessions (via What this workflow does This Telegram bot template connects with OpenAI to answer user queries while storing and retrieving user information from a Supabase database. The memory component ensures that the bot can reference past interactions, making it suitable for use cases such as customer support, virtual assistants, or any application where context retention is crucial. 1.Receive New Message: The bot listens for incoming messages from users in Telegram. Check User in Database: The workflow checks if the user is already in the Supabase database using the Create New User (if necessary): If the user does not exist, a new record is created in Supabase with the telegram_id and a unique Start or Continue Conversation with OpenAI: Based on the user’s context, the bot either creates a new thread or continues an existing one using the stored Merge Data: User-specific data and conversation context are merged. Send and Receive Messages: The message is sent to OpenAI, and the response is received and processed. Reply to User: The bot sends OpenAI’s response back to the user in Telegram. Setup Create a Telegram Bot using the Botfather and obtain the bot token. Set up Supabase: Create a new project and generate a Create a new table named create table public.telegram_users ( id uuid not null default gen_random_uuid (), date_created timestamp with time zone not null default (now() at time zone 'utc'::text), telegram_id bigint null, openai_thread_id text null, constraint telegram_users_pkey primary key (id) ) tablespace pg_default; OpenAI Setup: Create an OpenAI assistant and obtain the Customize your assistant’s personality or use cases according to your requirements. Environment Configuration in n8n: Configure the Telegram, Supabase, and OpenAI nodes with the appropriate credentials. Set up triggers for receiving messages and handling conversation logic. Set up OpenAI assistant ID in "++OPENAI - Run assistant++" node.

This workflow extends n8n and uses R language graphic capabilities. This is a Telegram bot which fetches weather data via the openweathermap.org API, plots an image using ggoplot2 package from R and sends the image to the Telegram user.

Overview This n8n workflow is designed to extract specific interests from messages in a Telegram chat and retrieve related information using the Facebook Graph API. It aims to provide a streamlined solution for parsing and analyzing user-provided interests within the Telegram platform. Features Interest Extraction:** Automatically identifies and extracts interests from messages that start with the hashtag "#interest". Data Retrieval:** Utilizes the Facebook Graph API to retrieve information related to the extracted interests. Structured Outputs:** Presents the retrieved data in an organized format for further analysis and review. Requirements Operational instance of n8n (self-hosted or cloud version). Basic understanding of n8n workflows and nodes. Setup and Configuration Import Workflow: Load the provided JSON workflow into your n8n instance. Configure Telegram Trigger Node: Ensure the Telegram trigger node is set up with the appropriate credentials and webhook ID. Configure and Test Nodes: Adjust node parameters as necessary and test the workflow to ensure proper functionality. How it Works Telegram Trigger: Listens for incoming messages in a specified Telegram chat. Check Message Contents: Verifies if the message begins with the specified hashtag and is from the designated chat ID. Extract Message: Extracts the content of the message for further processing. Split Message: Splits the extracted message to identify the interest and remaining content. Connect to Graph API: Utilizes the Facebook Graph API to search for information related to the extracted interest. Split Interests into a Table: Organizes the retrieved data into a structured table format. Get Variables: Maps the retrieved data to create a new JSON object containing specific fields related to the interest. Create a Spreadsheet: Generates a spreadsheet file in CSV format based on the retrieved and formatted data. Send the Spreadsheet File: Sends the generated spreadsheet file back to the original Telegram chat. Customization Modify the filtering conditions and fields to suit specific requirements. Adjust the frequency of the trigger node based on preference. Best Practices Regularly test the workflow to ensure consistent performance. Stay informed about any changes to external APIs that might affect the workflow's functionality. Contributing Your feedback and contributions are highly valued. Feel free to adapt, modify, and share enhancements with the n8n community.

The workflow starts by listening for messages from Telegram users. The message is then processed, and based on its content, different actions are taken. If it's a regular chat message, the workflow generates a response using the OpenAI API and sends it back to the user. If it's a command to create an image, the workflow generates an image using the OpenAI API and sends the image to the user. If the command is unsupported, an error message is sent. Throughout the workflow, there are additional nodes for displaying notes and simulating typing actions.

This workflow uses a WooCommerce trigger that will run a new product has been added, It will then post the product to Telegram and Twitter. To use this workflow you will need to set the credentials to use for the WooCommerce, Twitter and Telegram nodes.

A robust n8n workflow designed to enhance Telegram bot functionality for user management and broadcasting. It facilitates automatic support ticket creation, efficient user data storage in Redis, and a sophisticated system for message forwarding and broadcasting. How It Works Telegram Bot Setup: Initiate the workflow with a Telegram bot configured for handling different chat types (private, supergroup, channel). User Data Management: Formats and updates user data, storing it in a Redis database for efficient retrieval and management. Support Ticket Creation: Automatically generates chat tickets for user messages and saves the corresponding topic IDs in Redis. Message Forwarding: Forwards new messages to the appropriate chat thread, or creates a new thread if none exists. Support Forum Management: Handles messages within a support forum, differentiating between various chat types and user statuses. Broadcasting System: Implements a broadcasting mechanism that sends channel posts to all previous bot users, with a system to filter out blocked users. Blocked User Management: Identifies and manages blocked users, preventing them from receiving broadcasted messages. Versatile Channel Handling: Ensures that messages from verified channels are properly managed and broadcasted to relevant users. Set Up Steps Estimated Time**: Around 30 minutes. Requirements**: A Telegram bot, a Redis database, and Telegram group/channel IDs are necessary. Configuration**: Input the Telegram bot token and relevant group/channel IDs. Configure message handling and user data processing according to your needs. Detailed Instructions**: Sticky notes within the workflow provide extensive setup information and guidance. Live Demo Workflow Bot: Telegram Bot Link (Click here) Support Group: Telegram Group Link (Click here) Broadcasting Channel: Telegram Channel Link (Click here) Keywords: n8n workflow, Telegram bot, chat ticket system, Redis database, message broadcasting, user data management, support forum automation

Use case If you have a form where potential leads reach out, then you probably want to analyze those leads and send a notification if certain requirements are met, e.g. employee number is high enough. MadKudu is built exactly to solve this problem. We use it along with Hunter and Telegram to get a message for high quality leads. How to setup Add you MadKudu, Hunter, and Telegram credentials Set the Telegram chat id to send to Click the Test Workflow button, enter your email and check your email Activate the workflow and use the form trigger production URL to collect your leads in a smart way How to adjust this template You may want to raise or lower the threshold for your leads, as you see fit.

This workflow provides a complete solution for handling Telegram Stars payments, invoicing and refunds using n8n. It automates the process of sending invoices, managing pre-checkout approvals, recording transactions, and processing refunds for stars, making it ideal for businesses using Telegram Stars for digital payments. What are Telegram Stars? Learn more here. Key Features Payment Handling**: Automate invoice creation and sending via Telegram, with pre-checkout approval for smooth payment processing. Refund Management: Simplify the refund process using user IDs and payment charge IDs from successful **Telegram Stars transactions. Transaction Recording**: Record all payment details, such as user information and payment charge IDs, in Google Sheets for transparent financial tracking. Who Can Use This Workflow? Developers and Businesses: Looking to implement **Telegram Stars as a payment system within Telegram. Service Providers**: Managing subscriptions, donations, or digital sales through Telegram automation. Use Cases Subscription Sales Automation**: Use the workflow to issue invoices and automatically process payments for recurring subscriptions. Infopreneurs and Marketers: Use the workflow for delivering lead magnets, tripwires, and further automating sales via **Telegram Stars. Course Sales Automation**: Automate invoicing and refunds for educational platforms selling online courses. Developers and Businesses: Looking to implement **Telegram Stars as a payment system within Telegram. Service Providers**: Managing subscriptions, donations, or digital sales through Telegram automation. Online Educational Platforms**: Automate billing for courses and handle refunds easily. Setup Instructions Replace the Telegram API credentials with your bot API token from BotFather. Customize invoice details, including product name, description, and payment amount. Connect your Google Sheets for storing transaction logs. Configure refund steps for easy processing of star refunds when needed. Note: The setup is very simple—just follow the instructions provided on the yellow sticky notes within the workflow and insert your data. All other nodes are pre-configured and require no additional customization. The entire setup process takes just 1 minute. I provided a short Loom record with an explanation. Extensibility This workflow can be further customized to include user profile management, payment analytics, or integration with external services like CRMs or accounting tools. Additional modules can be easily connected to manage advanced features like Telegram User Registration. Available Templates Telegram Bot Starter Template: A foundational setup for creating custom Telegram bots. Telegram User Registration Workflow: Automate user registration and data collection via Telegram. Telegram Payment and Refund Workflow for Stars**: Streamline your Telegram payment processing with stars, invoices, and refunds. Support and Updates This workflow is supported and regularly updated to stay compatible with the latest Telegram features and n8n improvements. If you encounter any issues, technical support is available to ensure smooth integration and setup. Key terms: Telegram Stars payment workflow, Telegram refund automation, n8n payment template, Google Sheets transaction logging, Telegram bot for payments, automated refunds on Telegram, Telegram Stars invoice workflow. Please reach out to Victor if you need further assistance with your n8n workflows and automation!

I wanted a system to monitor website content changes and notify me. So I made it using n8n. Especially my competitor blogs. I wanted to know how often they are posting new articles. (I used their sitemap.xml file) (The below workflow may vary) In the Below example, I used HackerNews for example. Explanation: First HTTP Request node crawls the webpage and grabs the website source code Then wait for x minutes Again, HTTP Node crawls the webpage If Node compares both results are equal if anything is changed. It’ll go to the false branch and notify me in telegram. Workflow: Sample Response:

2 telegram Description Description Description

Image Creation with OpenAI and Telegram Check this channel: AutoTechAi_bot Description: In the realm of automation and artificial intelligence, n8n offers a sophisticated platform for seamlessly integrating AI algorithms to enhance image creation and communication processes. This innovative workflow leverages the capabilities of OpenAI and Telegram to facilitate creative image generation and streamline communication channels, ultimately enhancing user engagement and interaction. How to Use: Set Up Credentials: Configure credentials for the Telegram account and OpenAI API to enable seamless integration. Configure Nodes: Telegram Trigger Node: Set up the node to initiate the workflow based on incoming messages from users on Telegram. OpenAI Node: Utilize advanced AI algorithms to analyze text content from messages and generate intelligent responses. Telegram Node: Send processed data, including images and responses, back to users on Telegram for seamless communication. Merge Node: Organize and combine processed data for efficient handling and integration within the workflow. Aggregate Node: Aggregate all item data, including binaries if specified, for comprehensive reporting and analysis purposes. Run Workflow: Initiate the workflow to leverage AI-enhanced image processing and communication capabilities for enhanced user interactions. Monitor Execution: Keep an eye on the workflow execution for any errors or issues that may occur during processing. Customize Workflow: Tailor the workflow nodes, parameters, or AI models to align with specific business objectives and user engagement strategies. Experience Benefits: Embrace the power of AI-driven image processing and interactive communication on Telegram to elevate user engagement and satisfaction levels. By following these steps, businesses can unlock the transformative potential of AI integration in image creation and communication workflows using n8n. Elevate your user engagement strategies and deliver exceptional experiences to your audience through innovative AI-driven solutions. Embark on a journey of innovation and efficiency with AI integration in image creation and communication workflows using n8n!

With this workflow you can extract data from resume documents uploaded via a Telegram bot. Workflow transform readable content of PDF resume into structured data, using AI nodes and returns PDF with formatted, plain HTML. You can modify this workflow to perform other actions with structured data (e.g. insert it into database or create other, well-formatted documents). Functionality of this workflow was presented during the n8n community call on March 7, 2024 - recording of presentation available here. ⚠️ Workflow made for demo purposes. If you want to use it in real life, please make sure necessary measures for personal data protection are set. How it works? User uploads readable PDF resume document into Telegram bot. After authentication based on chat ID parameter, workflow extracts text from the PDF and transfers it into AI chain with connected sub-nodes: OpenAI Chat Model and Structured Output (JSON) Parser. Then, each extracted section (employment history, projects etc.) is formatted into desired HTML structure. Finally, the document is converted into new, structured PDF using Gotenberg. 💡 This workflow requires installed Gotenberg. If you are not familiar with this software, please have a look on my YouTube tutorial. You can also replace call to Gotenberg with other PDF generation service (such as PDFMonkey or ApiTemplate). Set up steps Create Telegram bot and add its credentials in n8n. Set your chat ID parameter in Auth node. Adjust JSON schema in Structured Output Parser according to your needs. Optionally: replace HTTP call to Gotenberg with PDF generation service of your choice. If you like this workflow, please subscribe to my YouTube channel and/or my newsletter.

Transforming Emails into Podcasts 🎙️ Check out this channel for example. The n8n workflow described here aims to revolutionize the way users engage with promotional emails by converting them into entertaining audio podcasts. This innovative project leverages automation through n8n to streamline tasks and enhance user experience. Project Benefit 🎧🌟 The primary goal of this project is to transform "CATEGORY_PROMOTIONS" emails into engaging audio content. By converting text into speech, users can enjoy promotional material hands-free, making it easier to consume information while on the go or relaxing. The workflow consists of several key steps orchestrated seamlessly to deliver a delightful experience to users. How to Use the Workflow: Gmail trigger Node: Initiates the workflow by fetching "CATEGORY_PROMOTIONS" emails at regular intervals. The Gmail Trigger node in your N8N workflow is set to poll for new emails every minute and is configured to filter emails with the label "CATEGORY_PROMOTIONS" before triggering the workflow. Steps to Use Filters Inside the Gmail Trigger Node: Configure Gmail Trigger Node: Set "Poll Times" to "Every Minute" to check for new emails at regular intervals. Enable the "Simple" toggle if you want to simplify the node interface. Under "Filters", specify the label IDs you want to filter by. In this case, it's set to "CATEGORY_PROMOTIONS". Adjust any additional options as needed. // Configure Gmail Trigger node pollTimes: { item: [ { mode: "everyMinute" } ] }, simple: false, filters: { labelIds: [ "CATEGORY_PROMOTIONS" ] }, options: {} Save and Execute: Save your workflow and execute it to start monitoring your Gmail account for new emails with the specified label filter. By following these steps, your workflow will effectively trigger based on new emails that match the "CATEGORY_PROMOTIONS" label in your Gmail account. Get message content Node: Extracts the email content for processing. Summarization Chain Node: Generates concise summaries using advanced methods for better readability. Delete the unnecessary items Node: Removes irrelevant details from the email content. Text to Free TTS Node: Converts the summary text into speech using Free TTS technology. Convert from base64 to File Node: Transforms the audio data into a compatible file format. Merge Text with Audio Node: Combines the text and audio components seamlessly. Aggregate in same cell Node: Gathers all processed data for finalization. Send Message to Telegram Node: Dispatches the audio message along with a caption to a designated Telegram chat ID. By automating these tasks, the workflow ensures efficient communication and delivers content in a more engaging format, fostering a positive user experience. Configuration Instructions: The configuration of this workflow involves setting up the necessary nodes and establishing connections between them. Each node performs a specific function crucial to the overall operation of the workflow. Additionally, credentials need to be provided for accessing Gmail and OpenAI services to enable seamless data processing and summarization. Utilizing Text-to-Speech API 🎧 In addition to n8n automation, an external Text-to-Speech API plays a pivotal role in generating audio content from text data. By sending a POST request with JSON data containing the text and voice preferences, users can quickly receive audio files of the converted content. The API offers a straightforward interface for text-to-speech conversion, making it ideal for creating audio clips efficiently. To access this API, simply submit the desired text and voice selection to receive the generated speech audio file. The API endpoint can be accessed at https://tiktok-tts.weilnet.workers.dev/api/generation or through https://tiktokvoicegenerator.com/. In conclusion, this n8n workflow coupled with a Text-to-Speech API presents a powerful solution for transforming emails into captivating podcasts, enhancing user engagement and communication effectiveness. By embracing automation and innovative technologies, this project aims to improve user experience and streamline content delivery processes. 🌈✨🚀

Overview This workflow automates the process of notifying users about new emails via Telegram and temporarily hosting the email content on a secret HTML page. It is ideal for users who need immediate notifications and a secure, temporary web view of their email content. Use Cases Immediate notification of new emails in Telegram with the ability to preview the email content in a secure, temporary HTML format. Automation for users who need to keep track of their emails without constantly checking their email client. Useful for teams or individuals who require instant updates on critical emails and prefer a quick preview through a web interface. My Personal Use Case: Secure Subscription Sharing From time to time, I find myself wanting to share my paid subscriptions with friends, but giving out OTP codes manually or sharing my email isn't a good idea due to security concerns. I attempted to use the IMAP node to integrate with Telegram secret channel for this purpose but encountered numerous problems, such as difficulties in scraping content from emails. Additionally, the Telegram API sometimes rejects certain special characters found within email contents. After facing these challenges, I discovered that rendering emails as HTML pages and sharing them directly is the most effective solution. This approach bypasses the issues with character limitations and content scraping, providing a seamless way to share subscription benefits securely. Services/APIs Used | Service/API | Node Type | Description | |----------------------|-------------------------|------------------------------------------------------| | IMAP Email Server | Email Trigger (IMAP) | Triggers the workflow on receiving a new email. | | Telegram API | Telegram | Sends notifications and manages messages in Telegram.| | GitHub Gist API | HTTP Request (Github Gist) | Temporarily hosts email content on GitHub Gist. | | GitHub Gist API (Deletion) | HTTP Request (Github Gist ‌) | Deletes the temporary GitHub Gist after a specified time. | | Wait | Wait | Delays the workflow for a specified period. | Configuration Steps Email Trigger (IMAP): Configure your IMAP email credentials to enable the workflow to check for new emails. Telegram Nodes: Insert your Telegram bot's API credentials and your chat ID in both Telegram nodes to send and delete messages. Github Gist Nodes: Provide your GitHub API credentials to create and delete Gists. Ensure the GitHub token has the necessary permissions to create and delete Gists. Wait Node: Adjust the wait time according to your preference for how long the email content should be accessible via the HTML page. Screenshot Additional Notes Ensure all credentials are securely stored and have the minimum necessary permissions for the workflow to function. Test the workflow with non-sensitive emails to ensure it operates as expected before using it with critical email accounts. Consider the privacy and security implications of temporarily hosting email content on GitHub Gist. For any questions or issues, refer to the respective API documentation for each service used or consult the n8n community for support.

Example: @SubAlertMe_Bot Summary: The automated image analysis and response workflow using n8n is a sophisticated solution designed to streamline the process of analyzing images sent via Telegram and delivering insightful responses based on the analysis outcomes. This cutting-edge workflow employs a series of meticulously orchestrated nodes to ensure seamless automation and efficiency in image processing tasks. Use Cases: This advanced workflow caters to a myriad of scenarios where real-time image analysis and response mechanisms are paramount. The use cases include: Providing immediate feedback on images shared within Telegram groups. Enabling automated content moderation based on the analysis of image content. Facilitating rapid categorization and tagging of images based on the results of the analysis. Detailed Workflow Setup: To effectively implement this workflow, users must adhere to a meticulous setup process, which includes: Access to the versatile n8n platform, ensuring seamless workflow orchestration. Integration of a Telegram account to facilitate image reception and communication. Utilization of an OpenAI account for sophisticated image analysis capabilities. Configuration of Telegram and OpenAI credentials within the n8n environment for seamless integration. Proficiency in creating and interconnecting nodes within the n8n workflow for optimal functionality. Detailed Node Description: Get the Image (Telegram Trigger): Actively triggers upon receipt of an image via Telegram, ensuring prompt processing. Extracts essential information from the received image message to initiate further actions. Merge all fields To get data from trigger: Seamlessly amalgamates all relevant data fields extracted from the trigger node for comprehensive data consolidation. Analyze Image (OpenAI): Harnesses the powerful capabilities of OpenAI services to conduct in-depth analysis of the received image. Processes the image data in base64 format to derive meaningful insights from the visual content. Aggregate all fields: Compiles and consolidates all data items for subsequent processing and analysis, ensuring comprehensive data aggregation. Send Content for the Analyzed Image (Telegram): Transmits the analyzed content back to the Telegram chat interface for seamless communication. Delivers the analyzed information in textual format, enhancing user understanding and interaction. Switch Node: The Switch node is pivotal for decision-making based on predefined conditions within the workflow. It evaluates incoming data to determine the existence or absence of specific elements, such as images in this context. Utilizes a set of rules to assess the presence of image data in the message payload and distinguishes between cases where images are detected and when they are not. This crucial node plays a pivotal role in directing the flow of the workflow based on the outcomes of its evaluations. Conclusion: The automation of image analysis processes through this sophisticated workflow not only enhances operational efficiency but also revolutionizes communication dynamics within Telegram interactions. By incorporating this advanced workflow solution, users can optimize their image analysis workflows, bolster communication efficacy, and unlock new levels of automation in image processing tasks.