Workflow Templates

Overview This automated workflow fetches Upwork job postings using Apify, removes duplicate job listings via Airtable, and sends new job opportunities to Slack. Key Features: Automated job retrieval** from Upwork via Apify API Duplicate filtering** using Airtable to store only unique jobs Slack notifications** for new job postings Runs every 30 minutes** during working hours (9 AM - 5 PM) This workflow requires an active Apify subscription to function, as it uses the Apify Upwork API to fetch job listings. Who is This For? This workflow is ideal for: Freelancers looking to track Upwork jobs in real time Recruiters automating job collection for analytics Developers who want to integrate Upwork job data into their applications What Problem Does This Solve? Manually checking Upwork for jobs is time-consuming and inefficient. This workflow: Automates job discovery based on your keywords Filters out duplicate listings, ensuring only new jobs are stored Notifies you on Slack when new jobs appear How the Workflow Works 1. Schedule Trigger (Every 20 Minutes) Triggers the workflow at 20-minute intervals Ensures job searches are only executed during working hours (9 AM - 5 PM) 2. Query Upwork for Jobs Uses Apify API to scrape Upwork job posts for specific keywords (e.g., "n8n", "Python") 3. Find Existing Jobs in Airtable Searches Airtable to check if a job (based on title and link) already exists 4. Filter Out Duplicate Jobs The Merge Node compares Upwork jobs with Airtable data The IF Node filters out jobs that are already stored in the database 5. Save Only New Jobs in Airtable The Insert Node adds only new job listings to the Airtable collection 6. Send a Slack Notification If a new job is found, a Slack message is sent with job details Setup Guide Required API Keys Upwork Scraper (Apify Token) – Get your token from Apify Airtable Credentials Slack API Token – Connect Slack to n8n and set the channel ID (default: #general) Configuration Steps Modify search keywords in the 'Assign Parameters' node (startUrls) Adjust the Working Hours in the 'If Working Hours' node Set your Slack channel in the Slack node Ensure Airtable is connected properly - you'll need to create a table with 'title' and 'link' columns. Adjust the 'If Working Hours' node to match your timezone and hours, or remove it altogether to receive notifications and updates constantly. How to Customize the Workflow Change keywords: update the startUrls in the 'Assign Parameters' node to track different job categories Change 'If Working Hours': Modify conditions in the IF Node to filter times based on your needs Modify Slack Notifications: Adjust the Slack message format to include additional job details Why Use This Workflow? Automated job tracking without manual searches Prevents duplicate entries in Airtable Instant Slack notifications for new job opportunities Customizable – adapt the workflow to different job categories Next Steps Run the workflow and test with a small set of keywords Expand job categories for better coverage Enhance notifications by integrating Telegram, Email, or a dashboard This workflow ensures real-time job tracking, prevents duplicates, and keeps you updated effortlessly.

Description This workflow automates the extraction of structured data from invoices or similar documents using Docsumo's API. Users can upload a PDF via an n8n form trigger, which is then sent to Docsumo for processing and structured parsing. The workflow fetches key document metadata and all line items, reconstructs each invoice row with combined header and item details, and finally exports all results as an Excel file. Ideal for automating invoice data entry, reporting, or integrating with accounting systems. How It Works A user uploads a PDF document using the integrated n8n form trigger. The workflow securely sends the document to Docsumo via REST API. After uploading, it checks and retrieves the parsed document results. Header information and table line items are extracted and mapped into structured records. The complete result is exported as an Excel (.xls) file. Setup Steps Docsumo Account: Register and obtain your API key from Docsumo. n8n Credentials Manager: Add your Docsumo API key as an HTTP header credential (never hardcode the key in the workflow). Workflow Configuration: In the HTTP Request nodes, set the authentication to your saved Docsumo credentials. Update the file type or document type in the request (e.g., "type": "invoice") as needed for your use case. Testing: Enable the workflow and use the built-in form to upload a sample invoice for extraction. Features Supports PDF uploads via n8n’s built-in form or via API/webhook extension. Sends files directly to Docsumo for document data extraction using secure credentials. Extracts invoice-level metadata (number, date, vendor, totals) and full line item tables. Consolidates all data in easy-to-use Excel format for download or integration. Modular node structure, easily extensible for further automation. Prerequisites Docsumo account with API access enabled. n8n instance with form, HTTP Request, Code, and Excel/Convert to File nodes. Working Docsumo API Key stored securely in n8n’s credential manager. Example Use Cases | Scenario | Benefit | |---------------------|-----------------------------------------| | Invoice Automation | Extract line items and metadata rapidly | | Receipts Processing | Parse and digitize business receipts | | Bulk Bill Imports | Batch process bills for analytics | Notes Credentials Security:** Do not store your API key directly in HTTP Request nodes; always use n8n credentials manager. Sticky Notes:** The workflow includes sticky notes for setup, input, API call, extraction, and output steps to assist template users. Custom Columns:** You can customize header or line item extraction by editing the Code node as needed.

Convert PDF documents to AI-generated podcasts with Google Gemini and Text-to-Speech Transform any PDF document into an engaging, natural-sounding podcast using Google's Gemini AI and advanced Text-to-Speech technology. This automated workflow extracts text content, generates conversational scripts, and produces high-quality audio files. Who is this for? This workflow template is perfect for content creators, educators, researchers, and marketing professionals who want to repurpose written content into audio format. Ideal for creating podcast episodes, educational content, or making documents more accessible. What problem does this solve? Converting written documents to engaging audio content manually is time-consuming and requires scriptwriting skills. This workflow automates the entire process, turning static PDFs into dynamic, conversational podcasts that sound natural and engaging. What this workflow does Extracts text from uploaded PDF documents Generates podcast script using Google Gemini AI with conversational tone Converts script to speech using Google's advanced TTS with customizable voices Processes audio into properly formatted WAV files Saves final podcast ready for distribution Setup Obtain API credentials: Get Google Gemini API key from AI Studio Configure credentials in n8n as "Google Gemini(PaLM) Api account" Configure voice settings: Choose from available voices: Kore (professional), Aoede (conversational), Laomedeia (energetic) Customize script generation prompts if needed Test the workflow: Upload a sample PDF file Verify audio output quality Adjust voice settings as preferred How to customize this workflow Modify script style:** Edit the prompt in the "Generate Podcast Script" node to change tone, length, or format Change voice:** Update the voice name in "Prepare TTS Request" node Add preprocessing:** Insert text cleaning nodes before script generation Integrate with storage:** Connect to Google Drive, Dropbox, or other storage services Add notifications:** Include Slack or email notifications when podcasts are ready Note: This template requires Google Gemini API access and works best with text-based PDF files under 10MB.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Automatically transform audio files into professional transcription reports with AI-powered speech recognition, timestamp generation, and formatted Google Docs output. What this workflow does Monitors Gmail for incoming audio attachments Downloads and processes audio files using VLM Run AI transcription Generates accurate transcriptions with precise timestamps and segmentation Creates professional reports in Google Docs with formatted output Handles asynchronous processing for long audio files without timeouts Setup Prerequisites: Gmail account, VLM Run API credentials, Google Docs access, self-hosted n8n. You need to install VLM Run community node Quick Setup: Configure Gmail OAuth2 for email monitoring Add VLM Run API credentials for audio transcription Set up Google Docs OAuth2 for report generation Create target Google Doc for transcription reports Update document URL in workflow nodes Test with sample audio file and activate Perfect for Meeting recordings and conference calls Voice memos and dictation workflows Interview transcriptions and journalism Podcast episode documentation Accessibility compliance and documentation Legal proceedings and court recordings Educational content and lecture notes Customer service call analysis Key Benefits Human-level accuracy** - Advanced AI speech recognition with automatic punctuation Timestamp precision** - Segmented transcriptions with exact time markers Multi-format support** - Handles MP3, WAV, M4A, AAC, OGG, FLAC files Asynchronous processing** - No timeouts for long audio files Professional formatting** - Beautifully structured Google Docs reports Automatic workflow** - Zero manual intervention required Saves hours per recording** - Transforms manual transcription into instant results Searchable documentation** - Google Docs integration enables easy content discovery How to customize Extend by adding: Speaker identification and diarization Integration with project management tools (Notion, Asana, Trello) Automatic summary generation from transcripts Translation to multiple languages Slack notifications for completed transcriptions Integration with CRM systems for call logging Audio quality enhancement preprocessing Custom formatting templates for different use cases Automatic keyword extraction and tagging Integration with calendar systems for meeting context This workflow revolutionizes audio documentation by combining cutting-edge AI transcription with professional report generation, making spoken content instantly accessible, searchable, and shareable across your organization.

Who is this template for? This template is designed for developers, DevOps engineers, and automation enthusiasts who want to streamline their GitLab merge request process using n8n, a low-code workflow automation tool. It eliminates manual intervention by automating the merging of GitLab branches through API calls. How it works ? Trigger the workflow: The workflow can be triggered by a webhook, a scheduled event, or a GitLab event (e.g., a new merge request is created or approved). Fetch Merge Request Details: n8n makes an API call to GitLab to retrieve merge request details. Check Merge Conditions: The workflow validates whether the merge request meets predefined conditions (e.g., approvals met, CI/CD pipelines passed). Perform the Merge: If all conditions are met, n8n sends a request to the GitLab API to merge the branch automatically. Setup Steps 1. Prerequisites An n8n instance (Self-hosted or Cloud) A GitLab personal access token with API access A GitLab repository with merge requests enabled 2. Create the n8n Workflow Set up a trigger: Choose a trigger node (Webhook, Cron, or GitLab Trigger). Fetch merge request details: Add an HTTP Request node to call GET /merge_requests/:id from GitLab API. Validate conditions: Check if the merge request has necessary approvals. Ensure CI/CD pipelines have passed. Merge the request: Use an HTTP Request node to call PUT /merge_requests/:id/merge API. 3. Test the Workflow Create a test merge request. Check if the workflow triggers and merges automatically. Debug using n8n logs if needed. 4. Deploy and Monitor Deploy the workflow in production. Use n8n’s monitoring features to track execution. This template enables seamless GitLab merge automation, improving efficiency and reducing manual work! Note: Never hard code API token or secret in your https request.

Overview Slack quietly released an update to their API that allows developers to build "AI Apps & Agents", which is a special classification of apps that have access to several special capabilities including: Multiple simultaneous chat threads with one user Loading "three dots" UI while your agent is thinking Option for users to pin your app to their top bar for quick chat access This workflow demonstrates how to build a Slack agent that takes advantage of all of these features. For a full video walkthrough of this workflow, watch this YouTube tutorial. Setup Instructions All of the below steps are required for this workflow to function properly unless otherwise noted. Create a Slack App Visit api.slack.com and click "Your Apps" Create a new app from scratch and follow the setup instructions In the Agents & AI Apps tab, enable the toggle and give your app a brief description In the OAuth & Permissions tab, enable the following bot token scopes: assistant:write chat:write channels:read im:history Install the app into your workspace and grant the requested permissions In your Slack workspace, right click your app's name in the sidebar, click "View app details", and make note of your apps Channel ID - you'll need this later. Copy your app's Bot User OAuth Token - you'll need that to create your n8n credentials In the Event Subscriptions tab, enable events and paste the workflows PRODUCTION webhook url (from this workflow's trigger node) into the input. In the same tab under "Susbcribe to bot events", select message.im Create a Postgres database In order to save the chat history and give your agent a working memory, you'll need your own Postgres database. You can use Supabase, Neon, or any other Postgres database provider. Once you've added your database's credentials to n8n, you can select those credentials in the Postgres Chat Memory node. This worklow saves all chat history in a table called chat_histories, but you name the table whatever you want. Create n8n Credentials You'll need to create the following credentials: Slack API. Use your Bot User OAuth Token referenced above. Bearer Auth. Use the same Bot User OAuth Token. Postgres. Use the connection string or config from your database provider. OpenRouter (or any other LLM model for the agent's model node) Wire Everything Up Now that you've created your Slack app, have your Postgres database, and have created credentials, follow these steps to wire up your workflow: In the "On Message Received" trigger, use your Slack API credential and enter your apps Channel ID in the "Channel To Watch" field. In the "Set Thinking Status" node, use your Bearer Auth credential. In the "Postgres Chat Memory" node, use your Postgres credential. In the "Send Reply" node, use your Slack API credential. Using the Chatbot Once you've completed the setup process and added in your credentials, you'll have a fully functional Slack chatbot complete with threads, loading UI, and the ability to pin your app to your workspace's top bar. Taking the Next Steps Now that this skeleton app is in place, it's up to you to add horsepower to the AI agent at the center of it all. Customize the prompts and add whatever tools you'd like. The sky is the limit! If you have any questions or feedback about this workflow, or would like me to build custom workflows for your business, email me at n8n@paperjam.agency.

Use case Workshop We are using this workflow in our workshops to teach how to use Tools a.k.a functions with artificial intelligence. In this specific case, we will use a generic "AI Agent" node to illustrate that it could use other models from different data providers. Enhanced Weather Forecasting In this small example, it's easy to demonstrate how to obtain weather forecast results from the Open-Meteo site to accurately display the upcoming days. This can be used to plan travel decisions, for example. What this workflow does We will make an HTTP request to find out the geographic coordinates of a city. Then, we will make other HTTP requests to discover the weather for the upcoming days. In this workshop, we demonstrate that the AI will be able to determine which tool to call first—it will first call the geolocation tool and then the weather forecast tool. All of this within a single client conversation call. Setup Insert an OpenAI Key and activate the workflow. by Davi Saranszky Mesquita https://www.linkedin.com/in/mesquitadavi/

What this workflow does This workflow in n8n demonstrates how to send a message in Lark using a Lark bot. It begins with a manual trigger and then retrieves the necessary Lark token via a POST request. The token is used to authenticate and send a message to a specific chat using the Lark API. The input node provides the required app_id, app_secret, chat_id, and message content. After obtaining the token, the message is sent with the Lark API's message/v4/send/ endpoint. Who This Is For This n8n workflow is ideal for organizations, teams, and developers who need to automate message sending within Lark, especially those managing notifications, alerts, or team reminders. It can help users reduce manual messaging tasks by leveraging a Lark bot to deliver messages at specific intervals or based on particular conditions, enhancing team communication and responsiveness. Setup Fill the Input node with your values Exchange the bearer token in the Send Message node with your token Author: Hiroshi

This workflow turns any Telegram bot into an AI-powered social media command center for photos, videos and voice notes. video demo From one Telegram chat you can: Send a photo and auto-post it to Instagram, TikTok and Pinterest with AI captions. Send a video and: Let AI generate titles + descriptions and upload it to TikTok, Instagram and YouTube. Use /thumb to generate 4 custom thumbnails with Nano Banana Pro. Use /edit ... to run FFmpeg edits (cut, mute, resize, speed, etc.) via Upload-Post FFmpeg jobs and get the edited video back in Telegram. Send a voice note and turn it into posts for LinkedIn, X (Twitter) and Threads, then auto-publish. Keep human approval in the loop: every caption or text post is shown in Telegram for you to accept before publishing. Out of the box, the captions and long descriptions are optimized for Spanish (es-ES), but you can easily change the prompts to any language or brand voice. What You Can Do From Telegram 1. Photo → Instagram, TikTok & Pinterest Just send a photo (or image as document) to your Telegram bot: The workflow downloads the photo from Telegram. Gemini 2.5 Flash** analyzes the image plus your caption/text (if any). An AI Agent generates platform-specific descriptions for: TikTok (short hook, 90 chars) Instagram Pinterest (title + description) You receive a message in Telegram with all the proposed descriptions. You approve or reject with inline buttons. On approval, Upload-Post publishes the photo to: Instagram TikTok Pinterest (to the board you configured) and sends back a status message with success flags, post URLs and error messages. 2. Video → TikTok, Instagram & YouTube (no commands) If you send a video with no special caption: The workflow treats it as a standard video post. It fetches the file from Telegram. Gemini 2.5 Flash** analyzes the video and describes its content. An AI Agent turns that description + your caption into: TikTok description Instagram description YouTube title + description You get a Telegram message with the three platform descriptions to review. Once you approve: It shows “Uploading…” in Telegram. The video is sent to Upload-Post, which uploads to TikTok, Instagram and YouTube with the generated text. Finally, you receive an upload report for each platform (success, URL, error message). 3. /thumb → AI Thumbnails for Your Video (Nano Banana Pro) If you send a video with caption exactly /thumb: The workflow downloads the video. Gemini 2.5 Flash* generates a *long, SEO-rich description in Spanish** of everything that happens in the video. A second AI Agent uses that detailed description to create 3 concepts: Each concept has: title, description, and a full prompt_thumbnail (Spanish, single line) specially crafted for Nano Banana Pro. In Telegram you see the 3 concepts (titles) and select: 0, 1, 2 or “create new”. Once you choose a concept: The prompt is sent to Nano Banana Pro (fal-ai/nano-banana-pro/edit) with your reference face image (configurable). Nano Banana Pro generates 4 thumbnails (16:9). The workflow downloads the 4 images and sends them back to you in Telegram as photos so you can pick and use your favorite in your YouTube/Upload-Post pipeline. Use /thumb whenever you already have the video and just want killer thumbnails generated with AI. 4. /edit … → Natural-Language FFmpeg Video Editor If you send a video with a caption starting with /edit, for example: /edit cut the first 3 seconds and remove the audio /edit crop to vertical 9:16 and speed up x1.5 /edit blur the background and keep the subject centered The workflow behaves as a text-to-FFmpeg command generator: An AI Agent (powered by Gemini) reads your /edit instructions. It generates a safe FFmpeg command in JSON format: Always uses ffmpeg -y Uses {input} and {output} placeholders No semicolons and no dangerous shell characters The workflow then: Downloads the original video from Telegram. Calls Upload-Post FFmpeg jobs API with the video and the generated full_command. Polls the job status until it’s finished. Downloads the processed (edited) video. Sends the edited video back to you in Telegram with a simple sendVideo node. This makes Telegram a front-end for a remote FFmpeg engine: you describe the edit in natural language, and the workflow handles all the FFmpeg complexity. > Note: The edited video is returned to Telegram; if you want to auto-post it, simply send the new video again without /edit so it goes through the normal multi-platform publishing path. 5. Voice Notes → LinkedIn, X & Threads (Text Posts) For voice messages: The Telegram Trigger detects message.voice. The workflow downloads the audio file. OpenAI Whisper** transcribes the recording. An AI Agent turns the transcription into: A LinkedIn post (Spanish, long-form dev/creator style, based on your examples). A Threads post (Spanish, up to ~500 chars). A Tweet / X post or thread (English, using hooks + hashtags like #n8n, #automation, #dev). In Telegram you see a preview message with the suggested copy for Threads, LinkedIn and X. After you approve: You get an “Uploading…” message. Upload-Post publishes: To your LinkedIn organization page (configured by ID). To X (Twitter). To Threads. The workflow sends a status message with success flags and URLs for each platform. This is perfect for “talk to your phone, ship content to all your text platforms”. How the Workflow Is Structured Telegram Trigger** Listens to every incoming message and routes by type: /start → No-Op voice → Audio pipeline document/photo → Photo pipeline video → Video/thumbnail/editor pipelines (/thumb, /edit or normal) AI Blocks (Gemini + OpenAI)** Gemini 2.5 Flash for: Photo understanding. Short video descriptions (for auto-posting). Long, detailed video summaries (for thumbnail generator). OpenAI Whisper for voice transcription. Multiple AI Agents (Gemini chat) with structured JSON output parsers for: Per-platform social captions. Threads/LinkedIn/X posts. Thumbnail prompts and title concepts. FFmpeg command generation. Upload-Post Integration** Photos → Instagram, TikTok, Pinterest. Videos → TikTok, Instagram, YouTube. Text → LinkedIn page, X, Threads. FFmpeg job endpoint for server-side video editing. All uploads return status, URL and error messages back into Telegram. Human-in-the-Loop** All critical AI outputs go through sendAndWait nodes in Telegram: You review and choose whether to publish or not. You choose which thumbnail concept to use. Requirements & Setup Accounts & APIs** Telegram bot (via @BotFather). Upload-Post.com account with your social profiles connected. OpenAI API key (Whisper). Google Gemini API key (AI Studio). Nano Banana Pro / fal.ai key (for thumbnails). Runtime** n8n instance (cloud or self-hosted). FFmpeg available where n8n runs (Docker image, VM, etc.) for local checks if needed (the heavy lifting is delegated to Upload-Post FFmpeg jobs). Configuration** Create Telegram credentials with your bot token. Create Upload-Post credentials with your API token. Set upload_post_user and pinterest_board_id in the Edit Fields node. Optionally replace: Example face image URL used for Nano Banana Pro. LinkedIn organization ID. Any language / tone in the AI agent system prompts. Ideal Use Cases Creators & influencers* who want to post to every platform from *one Telegram chat**. Agencies** who want a “content butler” clients can use without touching n8n. Solo devs & makers** who publish workflows, devlogs and product updates and want: Multi-platform video posts. Voice → LinkedIn/X/Threads posts. Easy text-based video editing and thumbnail generation. Install this template, plug in your keys, talk to your bot in Telegram, and turn it into your all-in-one AI social media machine.

💥 Create viral Ads with NanoBanana & Seedance, publish on socials via upload-post Who is this for? This workflow is designed for marketers, content creators, and small businesses who want to automate the creation of engaging social media ads without spending hours on manual design, video editing, or publishing. What problem is this workflow solving? / Use case Manually creating ads for multiple platforms is time-consuming and repetitive. You need to generate visuals, edit videos, add music, and then publish them across social channels. This workflow automates the end-to-end ad production pipeline, saving time while ensuring consistent, professional-quality output. What this workflow does Receives ad ideas via Telegram. Uses NanoBanana to generate and edit realistic product images. Transforms images into engaging short videos with Seedance. Generates background music with Suno. Merges video and audio into a polished final ad. Reads brand info and generates ad copy with AI (OpenAI). Publishes ads to Instagram, TikTok, YouTube, Facebook, and X via upload-post. Stores media and campaign data in Google Drive and Google Sheets for tracking. Sends back notifications and previews via Telegram. Setup Connect your accounts: Telegram Google Drive Google Sheets OpenAI API NanoBanana API Seedance API Suno API Upload-post Prepare Google Sheets: Add a sheet for brand details (name, category, features, website). Add another sheet for video logs (status, links, captions). Configure upload-post: Ensure your social accounts (TikTok, Instagram, YouTube, Facebook, X) are linked to upload-post. How to customize this workflow to your needs Prompts* → Adjust the *image/video/music prompts** to better reflect your brand’s tone and products. Ad copy* → Modify the AI prompt inside the *Ads Copywriter Generator** to control wording, style, and structure. Publishing scope* → Choose only the platforms you want (TikTok, Instagram, etc.) inside the *upload-post** node. Storage** → Update Google Drive folder IDs and Google Sheets document IDs to match your own workspace. 👉 With this template, you get a fully automated viral ad production system powered by AI visuals, video rendering, and auto-publishing across social platforms. Perfect for scaling your content strategy while saving time. 📄 Documentation: Notion Guide Demo Video 🎥 Watch the full tutorial here: YouTube Demo Need help customizing? Contact me for consulting and support : Linkedin / Youtube

🎬 AI Video Studio Bot - Telegram to YouTube Shorts, TikTok and Instagram Reels Automation Transform text into viral shorts — all from your phone 📱✨ 🎥 Watch It In Action 🔗 Full Demo: youtu.be/OI_oJ_2F1O0 🚀 What This Workflow Does Imagine having a full-stack AI video production studio in your pocket — no editing software, no dashboard hopping, no prompt engineering. Just pure creation magic through Telegram. This n8n workflow transforms Telegram into your personal AI video factory that: Your Message → AI Magic → Viral Short → Auto-Published ⏱️ 30 seconds 🎬 2-5 minutes 📤 Done! The Complete Pipeline: 📱 Message Telegram Bot - Send text, image, or voice memo 🤖 AI Prompt Generation - GPT-4 crafts perfect video prompts 🎬 Video Creation - Veo 3, Sora 2, or Seedance generates your short 📤 Auto-Upload - Instantly publishes to YouTube Shorts 🔁 Extend & Iterate - One-tap video extension (Veo only) No manual work. No technical skills. No limits. 💡 Why This Changes Everything | Traditional Way | This Workflow | |----------------|---------------| | ❌ Open 5+ platforms | ✅ One Telegram chat | | ❌ 30 min per video | ✅ 5 min per video | | ❌ Complex prompts needed | ✅ AI writes prompts for you | | ❌ Manual uploads | ✅ Auto-publishes everywhere | | ❌ Desktop only | ✅ Works from your phone | Result: Create 10+ YouTube Shorts during your lunch break 🚀 🎨 Video Styles - Choose Your Vibe Control everything with simple Telegram commands: | Command | Style | Perfect For | |---------|-------|------------| | /general | 🎭 Creative Shorts | Product demos, hooks, viral content | | /lost | 👻 Found Footage | Mystery, horror, urban exploration | | /3d | 🎮 3D Objects | Talking products, explainers, memes | | /story | 📖 Emotional Stories | Multi-scene narratives, brand stories | No command? AI intelligently picks the best style for your message. 🤖 AI Models - Pick Your Engine Choose your video generation model right from Telegram: Veo 3 / Veo 3 Fast ⚡ Best for: Quick iterations, realistic scenes Speed: 2-3 minutes Unique: Video extension support Sora 2 🎬 Best for: Cinematic quality, long sequences Speed: 4-5 minutes Unique: Best motion consistency Seedance 1.5 Pro 🌊 Best for: Artistic effects, fluid motion Speed: 3-4 minutes Unique: Stylized aesthetics Select directly in-chat with interactive buttons! ⚡ Power Features 🎯 Smart Video Generation AI analyzes your message intent Generates optimal prompts automatically Adapts to text, images, or voice input 📤 Auto-Publishing Pipeline Uploads to YouTube Shorts instantly AI-generated titles, descriptions, tags SEO-optimized for maximum reach 🔄 Extend & Refine One-tap video extension (Veo only) Keep the vibe, extend the story No re-generation needed 💳 Credit Management Real-time credit checking Prevents failed generations Session-based tracking with Redis 🔔 Status Monitoring Real-time generation updates Webhook polling for long jobs Graceful error handling & cancellation 🗂️ Session Storage Redis-powered state management Resume interrupted workflows Track generation history 🎪 Perfect For | Creator Type | Use Case | |-------------|----------| | 🎥 Faceless Channels | Generate endless Shorts without showing face | | 🏢 Agencies | Scale content production 10x for clients | | 📱 Solo Creators | Daily Shorts from your phone, no laptop needed | | 🤖 AI Farms | Automate content pipelines end-to-end | | 🧪 Experimenters | Rapid prototyping of video ideas | | 📊 Marketers | A/B test video concepts at scale | 🛠️ Tech Stack Telegram Bot API → User interface OpenAI GPT-4 → Prompt generation KIE.ai → Video generation (Veo/Sora/Seedance) YouTube Data API → Auto-publishing Redis → Session & state management S3-compatible → Video storage n8n → Orchestration layer Requirements: ✅ Telegram Bot Token ✅ OpenAI API Key ✅ KIE.ai Account (Veo/Sora/Seedance access) ✅ YouTube OAuth Credentials ✅ Redis Instance (recommended) ✅ S3-compatible Storage ✅ n8n Instance (cloud or self-hosted) 🎬 Real-World Workflow Example You: "A golden retriever puppy discovering snow for the first time" Bot: ✨ Generating your video... 📊 Credits: 50 remaining 🎬 Using: Veo 3 Fast ⏱️ ETA: 2 minutes 2 minutes later: ✅ Your video is ready! 📺 Uploaded to YouTube Shorts 🔗 Link: youtube.com/shorts/abc123 👁️ Views: 0 → 1.2K (24 hours) [Extend Video] [Generate New] Result: Viral short created from your phone while waiting for coffee ☕ 🔧 Customization Ideas 🎨 Extend the Platform Add TikTok publishing Include Instagram Reels Add Twitter video posts Support LinkedIn video 🎙️ Alternative Inputs Replace Telegram with WhatsApp Add Discord bot interface Support Slack commands Email-to-video pipeline 🎭 Creative Variations Swap OpenAI for Claude/Gemini Add custom style presets Include watermarking steps Generate captions automatically 📊 Analytics & Tracking Log all generations to Google Sheets Track video performance metrics A/B test title/thumbnail combinations Monitor credit usage trends 📊 Success Metrics After using this workflow for 30 days: | Metric | Before | After | Improvement | |--------|--------|-------|-------------| | ⏱️ Time per video | 45 min | 5 min | 9x faster | | 📹 Videos/week | 5 | 50+ | 10x volume | | 💰 Cost per video | $15 | $2 | 7.5x cheaper | | 📱 Creation location | Desktop only | Anywhere | ∞ flexibility | | 🧠 Prompt writing | Manual | Automated | No skill needed | 🚀 Quick Start Import workflow to n8n Add credentials (Telegram, OpenAI, KIE.ai, YouTube, Redis) Configure video storage (S3) Activate workflow Message your bot and watch the magic happen Setup time: ~20 minutes First video: ~5 minutes after setup 🏷️ Tags telegram ai-video youtube-shorts automation content-creation openai veo sora seedance text-to-video social-media creator-tools faceless-channel redis s3 n8n-workflow telegram-bot video-automation shorts-generator 📜 License MIT License - Use freely, modify, share, monetize! ⚡ Stop editing. Start generating. Scale your content empire. ⚡ Created by Joe Venner | Built with ❤️ and n8n

How it works This template is a complete, hands-on tutorial for building a RAG (Retrieval-Augmented Generation) pipeline. In simple terms, you'll teach an AI to become an expert on a specific topic—in this case, the official n8n documentation—and then build a chatbot to ask it questions. Think of it like this: instead of a general-knowledge AI, you're building an expert librarian. The workflow is split into two main parts: Part 1: Indexing the Knowledge (Building the Library) This is a one-time process you run manually. The workflow automatically scrapes all pages of the n8n documentation, breaks them down into small, digestible chunks, and uses an AI model to create a special numerical representation (an "embedding") for each chunk. These embeddings are then stored in n8n's built-in Simple Vector Store. This is like a librarian reading every book and creating a hyper-detailed index card for every paragraph. Important: This in-memory knowledge base is temporary. It will be erased if you restart your n8n instance, and you will need to run the indexing process again. Part 2: The AI Agent (The Expert Librarian) This is the chat interface. When you ask a question, the AI agent doesn't guess the answer. Instead, it uses your question to find the most relevant "index cards" (chunks) from the knowledge base it just built. It then feeds these specific, relevant chunks to a powerful language model (Gemini) with a strict instruction: "Answer the user's question using ONLY this information." This ensures the answers are accurate, factual, and grounded in your provided documents. Set up steps Setup time: 2 minutes (plus 15-20 minutes for indexing) This template uses n8n's built-in tools, removing the need for an external database. Follow these simple steps to get started. Configure Google AI Credentials: You will need a Google AI API key for the Gemini models. In your n8n workflow, go to any of the three Gemini nodes (e.g., Gemini 2.5 Flash). Click the Credential dropdown and select + Create New Credential. Enter your Gemini API key and save. Apply Credentials to All Nodes: Your new Google AI credential is now saved. Go to the other two Gemini nodes (Gemini Chunk Embedding and Gemini Query Embedding) and select your newly created credential from the dropdown list. Build the Knowledge Base: Find the Start Indexing manual trigger node at the top-left of the workflow. Click its "Execute workflow" button to start the indexing process. ⚠️ Be Patient: This will take 15-20 minutes as it scrapes and processes the entire n8n documentation. You only need to do this once per n8n session. If you restart n8n, you must run this step again. Chat with Your Expert Agent: Once the indexing is complete, Activate the entire workflow using the toggle at the top of the screen. Open the RAG Chatbot chat trigger node (bottom-left) and copy its Public URL. Open the URL in a new tab and start asking questions about n8n! For example: "How does the IF node work?" or "What is a sub-workflow?".