AI Automation Workflows — Page 18 | Neura Market
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    • Automate Voice and Text AI Interactions via Telegram with Deepgram and OpenAI

      Enable seamless voice and text interactions through Telegram using Deepgram for transcription and OpenAI for intelligent responses. Ideal for businesses seeking to enhance customer support with AI-driven voice and text capabilities.

      n8nFree

    • Automate AI Avatar Video Creation with HeyGen and Google Sheets

      Streamline your AI Avatar video production by integrating Google Sheets with HeyGen API for seamless video generation and storage.

      n8nFree

    • Interactive Image Editor with FLUX: Fill Tool for Inpainting

      > Like this template? [Connect with Eduard](https://www.linkedin.com/in/parsadanyan/) via LinkedIn. This workflow is a prototype of an AI-powered image editing interface, similar to Photoshop's Generative Fill feature, but running entirely in the browser. It provides a web-based editor that allows users to: - Select areas in images using an adjustable brush tool - Input text prompts to guide the AI generation - Compare original and generated images side by side - Iterate on edits with different prompts and settings - Save or reuse generated images > Perfect for [product catalog management](https://www.reddit.com/r/n8n/comments/1h98n7a/have_a_product_catalog_make_a_flux1_in_painting/), seasonal content updates, and creative image editing tasks! **Requirements** -------------- - [FLUX API Access](https://api.bfl.ai/): You'll need API credentials from FLUX to use this workflow. - Configure the [HTTP Header Auth credential](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.httprequest/) in n8n with your FLUX API key **Key Components** ---------------- - [FLUX Fill API](https://api.us1.bfl.ai/scalar#tag/tasks/POS/v1/flux-pro-1.0-fill) for AI-powered image generation - [Konva.js](https://konvajs.org/) for canvas manipulation - [img-comparison-slider](https://www.npmjs.com/package/img-comparison-slider) for result visualization - [Custom CSS/JS](https://github.com/ed-parsadanyan/n8n-flux-fill-demo) for editor functionality 1. **Simple Editor Interface** - HTML page with an editor is served on the Webhook call - Adjustable brush selection tool - Provides several mock examples and allows uploading custom images - Basic prompt and FLUX model parameter controls 2. **Image Processing Pipeline** - Handles image and mask separately - Processes FLUX Fill API requests - Delivers results back to the editor 3. **Result Viewer** - Split-screen comparison of original and generated images - Interactive slider for before/after comparison - Options to save or continue editing - Support for multiple iteration cycles **Use Cases** ----------- This prototype is particularly useful for: - Testing AI-powered image editing concepts - Quick product visualization experiments - Exploring creative image variations - Demonstrating inpainting capabilities > **Pro tip**: Save masks for frequently edited areas to quickly generate variations with different prompts! The workflow can be extended to integrate with various data sources and can be customized for specific business needs.

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  1. Simulate Job Interviews with Google Gemini AI Voice Assistant

    This workflow facilitates realistic job interview simulations using Google Gemini AI, providing dynamic and personalized practice by maintaining conversation history for relevant follow-up questions.

    n8nFree

  2. Automate PDF Image Extraction & Analysis with GP-40 and Google Drive

    **Use Case** Manually extracting images from PDF files for analysis is often slow and inefficient. Many users resort to taking screenshots of each page, uploading them to an AI tool like OpenAI for image analysis, and then manually copying the insights into a document. This manual process is time-consuming and prone to errors. This workflow streamlines the entire process by automatically extracting images from a PDF, analyzing them using the GP-4o model, and saving the results in seconds—eliminating the need for manual effort. **What This Workflow Does** - Extracts all images from the uploaded PDF file automatically. The workflow scans each page of the PDF and identifies embedded images without manual intervention. - Uses the GP-4o model to analyze each extracted image. Each image is processed through GP-4o to generate descriptive insights, summaries, or context-specific analysis depending on the use case. - Saves the analysis results to a .txt file, including image URLs. The final output is a plain text file containing both the image URLs (e.g., hosted on cloud storage) and the corresponding GP-4o analysis, ready for further use or sharing. **Setup** 1. Set up your credentials when you first open the workflow. You'll need accounts for OpenAI, Convert API, and Google Drive. 2. Convert API does not rate-limit your API; sometimes, you may receive a 503 service unavailable error. Nevertheless, it doesn't mean that you cannot convert your file. It simply means that you should retry the conversion in a few seconds. 3. Upload a PDF with images to Google Drive. 4. Remove unnecessary parts and retrieve image-related information. 5. Integrate image and image analysis information together. 6. Analyze each image using the OPENAI GP-4o model. 7. Retrieve all image analysis content and image URL. 8. Integrate multiple image URLs and analysis content. 9. Output content to a .txt file. The template was created in n8n v1.83.2. **How to Customize** - Replace the manual trigger with a Google Drive trigger or other automation triggers. - Change the image analysis model (e.g., switch or fine-tune GP-4o). - Send the results to other platforms (e.g., Slack, Telegram, LINE, etc.) instead of saving to a .txt file.

    n8nFree

  3. Automate Travel Agency Assistant with OpenAI and Google Drive

    This workflow automates the creation and management of a custom OpenAI Assistant for a travel agency, utilizing Google Drive for document storage and retrieval.

    n8nFree

  4. Transcribe WhatsApp Audio Messages Using Whisper AI via Groq

    Automatically convert WhatsApp audio messages to text using Whisper AI for improved accessibility and communication efficiency.

    n8nFree

  5. Create a Dynamic Telegram AI Bot with LangChain and DALL-E Integration

    Develop a flexible Telegram bot that leverages LangChain nodes and DALL-E for advanced AI interactions and image generation.

    n8nFree

  6. Comprehensive LLM Usage Tracker & Cost Monitor with Node-Level Analytics

    # LLM Cost Monitor & Usage Tracker for n8n ## What This Workflow Does This workflow provides comprehensive monitoring and cost tracking for all LLM/AI agent usage across your n8n workflows. It extracts detailed token usage data from any workflow execution and calculates precise costs based on current model pricing. ### The Problem It Solves When running LLM nodes in n8n workflows, the token usage and intermediate data are not directly accessible within the same workflow. This monitoring workflow bridges that gap by: - Retrieving execution data using the execution ID - Extracting all LLM usage from any nested structure - Calculating costs with customizable pricing - Providing detailed analytics per node and model - **WARNING**: It works after the full execution of the workflow (i.e., you can't get this data before completion of all tasks in the workflow) ## ℹ️ Setup Instructions ### Prerequisites 1. **Experience Required**: Basic familiarity with n8n LLM nodes and AI agents 2. **Agent Configuration**: In your monitored workflows, go to agent settings and enable **Return Intermediate Steps** 3. For getting execution data, you need to set up the n8n API in your instance (also available on the free version) ### Installation Steps 1. Import this monitoring workflow into your n8n instance 2. Go to Settings >> select n8n API from the left bar >> define an API. Now you can add this as the credential for your Get an Execution node 3. Configure your model name mappings in the **Standardize Names** node 4. Update model pricing in the **Model Prices** node (prices per 1M tokens) 5. To monitor a workflow: - Add an **Execute Workflow** node at the end of your target workflow - Select this monitoring workflow - **Important**: Turn OFF Wait For Sub-Workflow Completion - Pass the execution ID as input ## ✒️ Customization ### When You See Errors If the workflow enters the error path, it means an undefined model was detected. Simply: 1. Add the model name to the **standardize_names_dict** 2. Add its pricing to the **model_price_dict** 3. Re-run the workflow ### Configurable Elements - **Model Name Mapping**: Standardize different model name variations (e.g., gpt-4-0613 → gpt-4) - **Pricing Dictionary**: Set costs per million tokens for input/output - **Extraction Depth**: Captures tokens from any nesting level automatically ## 📊 Output Data ### Per LLM Call - **Cost Breakdown**: Prompt, completion, and total costs in USD - **Token Metrics**: Prompt tokens, completion tokens, total tokens - **Performance**: Execution time, start time, finish reason - **Content Preview**: First 100 chars of input/output for debugging - **Model Parameters**: Temperature, max tokens, timeout, retry count - **Execution Context**: Workflow name, node name, execution status - **Flow Tracking**: Previous nodes chain ### Summary Statistics - Total executions and costs - Breakdown by model type - Breakdown by node - Average cost per call - Total execution time ## 🔑 Key Benefits - **No External Dependencies**: Everything runs within n8n - **Universal Compatibility**: Works with any workflow structure - **Automatic Detection**: Finds LLM usage regardless of nesting - **Real-time Monitoring**: Track costs as workflows execute - **Debugging Support**: Preview actual prompts and responses - **Scalable**: Handles multiple models and complex workflows ## ✨ Example Use Cases - **Cost Optimization**: Identify expensive nodes and optimize prompts - **Usage Analytics**: Track token consumption across teams/projects - **Budget Monitoring**: Set alerts based on cost thresholds - **Performance Analysis**: Find slow-running LLM calls - **Debugging**: Review actual inputs/outputs without logs - **Compliance**: Audit AI usage across your organization ## 🚀 Quick Start 1. Import workflow 2. Update model prices (if needed) 3. Add monitoring to any workflow with the Execute Workflow node 4. View detailed cost breakdowns instantly --- *Note: Prices are configured per million tokens. Default includes GPT-4, GPT-3.5, Claude, and other popular models. Add custom models as needed.*

    n8nFree

  7. Automate Domain Availability Checks with AI Chatbot Using WHMCS and Google Gemini

    This n8n workflow integrates Google Gemini AI with WHMCS to create a chatbot that automates domain availability checks, enhancing customer support for domain registrars and web hosting services.

    n8nFree

  8. Automate Website Scraping and AI Analysis with Apify and OpenRouter

    This workflow leverages Apify for web scraping and OpenRouter for AI-driven prompt execution, enabling automated data extraction and analysis from websites.

    n8nFree

  9. Automate AI-Driven Handbook Creation with Multi-Agent Orchestration and Human Review

    This n8n workflow automates the creation of Markdown-based handbooks using a multi-agent AI system with human oversight. It orchestrates AI agents for content generation, review, and synthesis, ensuring high-quality outputs through iterative refinement and human approval.

    n8nFree

  10. AI Voice Chat Using Webhook, Memory Manager, OpenAI, Google Gemini & ElevenLabs

    ## Who is this for? This workflow is designed for businesses or developers looking to integrate voice-based chat applications with dynamic responses and conversational memory. ## What problem does this solve? It automates AI-powered voice conversations, maintaining context between sessions and converting speech-to-text and text-to-speech. ## What this workflow does: The workflow receives audio input, transcribes it using OpenAI, and processes the conversation using Google Gemini Chat Model (you can use the OpenAI Chat Model). Responses are converted back to speech using ElevenLabs. ## Prerequisites: You'll need API keys for: * OpenAI (you can obtain it from the OpenAI website) * ElevenLabs (you can obtain it from their website) * Google Gemini (You can obtain it from `Google AI Studio`) ## Setup: * Configure your API keys * Ensure that the value `(voice_message)` in the `Path` parameter in the Webhook node is used as the name of the parameter that will contain the voice message you are sending via the HTTP Post request.

    n8nFree

  11. Automate AI-Enhanced Image Generation with FLUX Kontext and Google Integration

    This workflow automates the creation of AI-enhanced images using FLUX Kontext based on prompts from Google Sheets. The images are stored in Google Drive, and their URLs are updated back to the spreadsheet for easy access.

    n8nFree

  12. Automate Gmail Email Categorization and Labeling with GPT-4o Mini

    Effortlessly organize your existing Gmail inbox by categorizing and labeling emails using AI. This workflow processes unlabeled emails and applies appropriate labels based on content analysis.

    n8nFree

  13. Generate Random Strings from Predefined Characters

    Create random strings of specified length using characters from a predefined set, ideal for generating unique identifiers or passwords.

    MakeFree

  14. Dynamically Switch Between LLMs for AI Agents Using LangChain Code

    # Dynamically switch between LLMs for AI Agents using LangChain Code ## Purpose This example workflow demonstrates a way to connect multiple LLMs to a single AI Agent/LangChain Node and programmatically use one - or in this case loop through them. ## What it does This AI workflow takes in customer complaints and generates a response that is being validated before returned. If the answer was not satisfactory, the response will be generated again with a more capable model. ## How it works - A LangChain Code Node allows multiple LLMs to be connected to a single Basic LLM Chain. On every call, only one LLM is actually being connected to the Basic LLM Chain, which is determined by the index defined in a previous Node. - The AI output is later validated by a Sentiment Analysis Node. - If the result was not satisfactory, it loops back to the beginning and executes the same query with the next available LLM. - The loop ends either when the result passed the requirements or when all LLMs have been used. ## Setup - Clone the workflow and select the belonging credentials. You'll need an OpenAI Account, alternatively, you can swap the LLM nodes with ones from a different provider like Anthropic after the import. ## How to use **Beware that the order of the used LLMs is determined by the order they have been added to the workflow, not by the position on the canvas.** After cloning this workflow into your environment, open the chat and send this example message: > I really **love** waiting two weeks just to get a keyboard that doesn't even work. Great job. Any chance I could actually use the thing I paid for sometime this month? Most likely you will see that the first validation fails, causing it to loop back to the generation node and try again with the next available LLM. **Since AI responses are unpredictable, the results and number of tries will differ for each run.** ## Disclaimer Please note that this workflow can only run on self-hosted n8n instances, since it requires the LangChain Code Node.

    n8nFree

  15. Automate Competitor Monitoring and Content Ideation with GPT-4 and Gemini

    This workflow helps women creators and lifestyle brands effortlessly monitor competitor content and generate weekly content ideas using Firecrawl, OpenAI, and Gemini, with results stored in Google Sheets.

    n8nFree

  16. Automate YouTube SEO Content and Thumbnail Creation from Video Scripts

    Streamline your YouTube SEO process by automatically generating SEO content and thumbnails from video scripts using Google Sheets, OpenAI, and Runway.

    n8nFree

  17. Automate Comprehensive Research Report Generation and Delivery

    Streamline the creation of professional research reports using AI and multiple data sources, with automated delivery via Gmail or Telegram.

    n8nFree

  18. Automate LinkedIn Lead Generation and Outreach for Legal Professionals

    Streamline your outreach process by automatically finding and personalizing messages for solo lawyers and small law firm founders using LinkedIn data, Google Sheets, and AI tools.

    n8nFree

  19. Allow Users to Send a Sequence of Messages to an AI Agent in Telegram

    ### Use Case When creating chatbots that interface through applications such as **Telegram** and **WhatsApp**, users can often send multiple shorter messages in quick succession, in place of a single, longer message. This workflow accounts for this behavior. ### What it Does This workflow allows users to send several messages in quick succession, treating them as one coherent conversation instead of separate messages requiring individual responses. ### How it Works 1. When messages arrive, they are stored in a **Supabase PostgreSQL** table. 2. The system waits briefly to see if additional messages arrive. 3. If no new messages arrive within the waiting period, all queued messages are: - Combined and processed as a single conversation. - Responded to with one unified reply. - Deleted from the queue. ### Setup 1. Create a table in Supabase called **message_queue**. It needs to have the following columns: **user_id** (`uint8`), **message** (`text`), and **message_id** (`uint8`). 2. Add your **Telegram**, **Supabase**, **OpenAI**, and **PostgreSQL** credentials. 3. Activate the workflow and test by sending multiple messages to the Telegram bot in one go. 4. Wait ten seconds after which you will receive a single reply to all of your messages. ### How to Modify it to Your Needs - Change the value of **Wait Amount** in the **Wait 10 Seconds** node in order to modify the buffering window. - Add a **System Message** to the **AI Agent** to tailor it to your specific use case. - Replace the **OpenAI** sub-node to use a different language model.

    n8nFree

  20. AI-Driven Recipe Suggestions via WhatsApp Using Pantry Items

    Transform your pantry items into delicious recipes with AI-powered suggestions delivered through WhatsApp. Integrate Google Gemini AI and FatSecret API for personalized cooking assistance.

    n8nFree

  21. Deploy a Fully Functional Google Cloud Firestore MCP Server for AI Integration

    Set up a comprehensive MCP server to manage all Google Cloud Firestore operations seamlessly with AI agents. This workflow requires zero configuration and includes all seven operations pre-built for immediate use.

    n8nFree
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