Workflow Templates

This workflow provides automated access to the Ibm Granite Granite Speech 3.3 8B AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for text generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete text generation process using the Ibm Granite Granite Speech 3.3 8B model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: Granite-speech-3.3-8b is a compact and efficient speech-language model, specifically designed for automatic speech recognition (ASR) and automatic speech translation (AST). Key Capabilities Advanced text generation and processing** Natural language understanding and generation** Intelligent text manipulation and analysis** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Ibm Granite/granite-speech-3.3-8b AI model Ibm Granite Granite Speech 3.3 8B**: The core AI model for text generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Text Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Content Writing**: Generate articles, blogs, and marketing copy Code Generation**: Assist with programming and code documentation Text Analysis**: Process and analyze large volumes of text data Automated Communication**: Generate responses and communication templates Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #textgeneration #nlp #aiwriting #textai #contentgeneration #aitext #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation

This workflow provides automated access to the Lucataco Seed X Ppo AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for text generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete text generation process using the Lucataco Seed X Ppo model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: Seed-X-PPO-7B by ByteDance-Seed, a powerful series of open-source multilingual translation language models Key Capabilities Advanced text generation and processing** Natural language understanding and generation** Intelligent text manipulation and analysis** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Lucataco/seed-x-ppo AI model Lucataco Seed X Ppo**: The core AI model for text generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Text Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Content Writing**: Generate articles, blogs, and marketing copy Code Generation**: Assist with programming and code documentation Text Analysis**: Process and analyze large volumes of text data Automated Communication**: Generate responses and communication templates Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #textgeneration #nlp #aiwriting #textai #contentgeneration #aitext #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation

This workflow provides automated access to the Zsxkib Canary Qwen 2.5B AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for text generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete text generation process using the Zsxkib Canary Qwen 2.5B model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: 🎤The best open-source speech-to-text model as of Jul 2025, transcribing audio with record 5.63% WER and enabling AI tasks like summarization directly from speech✨ Key Capabilities Advanced text generation and processing** Natural language understanding and generation** Intelligent text manipulation and analysis** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Zsxkib/canary-qwen-2.5b AI model Zsxkib Canary Qwen 2.5B**: The core AI model for text generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Text Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Content Writing**: Generate articles, blogs, and marketing copy Code Generation**: Assist with programming and code documentation Text Analysis**: Process and analyze large volumes of text data Automated Communication**: Generate responses and communication templates Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #textgeneration #nlp #aiwriting #textai #contentgeneration #aitext #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation

LangChain is a framework for building AI functionality that users large language models. By leveraging the functionality of LangChain, you can write even more powerful workflows. This workflow shows how you can write LangChain code within n8n, including importing LangChain modules. The workflow itself produces a summary of a YouTube video, when given the video's ID. Note that to use this template, you need to be on n8n version 1.19.4 or later.

This n8n template showcases the new HTTP tool released in version 1.47.0. Overall, the tool helps simplify AI Agent workflows where custom sub-workflows were performing the same simple http requests. Comparisons 1. AI agent that can scrape webpages Remake of https://n8n.io/workflows/2006-ai-agent-that-can-scrape-webpages/ Changes: Replaces Execute Workflow Tool and Subworkflow Replaces Response Formatting 2. Allow your AI to call an API to fetch data Remake of https://n8n.io/workflows/2094-allow-your-ai-to-call-an-api-to-fetch-data/ Changes: Replaces Execute Workflow Tool and Subworkflow Replaces Manual Query Params Definitions Replaces Response Formatting

Modern AI systems are powerful but pose privacy risks when handling sensitive data. Organizations need AI capabilities while ensuring: ✅ Sensitive data never leaves secure environments ✅ Compliance with regulations (GDPR, HIPAA, PCI, SOX) ✅ Real-time decision making about data sensitivity ✅ Comprehensive audit trails for regulatory review The Concept: Intelligent Data Classification + Smart Routing The goal of this concept is to build the foundations of the safe and compliant use of LLMs in Agentic workflows by automatically detecting sensitive data, applying sanitization rules, and intelligently routing requests through secure processing channels. This workflow will analyze the user's chat or webhook input and attempt to detect PII using the Enhanced PII Pattern Detector. If detected, the workflow will process that input via a series of Compliance, Auditing, and Security steps which log and sanitizes the request prior to any LLM being pinged. Why Multi-Tier Routing? Traditional systems use binary decisions (sensitive/not sensitive). Our 3-tier approach provides: ✅ Granular Security: Critical PII gets maximum protection ✅ Performance Optimization: Clean data gets full cloud capabilities ✅ Cost Efficiency: Expensive local processing only when needed ✅ User Experience: Maintains conversational flow across security levels Why Context-Aware Detection? Regex patterns alone miss contextual sensitivity. Our approach: ✅ Catches Intent: "Bank account" discussion is sensitive even without account numbers ✅ Reduces False Negatives: Medical discussions stay secure even without explicit medical IDs ✅ Proactive Protection: Identifies sensitive contexts before PII is shared ✅ Compliance Alignment: Matches how regulations actually define sensitive data Why Risk Scoring vs Binary Classification? Binary PII detection creates artificial boundaries. Risk scoring provides: ✅ Nuanced Decisions: Multiple low-risk patterns might aggregate to high risk ✅ Adaptive Thresholds: Organizations can adjust sensitivity based on their needs ✅ Better UX: Users aren't unnecessarily restricted for low-risk scenarios ✅ Audit Transparency: Clear reasoning for every routing decision Why Comprehensive Monitoring? Privacy systems require trust and verification: ✅ Compliance Proof: Audit trails demonstrate regulatory compliance ✅ Performance Optimization: Identify bottlenecks and improve efficiency ✅ Security Validation: Ensure no sensitive data leakage occurs ✅ Operational Insights: Understand usage patterns and system health How to Install: All that you will need for this workflow are credentials for your LLM providers such as Ollama, OpenRouter, OpenAI, Anthropic, etc. This workflow is customizable and allows the user to define the best LLM and storage/memory solutions for their specific use case.

Adobe developer API Did you know that Adobe provides an API to perform all sort of manipulation on PDF files : Split PDF, Combine PDF OCR Insert page, delete page, replace page, reorder page Content extraction (text content, tables, pictures) ... The free tier allows up to 500 PDF operation / month. As it comes directly from Adobe, it works often better than other alternatives. Adobe documentation: https://developer.adobe.com/document-services/docs/overview/pdf-services-api/howtos/ https://developer.adobe.com/document-services/docs/overview/pdf-extract-api/gettingstarted/ What does this workflow do The API is a bit painful to use. To perform a transformation on a PDF it requires to Authenticate and get a temporal token Register a new asset (file) Upload you PDF to the registered asset Perform a query according to the transformation requested Wait for the query to be proccessed by Adobe backend Download the result This workflow is a generic wrapper to perform all these steps for any transformation endpoint. I usually use it from other workflow with an Execute Workflow node. Examples are given in the workflow. Example use case This service is useful for example to clean PDF data for an AI / RAG system. My favorite use-case is to extract table as images and forward images to an AI for image recognition / description which is often more accuarate than feedind raw tabular data to a LLM.

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.

This is a workflow where a support channel on Telegram is being used to gather customer feedback. Depending on certain keywords in the customer's message, this workflow creates a ticket with a tag in your Freshdesk instance. The customer is then sent a message on Telegram and an item is created on Monday.com for tracking.

This workflow takes a text file as input. It pulls the information from the text file and used it as a parameter to execute a command for each text line. This workflow references a file /home/n8n/filelist.txt in the Read Binary File node which will need to be changed to work properly. You can also edit the Execute Command node to modify what happens for each of these lines of text. Note: This workflow requires the Execute Command node which is only available on the on-premise version of n8n.

At the end, add the service you need, for example Telegram ++You can only see the result when you run workflow.++ *Based on these answers: Latest RSS Feed -> Rocket.Chat for get only new post Rss to Twitter with Image for get image*

This n8n template demonstrates how to use AI to generate custom images from scratch - fully automated, prompt-driven, and ready to deploy at scale. Use cases are many: You can use it for marketing visuals, character art, digital posters, storyboards, or even daily image generation for your personal purposes. How It Works The flow is triggered by a chat message in N8N or via Telegram. The default image size is 1080 x 1920 pixels. To use a different size, update the values in the “Fields - Set Values” node before triggering the workflow. The input is parsed into a clean, structured prompt using a multi-step transformation process. Our AI Agent sends the final prompt to Google Gemini’s image model for generation (you can also integrate with OpenAI or other chat models). The raw image data created by the AI Agent will be run through a number of codes to make sure it's feasible for your preview if needed and downloading. Then, we use an HTTP node to fetch the result so you can preview the image. You can send it back to the chat message in N8N or Telegram, or save it locally to your disk. How To Use Download the workflow package. Import the package into your N8N interface. Set up the credentials in the following nodes for tool access and usability: "Telegram Trigger"; "AI Agent - Create Image From Prompt"; "Telegram Response" or "Save Image To Disk" (based on your wish). Activate the "Telegram Response" OR "Save Image To Disk" node to specify where you want to save your image later. Open the chat interface (via N8N or Telegram). Type your image prompt or detailed descriptions and send. Wait for the process to run and finish in a few seconds. Check the result in your desired saving location. Requirements Google Gemini account with image generation access. Telegram bot access and chat setup (optional). Connection to local storage (optional). How To Customize We’re setting the default image size to 1080 x 1920 pixels and the default image model to "flux". You can customize both of these values in the “Fields – Set Values” node. Supported image model options include: "flux", "kontext", "turbo", and "gptimage". In the “AI Agent – Create Image From Prompt” node, you can also change the AI chat model. By default, it uses Google Gemini, but you can easily replace it with OpenAI ChatGPT, Microsoft AI Copilot, or any other compatible provider. Need Help? Join our community on different platforms for support, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle