by Yaron Been
Aihilums Sehatsanjha AI Generator Description None Overview This n8n workflow integrates with the Replicate API to use the aihilums/sehatsanjha model. This powerful AI model can generate high-quality other content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Optional Parameters cookie** (string, default: None): Cookie to be returned unchanged user_id** (string, default: ): Unique session identifier audio_file** (string, default: None): Audio file user_state** (string, default: None): User state end_session** (boolean, default: False): End the current recording new_session** (boolean, default: False): Start a new recording How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate other content Access the generated output from the final node API Reference Model: aihilums/sehatsanjha API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of other generation parameters
by Yaron Been
Description This workflow automatically generates comprehensive property market reports by scraping real estate listings and market data from multiple sources. It helps real estate professionals save time and provide data-driven insights to clients without manual research. Overview This workflow automatically generates property market reports by scraping real estate listings and market data. It uses Bright Data to access multiple real estate websites and compiles the data into comprehensive reports. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping real estate websites and property data without getting blocked. Spreadsheets/Databases:** For storing and analyzing property data. Document Generation:** For creating professional PDF reports. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Data Storage: Configure where you want to store the property data. Customize: Specify locations, property types, and report format. Use Cases Real Estate Agents:** Generate market reports for clients. Property Investors:** Track market trends in target areas. Market Analysts:** Automate data collection for property market analysis. Connect with Me Website:** https://www.nofluff.online YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #realestate #propertymarket #brightdata #marketreports #propertyanalysis #realestatedata #markettrends #propertyinvestment #n8nworkflow #workflow #nocode #realestateanalysis #propertyreports #realestateintelligence #marketresearch #propertyscraping #realestateautomation #investmentanalysis #propertytrends #datadriven #realestatetech #propertyinsights #marketanalysis #realestateinvesting
by Yaron Been
Description This workflow automatically monitors and tracks trending topics across multiple platforms and websites. It helps content creators and marketers stay ahead of the curve by identifying emerging trends before they go mainstream. Overview This workflow automatically monitors and tracks trending topics across multiple platforms and websites. It uses Bright Data to scrape trend data from social media, news sites, and other sources, then compiles the information into a structured format. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping trend data from various websites without getting blocked. Spreadsheets/Databases:** For storing and analyzing trend information. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Data Storage: Configure where you want to store the trend data. Customize: Specify which platforms to monitor and what topics to focus on. Use Cases Content Creators:** Stay on top of trending topics for content ideas. Marketers:** Identify emerging trends for timely campaigns. Researchers:** Track the evolution of topics and conversations over time. Connect with Me Website:** https://www.nofluff.online YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #trends #trendtracking #brightdata #contentmarketing #trendanalysis #trendalerts #markettrends #trendmonitoring #n8nworkflow #workflow #nocode #trendresearch #emergingtrends #socialmediatrends #trendscraping #trenddata #contentideas #digitalmarketing #marketresearch #trendforecasting #trendspotting #dataanalysis #marketintelligence #trendautomation
by Yaron Been
Fire Part Crafter Image Generator Description PartCrafter is a structured 3D mesh generation model that creates multiple parts and objects from a single RGB image. Overview This n8n workflow integrates with the Replicate API to use the fire/part-crafter model. This powerful AI model can generate high-quality image content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters image** (string): Input image for 3D mesh generation Optional Parameters seed** (integer, default: 0): Random seed for reproducibility. Use 0 for random seed num_parts** (integer, default: 16): Number of parts to generate num_tokens** (string, default: 2048): Number of tokens for generation guidance_scale** (number, default: 7): Guidance scale for generation remove_background** (boolean, default: False): Remove background from input image use_flash_decoder** (boolean, default: False): Use flash decoder for faster inference (Tempermental?) num_inference_steps** (integer, default: 50): Number of inference steps How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate image content Access the generated output from the final node API Reference Model: fire/part-crafter API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of image generation parameters
by Yaron Been
Google Veo 3 Video Generator Description Sound on: Google’s flagship Veo 3 text to video model, with audio Overview This n8n workflow integrates with the Replicate API to use the google/veo-3 model. This powerful AI model can generate high-quality video content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Text prompt for video generation Optional Parameters seed** (integer, default: None): Random seed. Omit for random generations resolution** (string, default: 720p): Resolution of the generated video negative_prompt** (string, default: None): Description of what to discourage in the generated video How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate video content Access the generated output from the final node API Reference Model: google/veo-3 API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of video generation parameters
by David w/ SimpleGrow
Receive Webhook Notification The workflow starts when a webhook receives a POST request from Whapi, notifying that a new participant has joined a WhatsApp group. Filter the Event The workflow checks two conditions: The event is for the correct WhatsApp group (matching the specific group ID). The action type is "add" (meaning a user was added to the group). Send Welcome Message If both conditions are met, the workflow sends a personalized welcome message to the new participant via Whapi. The message explains the group rules and how the user can earn points and participate in weekly raffles. Create Airtable Record After sending the welcome message, the workflow creates a new record in the Airtable database for the new participant. The record includes: The participant’s WhatsApp ID An initial engagement count of 100 points The date of the last interaction (set to today) Result Every new group member is automatically welcomed and registered in your engagement database with starter points, ready to participate in your group’s activities and rewards. This workflow ensures new users are greeted, informed, and instantly included in your engagement tracking system.
by Yaron Been
Fire Flux Image Generator Description The image generation model tailored for local development and personal use Overview This n8n workflow integrates with the Replicate API to use the fire/flux model. This powerful AI model can generate high-quality image content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Prompt for generated image Optional Parameters seed** (integer, default: 0): Random seed. Set for reproducible generation go_fast** (boolean, default: True): Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16 megapixels** (string, default: 1): Approximate number of megapixels for generated image num_outputs** (integer, default: 1): Number of outputs to generate aspect_ratio** (string, default: 2:1): Aspect ratio for the generated image output_format** (string, default: png): Format of the output images output_quality** (integer, default: 80): Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs num_inference_steps** (integer, default: 4): Number of denoising steps. 4 is recommended, and lower number of steps produce lower quality outputs, faster. disable_safety_checker** (boolean, default: False): Disable safety checker for generated images. How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate image content Access the generated output from the final node API Reference Model: fire/flux API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of image generation parameters
by Yaron Been
Ibm Granite Granite Speech 3.3 8b Text Generator 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). Overview This n8n workflow integrates with the Replicate API to use the ibm-granite/granite-speech-3.3-8b model. This powerful AI model can generate high-quality text content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Optional Parameters seed** (integer, default: None): Random seed. Leave blank to randomize the seed. audio** (array, default: None): Audio inputs for the model. top_k** (integer, default: 50): The number of highest probability tokens to consider for generating the output. If > 0, only keep the top k tokens with highest probability (top-k filtering). top_p** (number, default: 0.9): A probability threshold for generating the output. If < 1.0, only keep the top tokens with cumulative probability >= top_p (nucleus filtering). Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751). prompt** (string, default: ): User prompt to send to the model. max_tokens** (integer, default: 512): The maximum number of tokens the model should generate as output. min_tokens** (integer, default: 0): The minimum number of tokens the model should generate as output. temperature** (number, default: 0.6): The value used to modulate the next token probabilities. chat_template** (string, default: None): A template to format the prompt with. If not provided, the default prompt template will be used. system_prompt** (string, default: None): System prompt to send to the model.The chat template provides a good default. How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate text content Access the generated output from the final node API Reference Model: ibm-granite/granite-speech-3.3-8b API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of text generation parameters
by Yaron Been
Bytedance Seededit 3.0 Image Generator Description Text-guided image editing model that preserves original details while making targeted modifications like lighting changes, object removal, and style conversion Overview This n8n workflow integrates with the Replicate API to use the bytedance/seededit-3.0 model. This powerful AI model can generate high-quality image content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Text prompt for image generation image** (string): Input image to edit Optional Parameters seed** (integer, default: None): Random seed. Set for reproducible generation guidance_scale** (number, default: 5.5): Prompt adherence. Higher = more literal. How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate image content Access the generated output from the final node API Reference Model: bytedance/seededit-3.0 API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of image generation parameters
by n8n Team
This workflow demonstrates how to export SQL to XML and present the data nicely formatted using an XSL Template. The upper part of the workflow starts with a webhook. Then it gets several random records from the SQL table and converts them into an XML string. Then a final XML file is created that contains a link to the XML Stylesheet file. The lower part of the workflow contains a helper Webhook that reads an XSL Template from the GitHub gist and serves it back via the Respond to Webhook node. This is required to comply with the CORS rules of modern browsers. These rules dictate that both XML data and a stylesheet file should come from the same domain.
by Eduard
This workflow demonstrates how easy it is to export SQL query to Excel automatically! Before running the workflow please make sure you have access to a remote SQL server (MS SQL, MySQL, PostgreSQL etc.) with a sample table: Date,Band,ConcertName,Country,City,Location,LocationAddress, 2023-05-28,Ozzy Osbourne,No More Tours 2 - Special Guest: Judas Priest,Germany,Berlin,Mercedes-Benz Arena Berlin,"Mercedes-Platz 1, 10243 Berlin-Friedrichshain", 2023-05-08,Elton John,Farewell Yellow Brick Road Tour 2023,Germany,Berlin,Mercedes-Benz Arena Berlin,"Mercedes-Platz 1, 10243 Berlin-Friedrichshain", 2023-05-26,Hans Zimmer Live,Europe Tour 2023,Germany,Berlin,Mercedes-Benz Arena Berlin,"Mercedes-Platz 1, 10243 Berlin-Friedrichshain", 2023-07-07,Depeche Mode,Memento Mori World Tour 2023,Germany,Berlin,Olympiastadion Berlin,"Olympischer Platz 3, 14053 Berlin-Charlottenburg", The detailed process is explained in the tutorial https://blog.n8n.io/export-sql-to-excel
by Tom
This workflow parses content from a website (for this example, Baserow's release page) and creates an RSS feed based on the extracted data. Prerequisites Some familiarity with HTML and CSS selectors Nodes Webhook node triggers the workflow when new content (a new Baserow release) is published on a website. Set nodes set the required URLs and links for the RSS feed. HTTP Request node fetches data from a specified website page. HTML Extract nodes extract the posts and their fields (such as date, title, description, and link) from the website. Item Lists node iterates over each post on the page. Date & Time node converts the date of the post to a different format. Function Item node creates RSS items for each post. Function node creates the response code for the RSS feed. Respond to Webhook node returns the RSS feed in response to the Webhook node. The result of this workflow would look like this: