AI Workflows
Artificial Intelligence tools and workflows
Enhance WordPress User Experience with AI Chatbot Using Supabase and OpenAI
This workflow integrates WordPress content with Supabase and OpenAI to create an AI chatbot that enhances user experience through Retrieval-Augmented Generation (RAG).
n8n$19.99Create a Multi-functional AI Telegram Bot with PDF Search and Google Suite Automation
Build a comprehensive AI-powered assistant on Telegram that integrates voice interactions, PDF document search, and Google Suite automation. Ideal for beginners exploring advanced AI capabilities.
n8n$19.99Automate YouTube Comment Sentiment Analysis with Google Sheets and AI
This n8n workflow automates the extraction and sentiment analysis of YouTube video comments using Google Sheets and AI, providing insights into audience sentiment.
n8n$14.99Automate Web Accessibility Audits with AI-Generated Alt Texts
Enhance your website's accessibility by automatically generating descriptive alt texts for images using AI and storing results in Google Sheets.
n8n$9.99Automate Hairstyle Edits and LINE Group Sharing with OpenAI
This workflow automates the process of editing hairstyles in images using OpenAI, uploading the results to Cloudinary, and sharing them with a LINE group. Ideal for salons and creative teams seeking efficient and consistent hairstyle modifications.
n8n$4.99Automate GLPI Knowledge Base RAG Pipeline with Google Gemini and PostgreSQL
This workflow automates the creation of a Retrieval-Augmented Generation (RAG) pipeline using GLPI Knowledge Base content. It streamlines data retrieval, transformation, and vector storage, enhancing the efficiency of building AI-powered support agents.
n8n$9.99Automate PDF Analysis and Reporting with Mistral OCR and AI Agents
Leverage Mistral's advanced OCR capabilities to transform complex PDFs into detailed research reports or concise newsletters using AI-driven workflows.
n8n$14.99Transcribing Bank Statements to Markdown Using Gemini Vision AI
This n8n workflow demonstrates an approach to parsing bank statement PDFs with multimodal LLMs as an alternative to traditional OCR. This allows for much more accurate data extraction from the document, especially when it comes to tables and complex layouts. Multimodal Parsing is better than traditional OCR because: - It reduces complexity and overhead by avoiding the need to preprocess the document into text format such as markdown before passing to the LLM. - It handles non-standard PDF formats which may produce garbled output via traditional OCR text conversion. - It's orders of magnitude cheaper than premium OCR models that still require post-processing cleanup and formatting. LLMs can format to any schema or language you desire! ## How it works You can use the example bank statement created specifically for this workflow here: [https://drive.google.com/file/d/1wS9U7MQDthj57CvEcqG_Llkr-ek6RqGA/view?usp=sharing](https://drive.google.com/file/d/1wS9U7MQDthj57CvEcqG_Llkr-ek6RqGA/view?usp=sharing) - A PDF bank statement is imported via Google Drive. For this demo, I've created a mock bank statement which includes complex table layouts of 5 columns. Typically, OCR will be unable to align the columns correctly and mistake some deposits for withdrawals. - Because multimodal LLMs do not accept PDFs directly, we'll have to convert the PDF to a series of images. We can achieve this by using a tool such as [Stirling PDF](https://github.com/Stirling-Tools/Stirling-PDF/). Stirling PDF is self-hostable which is handy for sensitive data such as bank statements. - Stirling PDF will return our PDF as a series of JPGs (one for each page) in a zipped file. We can use n8n's decompress node to extract the images and ensure they are ordered by using the Sort node. - Next, we'll resize each page using the Edit Image node to ensure the right balance between resolution limits and processing speed. - Each resized page image is then passed into the Basic LLM node which will use our multimodal LLM of choice - Gemini 1.5 Pro. In the LLM node's options, we'll add a user message of type binary (data) which is how we add our image data as an input. - Our prompt will instruct the multimodal LLM to transcribe each page to markdown. Note, you do not need to do this - you can just ask for data points to extract directly! Our goal for this template is to demonstrate the LLM's ability to accurately read the page. - Finally, with our markdown version of all pages, we can pass this to another LLM node to extract required data such as deposit line items. ## Requirements - Google Gemini API for Multimodal LLM. - Google Drive access for document storage. - [Stirling PDF](https://github.com/Stirling-Tools/Stirling-PDF) instance for PDF to Image conversion ## Customizing the workflow - At the time of writing, Gemini 1.5 Pro is the most accurate in text document parsing with a relatively low cost. If you are not using Google Gemini, however, you can switch to other multimodal LLMs such as OpenAI GPT or Anthropic Claude. If you don't need the markdown, simply asking what to extract directly in the LLM's prompt is also acceptable and would save a few extra steps. - Not parsing any bank statements any time soon? This template also works for invoices, inventory lists, contracts, legal documents, etc.
n8n$14.99Message Buffer System with Redis for Efficient Processing
## Message-Batching Buffer Workflow (n8n) **This workflow implements a lightweight message-batching buffer using Redis for temporary storage and a JavaScript consolidation function to merge messages.** It collects incoming user messages per session, waits for a configurable inactivity window or batch size threshold, consolidates buffered messages via custom code, then clears the buffer and returns the combined response—all without external LLM calls. --- ### Key Features * **Redis-backed buffer** queues incoming messages per `context_id`. * **Centralized Config Parameters** node to adjust thresholds and timeouts in one place. * **Dynamic wait time** based on message length (configurable `minWords`, `waitLong`, `waitShort`). * **Batch trigger** fires on inactivity timeout or when `buffer_count` ≥ `batchThreshold`. * **Zero-cost consolidation** via built-in JavaScript Function (`consolidate buffer`)—no GPT-4 or external API required. --- ### Setup Instructions 1. **Extract Session & Message** * Trigger: `When chat message received` (webhook) or `When testing workflow` (manual). * Map inputs: set variables `context_id` and `message` into a Set node named **Mock input data** (for testing) or a proper mapping node in production. 2. **Config Parameters** * Add a Set node **Config Parameters** with: ``` minWords: 3 # Word threshold waitLong: 10 # Timeout (s) for long messages waitShort: 20 # Timeout (s) for short messages batchThreshold: 3 # Messages to trigger batch early ``` * All downstream nodes reference these JSON values dynamically. 3. **Determine Wait Time** * Node: **get wait seconds** (Code) * JS code: ```js const msg = $json.message || ""; const wordCount = msg.split(/\s+/).filter(w => w).length; const { minWords, waitLong, waitShort } = items[0].json; const waitSeconds = wordCount < minWords ? waitShort : waitLong; return [{ json: { context_id: $json.context_id, message: msg, waitSeconds } }]; ``` 4. **Buffer Message in Redis** * **Buffer messages**: `LPUSH buffer_in:{{$json.context_id}}` with payload `{text, timestamp}`. * **Set buffer_count increment**: `INCR buffer_count:{{$json.context_id}}` with TTL `{{$json.waitSeconds + 60}}`. * **Set last_seen**: record `last_seen:{{$json.context_id}}` timestamp with same TTL. 5. **Check & Set Waiting Flag** * **Get waiting_reply**: if null, **Set waiting_reply** to `true` with TTL `{{$json.waitSeconds}}`; else exit. 6. **Wait for Inactivity** * **WaitSeconds** (webhook): pauses for `{{$json.waitSeconds}}` seconds before batch evaluation. 7. **Check Batch Trigger** * **Get last_seen** and **Get buffer_count**. * IF `(now - last_seen) ≥ waitSeconds * 1000` OR `buffer_count ≥ batchThreshold`, proceed; else use **Wait** node to retry. 8. **Consolidate Buffer** * **consolidate buffer** (Code): ```js const j = items[0].json; const raw = Array.isArray(j.buffer) ? j.buffer : []; const buffer = raw.map(x => { try { return typeof x === 'string' ? JSON.parse(x) : x; } catch { return null; } }).filter(Boolean); buffer.sort((a, b) => new Date(a.timestamp) - new Date(b.timestamp)); const texts = buffer.map(e => e.text?.trim()).filter(Boolean); const unique = [...new Set(texts)]; const message = unique.join(" "); return [{ json: { context_id: j.context_id, message } }]; ``` 9. **Cleanup & Respond** * **Delete** Redis keys: `buffer_in`, `buffer_count`, `waiting_reply`, `last_seen` (for the `context_id`). * Return consolidated `message` to the user via your chat integration. --- ### Customization Guidance * **Adjust thresholds** by editing the **Config Parameters** node. * **Change concatenation** (e.g., line breaks) by modifying the `join` separator in the consolidation code. * **Add filters** (e.g., ignore empty or system messages) inside the consolidation Function. * **Monitor performance**: for very high volume, consider sharding Redis keys by date or user segments. --- © 2025 Innovatex Automation & AI Solutions [innovatexiot.carrd.co](https://innovatexiot.carrd.co/) [LinkedIn](https://www.linkedin.com/in/edisson-andres-garcia-herrera-63a91517b/)
n8n$14.99Automate Document Processing and Delivery with Mistral OCR and AI
Streamline your document processing by leveraging Mistral OCR for data extraction, AI for intelligent processing, and multi-channel delivery through Gmail and Telegram.
n8n$14.99Generate a Legal Website Accessibility Statement with AI and WAVE
## Who is this for? This template is for any website owner, digital agency, or compliance officer operating within the **European Union**. It's designed for users who need to comply with the upcoming **European Accessibility Act (EAA)** but may not have deep technical or legal expertise. ## Disclaimer This workflow uses an npm package called cheerio to work with the specified URLs HTML code. Installing packages is only possible in self-hosting. ## What problem is this workflow solving? / Use Case Starting **June 28, 2025**, the European Accessibility Act (EAA) mandates that most websites offering products or services in the EU must be accessible and publish a formal Accessibility Statement. Manually creating this legal document is complex, requiring both a technical site analysis and knowledge of specific legal requirements. This workflow automates the generation of a compliant first draft, saving significant time and effort. ## What this workflow does After you input your details (like website URL and API key) in a central configuration node, this workflow automatically: 1. Scans your live website for accessibility issues using the powerful **WAVE API**. 2. Processes the scan results to identify the main problem areas. 3. Instructs a **Google Gemini AI agent** with a specialized legal prompt based on the European Accessibility Act. 4. Generates a formal Accessibility Statement in your desired language. 5. Saves the statement as an `.html` file and **sends it to you as an email attachment**. ## Setup This workflow is designed for a quick setup: 1. **Configure All Variables:** Click the **CHANGE THESE: dependencies** node. This is your central control panel. Fill in all the values, including your WAVE API Key, the URL to analyze, company details, and desired output language. 2. **Set Up Credentials:** You will need to connect your Google accounts for the workflow to run. * **Gemini:** Click the **gemini 2.5 pro** node, click the gear icon next to the Credential field, and connect your Google Gemini API credentials. * **Gmail:** Click the **Send report by email** node and connect your Gmail account to allow sending the final report. 3. **Activate & Execute:** Make sure the workflow is **active** in the top-right corner, then click **Execute Workflow** to run your first analysis. ## How to customize this workflow to your needs This template is a great starting point for any EU country. Here's how to adapt it: * **Localize for Your Country (Important!):** The generated statement contains a placeholder for the Enforcement Procedure. You **must** edit the prompt in the **Accessibility Statement Generator** node to replace this placeholder with the name and link to your specific country's official enforcement body. * **Change the AI:** Swap the Google Gemini node for any other AI model, like OpenAI or Anthropic Claude, by replacing the node and connecting it to the agent. * **Change the Trigger:** Replace the **When clicking 'Execute workflow'** node with a Form Trigger or Webhook Trigger to run this workflow based on external inputs, for example, to offer this analysis as a service to your clients.
n8n$9.99Automate YouTube Video to SEO Blog Post Conversion with AI
Transform YouTube videos into SEO-optimized blog posts using AI tools. This workflow extracts video transcripts, generates blog content and images, and emails the final package for publication.
n8n$9.99Automate Social Media Captions with AI and Airtable
This workflow automates the creation of social media post captions using AI, integrating seamlessly with Airtable to utilize stored background information such as target audience and tonality.
n8n$9.99Generate Written Content with GPT Recursive Writing & Editing Agents
# Who is this for? Content creators, writers, and automation enthusiasts experimenting with recursive AI workflows for content generation and refinement. Ideal for those exploring AI agents that collaborate in cycles of writing and editing. # What problem does this solve? This template introduces a fully automated, recursive writing-editing loop using multi-agent collaboration. A "Writing Agent" generates content based on an input topic. An "Editing Agent" reviews it, suggests improvements, and determines whether the work is complete. The loop continues until the editor is satisfied—allowing for high-quality, iterative AI-assisted writing with minimal human input. # How it works This template is a foundational setup to help you build custom recursive writing workflows: 1. **Trigger**: Activated by an n8n chat message containing a topic. You can customize this to work with webhooks, forms, or other input sources. 2. **Edit Handler**: A code node checks for previous edits and sets a default empty string if none are found. 3. **Writing Agent**: Generates a blurb based on the topic and any edits. Customize the prompt in this node by editing the user/system instructions to fit your tone, domain, or style preferences. 4. **Editing Agent**: Suggests specific edits and outputs a structured JSON object: ```json { "status": "incomplete", "edits": "Replace passive voice with active voice in the second sentence. Clarify the main idea in the opening line." } ``` You can adjust the JSON format or editing criteria in the prompt field. Customize the prompt in this node by editing the user/system instructions to fit your tone, domain, or style preferences. 5. **Recursive Loop**: If the status is "incomplete," the edits are passed back to the Writing Agent, which revises the blurb. 6. **Completion**: Once the Editing Agent outputs a status of "complete," the workflow ends, and the final blurb is returned to the n8n chat. # Setup Steps 1. **Import the template** into your n8n workspace. 2. **Configure API Credentials**: Link your OpenAI API key (or your preferred LLM like Claude or Gemini) in the credentials section. 3. **Customize the Prompts** (Optional but recommended): - In the **Writing Agent**, you can instruct it to mimic a specific tone, format, or genre. - In the **Editing Agent**, specify your editing standards (e.g., concise, persuasive, technical). - Modify the JSON output structure in the **Structured Output Parser** node if needed. 4. **Test and Iterate**: Run a test by sending a topic via the chat trigger and observe the loop behavior. # Example Output **Input Topic**: "The future of remote work" **Final Blurb**: "Remote work is here to stay. As companies embrace flexible setups, productivity and employee satisfaction are reaching new highs. The challenge now is to build culture and collaboration tools that keep up." This template offers a powerful starting point for recursive AI writing. Expand it with additional agents, tone shifts, formatting layers, or sentiment analysis as needed.
n8n$9.99Automate Research Question Generation from PDFs Using InfraNodus
This workflow automates the generation of research questions from PDF documents by identifying content gaps using InfraNodus knowledge graphs. It is ideal for researchers and analysts looking to uncover new insights and ideas.
n8n$9.99Automate Data Extraction via Telegram with AI and Bright Data MCP
Leverage AI to automate data extraction tasks through a Telegram bot using Bright Data MCP tools. This workflow simplifies complex operations by allowing natural language commands.
n8n$14.99Automate Weekly Tech Research with AI, Notion, and Gmail
This workflow automates your weekly tech research and reporting using AI. It schedules tasks, gathers insights with AI, stores data in Notion, and sends summary reports via Gmail.
n8n$9.99Automate Markdown to Contentful Rich Text Conversion with AI
This workflow automates the conversion of markdown content into Contentful Rich Text format using AI, ensuring seamless integration and publishing to Contentful.
n8n$9.99Automate Paul Graham Essay Analysis with Milvus and AI Chat
This workflow automates the retrieval and analysis of Paul Graham essays using Milvus for vector storage and AI for semantic search and chat capabilities.
n8n$14.99Automate WordPress Category Mapping with Azure OpenAI's GPT-5 Mini
Streamline your WordPress content categorization by using Azure OpenAI's GPT-5 Mini to automatically map content topics to category IDs, reducing manual errors and speeding up publishing.
n8n$4.99Automate Contact Data Conversion to JSON for System Integration
This n8n workflow automatically transforms unstructured contact information into structured JSON using AI, facilitating seamless integration with CRM or ERP systems.
n8n$9.99Automate AI Content Generation with Replicate's 2Ndmoises_Generator
This n8n workflow leverages the Replicate API to automate content generation using the moicarmonas/2ndmoises_generator model. It manages authentication, initiates predictions, monitors progress, and processes results efficiently.
n8n$9.99Automated WhatsApp Nutrition Consultant with AI
Transform WhatsApp into a 24/7 nutrition consultant using AI for meal analysis and personalized dietary advice.
n8n$14.99Automated AI-Driven Content Creation and Publishing for WordPress
Streamline your content strategy by automating the creation, optimization, and publishing of blog posts on WordPress using AI tools and Airtable.
n8n$19.99
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