Generate YouTube scripts for shorts & long-form with Gemini AI and Tavily Research
π€ Automated YouTube Script Generator (Shorts & Long-Form)
This workflow is a content multiplier. Provide a single video topic via a form, and it automatically researches, outlines, and writes two separate scripts: one for a YouTube Shorts and another for a Long-form video, saving both directly to Google Docs.
β¨ Key Features
- Dual-Format Output: Creates tailored scripts for both Shorts and long-form videos from one idea.
- AI-Powered Writing: Uses Google Gemini for all creative steps, from building a structured outline to writing the final scripts.
- Up-to-Date Research: Integrates Tavily AI to pull fresh, relevant information from the web.
- Fully Automated: An end-to-end process that takes a form submission and delivers final documents to your Google Drive with no manual steps.
βοΈ How It Works
After a topic is submitted, the workflow splits into two parallel branches:
- The Shorts Branch: This path is built for speed. It performs a quick web search and immediately uses an AI agent to write a short, punchy script.
- The Long-Form Branch: This path focuses on structure. It conducts a web search, uses an AI agent to first create a detailed outline, and then uses another AI agent to write a comprehensive script based on that outline.
π Prerequisites
- An active n8n instance.
- A form to submit your video topic.
- API keys for Tavily AI and Google Gemini.
- Google Account credentials (OAuth2) configured in n8n for Google Docs.
π οΈ Setup Guide
- On form submission Trigger: Configure your form to accept a field for your video topic (e.g., a field named
topic). - Tavily Nodes: In both
Tavilynodes, select or create your Tavily API credential and paste in your API key. - Google Gemini Chat Model: In the nodes labeled
AI AgentandCreate Outline, select your Google AI credential linked to your Gemini API key. - Google Docs Nodes: For all four Google Docs nodes (
Create Doc,Update Doc, etc.), select your Google OAuth2 credential. - Activate the Workflow: Once all credentials are in place, save and activate the workflow.
π How to Use
- Activate the workflow.
- Submit your topic via the connected form.
- Check your Google Drive a few moments later for your the new script!
Generate YouTube Scripts for Shorts & Long-Form with Gemini AI and Tavily Research
This n8n workflow automates the generation of YouTube video scripts for both short-form (Shorts) and long-form content. It leverages Google Gemini AI for content creation and Tavily Research for information gathering, allowing you to quickly produce engaging and well-researched scripts based on a simple topic input.
What it does
This workflow streamlines the content creation process through the following steps:
- Triggers on Form Submission: The workflow starts when a user submits a form, providing a YouTube video topic and specifying whether it should be a "Short" or "Long" form video.
- Sets Video Type: Based on the form input, it sets a variable to determine if the video is a "Short" or "Long" form.
- Conditional Logic for Content Length:
- If "Short": It uses the Google Gemini AI to generate a concise script suitable for YouTube Shorts, incorporating Tavily Research for relevant information.
- If "Long": It uses the Google Gemini AI to generate a more detailed, long-form script, also leveraging Tavily Research for comprehensive data.
- Generates Script with AI Agent: An AI Agent (Google Gemini) is employed to plan and execute the script generation, utilizing a search tool (Tavily Research) to gather up-to-date and accurate information related to the provided topic.
- Creates Google Doc: The generated script (either short or long) is then automatically saved as a new document in Google Docs.
Prerequisites/Requirements
To use this workflow, you will need:
- n8n Account: A running instance of n8n.
- Google Gemini API Key: For the Google Gemini AI Agent and Chat Model nodes.
- Tavily Research API Key: For the HTTP Request node that performs web searches.
- Google Docs Credentials: An authenticated Google Docs account with n8n to create documents.
Setup/Usage
- Import the Workflow: Download the provided JSON and import it into your n8n instance.
- Configure Credentials:
- Set up your Google Gemini credentials for the "Google Gemini Chat Model" and "AI Agent" nodes.
- Configure your Tavily Research API Key in the "HTTP Request" node.
- Set up your Google Docs credentials for the "Google Docs" node.
- Activate the Workflow: Once all credentials are set, activate the workflow.
- Submit the Form: Access the n8n Form Trigger URL and submit a new form with your desired YouTube video topic and select the video type ("Short" or "Long").
- Monitor Google Docs: The generated script will appear as a new document in your configured Google Docs account.
Related Templates
Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax
Spark your creativity instantly in any chatβturn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. π What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing π§ Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation π Required Credentials OpenAI API Setup Go to platform.openai.com β API keys (sidebar) Click "Create new secret key" β Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai β Dashboard β API Keys Generate a new API key β Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) βοΈ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflowβchat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" π― Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration β οΈ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions
Automate Dutch Public Procurement Data Collection with TenderNed
TenderNed Public Procurement What This Workflow Does This workflow automates the collection of public procurement data from TenderNed (the official Dutch tender platform). It: Fetches the latest tender publications from the TenderNed API Retrieves detailed information in both XML and JSON formats for each tender Parses and extracts key information like organization names, titles, descriptions, and reference numbers Filters results based on your custom criteria Stores the data in a database for easy querying and analysis Setup Instructions This template comes with sticky notes providing step-by-step instructions in Dutch and various query options you can customize. Prerequisites TenderNed API Access - Register at TenderNed for API credentials Configuration Steps Set up TenderNed credentials: Add HTTP Basic Auth credentials with your TenderNed API username and password Apply these credentials to the three HTTP Request nodes: "Tenderned Publicaties" "Haal XML Details" "Haal JSON Details" Customize filters: Modify the "Filter op ..." node to match your specific requirements Examples: specific organizations, contract values, regions, etc. How It Works Step 1: Trigger The workflow can be triggered either manually for testing or automatically on a daily schedule. Step 2: Fetch Publications Makes an API call to TenderNed to retrieve a list of recent publications (up to 100 per request). Step 3: Process & Split Extracts the tender array from the response and splits it into individual items for processing. Step 4: Fetch Details For each tender, the workflow makes two parallel API calls: XML endpoint - Retrieves the complete tender documentation in XML format JSON endpoint - Fetches metadata including reference numbers and keywords Step 5: Parse & Merge Parses the XML data and merges it with the JSON metadata and batch information into a single data structure. Step 6: Extract Fields Maps the raw API data to clean, structured fields including: Publication ID and date Organization name Tender title and description Reference numbers (kenmerk, TED number) Step 7: Filter Applies your custom filter criteria to focus on relevant tenders only. Step 8: Store Inserts the processed data into your database for storage and future analysis. Customization Tips Modify API Parameters In the "Tenderned Publicaties" node, you can adjust: offset: Starting position for pagination size: Number of results per request (max 100) Add query parameters for date ranges, status filters, etc. Add More Fields Extend the "Splits Alle Velden" node to extract additional fields from the XML/JSON data, such as: Contract value estimates Deadline dates CPV codes (procurement classification) Contact information Integrate Notifications Add a Slack, Email, or Discord node after the filter to get notified about new matching tenders. Incremental Updates Modify the workflow to only fetch new tenders by: Storing the last execution timestamp Adding date filters to the API query Only processing publications newer than the last run Troubleshooting No data returned? Verify your TenderNed API credentials are correct Check that you have setup youre filter proper Need help setting this up or interested in a complete tender analysis solution? Get in touch π LinkedIn β Wessel Bulte
Auto-reply & create Linear tickets from Gmail with GPT-5, gotoHuman & human review
This workflow automatically classifies every new email from your linked mailbox, drafts a personalized reply, and creates Linear tickets for bugs or feature requests. It uses a human-in-the-loop with gotoHuman and continuously improves itself by learning from approved examples. How it works The workflow triggers on every new email from your linked mailbox. Self-learning Email Classifier: an AI model categorizes the email into defined categories (e.g., Bug Report, Feature Request, Sales Opportunity, etc.). It fetches previously approved classification examples from gotoHuman to refine decisions. Self-learning Email Writer: the AI drafts a reply to the email. It learns over time by using previously approved replies from gotoHuman, with per-classification context to tailor tone and style (e.g., different style for sales vs. bug reports). Human Review in gotoHuman: review the classification and the drafted reply. Drafts can be edited or retried. Approved values are used to train the self-learning agents. Send approved Reply: the approved response is sent as a reply to the email thread. Create ticket: if the classification is Bug or Feature Request, a ticket is created by another AI agent in Linear. Human Review in gotoHuman: How to set up Most importantly, install the gotoHuman node before importing this template! (Just add the node to a blank canvas before importing) Set up credentials for gotoHuman, OpenAI, your email provider (e.g. Gmail), and Linear. In gotoHuman, select and create the pre-built review template "Support email agent" or import the ID: 6fzuCJlFYJtlu9mGYcVT. Select this template in the gotoHuman node. In the "gotoHuman: Fetch approved examples" http nodes you need to add your formId. It is the ID of the review template that you just created/imported in gotoHuman. Requirements gotoHuman (human supervision, memory for self-learning) OpenAI (classification, drafting) Gmail or your preferred email provider (for email trigger+replies) Linear (ticketing) How to customize Expand or refine the categories used by the classifier. Update the prompt to reflect your own taxonomy. Filter fetched training data from gotoHuman by reviewer so the writer adapts to their personalized tone and preferences. Add more context to the AI email writer (calendar events, FAQs, product docs) to improve reply quality.