HTTP Request workflows
458 results — all source-linked n8n references
Complete business WhatsApp AI-Powered RAG Chatbot using OpenAI
The provided workflow in n8n is designed to create a Business WhatsApp AI RAG (Retrieval-Augmented Generation) Chatbot. How it works: Webhook Setup: The workflow begins by setting up webhooks for verification and response. The Verify webhook receives GET requests and sends back a verification code, while the Respond webhook handles incoming POST requests from Meta regarding WhatsApp messages. Message Handling: Once a message is received, the workflow checks if the incoming JSON contains a user message. If it does, the message is processed further; otherwise, a generic response is sent. AI Agent Interaction: The user's message is passed to the AI Agent node, which uses a conversational agent with a predefined system message tailored for an electronics store. This ensures that the AI provides accurate and professional responses based on the knowledge base. Knowledge Base Utilization: The AI Agent references a knowledge base stored in Qdrant, a vector database. Documents from Google Drive are downloaded, vectorized using OpenAI embeddings, and stored in Qdrant for retrieval during conversations. Response Generation: The AI Agent generates a response using the OpenAI chat model (gpt-4o
WSpot Workplace Discrimination Patterns with AI
How It Works: • Scrapes company review data from Glassdoor using ScrapingBee. • Extracts demographic-based ratings using AI-powered text analysis. • Calculates workplace disparities with statistical measures like z-scores, effect sizes, and p-values. • Generates visualizations (scatter plots, bar charts) to highlight patterns of discrimination or bias. Example Visualizations: Set Up Steps: Estimated time: ~20 minutes. • Replace ScrapingBee and OpenAI credentials with your own. • Input the company name you want to analyze (best results with large U.S.-based organizations). • Run the workflow and review the AI-generated insights and visual reports. This workflow empowers users to identify potential workplace discrimination trends, helping advocate for greater equity and accountability. Additional Credit: Wes Medford For algorithms and inspiration
WSocial Media Analysis and Automated Email Generation
Social Media Analysis and Automated Email Generation > by Thomas Vie [email protected] Who is this for? This template is ideal for marketers, lead generation specialists, and business professionals seeking to analyze social media profiles of potential leads and automate personalized email outreach efficiently. What problem is this workflow solving? Manually analyzing social media profiles and crafting personalized emails can be time-consuming and prone to errors. This workflow streamlines the process by integrating social media APIs with AI to generate tailored communication, saving time and increasing outreach effectiveness. What this workflow does: Google Sheets Integration: Start with a Google Sheet containing lead information such as LinkedIn URL, Twitter handle, name, and email. Social Media Data Extraction: Automatically fetch profile and activity data from Twitter and LinkedIn using RapidAPI integrations. AI-Powered Content Generation: Use OpenAI's Chat Model to analyze the extracted data and generate personalized email subject lines and cover letters. Automated Email Dispatch: Send the generated email directly to the lead, with a copy sent to yourself for tracking purpos
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AI-Generated Summary Block for WordPress Posts
What is this workflow? This n8n template automates the process of adding an AI-generated summary at the top of your WordPress posts. It retrieves, processes, and updates your posts dynamically, ensuring efficiency and flexibility without relying on a heavy WordPress plugin. Example of AI Summary Section How It Works Triggers → Runs on a scheduled interval or via a webhook when a new post is published. Retrieves posts → Fetches content from WordPress and converts HTML to Markdown for AI processing. AI Summary Generation → Uses OpenAI to create a concise summary. Post Update → Inserts the summary at the top of the post while keeping the original excerpt intact. Data Logging & Notifications → Saves processed posts to Google Sheets and notifies a Slack channel. Why use this workflow? ✅ No need for a WordPress plugin → Keeps your site lightweight. ✅ Highly flexible → Easily connect with Google Sheets, Slack, or other services. ✅ Customizable → Adapt AI prompts, formatting, and integrations to your needs. ✅ Smart filtering → Ensures posts are not reprocessed unnecessarily. 💡 Check the detailed sticky notes for setup instructions and customization options!
BCWAuto-Tag Blog Posts in WordPress with AI
How it works: This workflow automates tagging for WordPress posts using AI: Fetch blog post content and metadata. Generate contextually relevant tags using AI. Verify existing tags in WordPress and create new ones if necessary. Automatically update posts with accurate and optimized tags. Set up steps: Estimated time: ~15 minutes. Configure the workflow with your WordPress API credentials. Connect your content source (e.g., RSS feed or manual input). Adjust tag formatting preferences in the workflow settings. Run the workflow to ensure proper tag creation and assignment. This workflow is perfect for marketers and content managers looking to streamline their content categorization and improve SEO efficiency.
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Automate Content Generator for WordPress with DeepSeek R1
This workflow is designed to generate SEO-friendly content with DeepSeek R1 (or V3), publish it on WordPress, and update a Google Sheets document with the details of the created post. Below is a detailed analysis of what each node in the workflow does: How It Works Triggering the Workflow: The workflow starts with a Manual Trigger node, which is activated when the user clicks "Test workflow" in the n8n interface. Fetching Data: The Get Ideas node retrieves data from a Google Sheets document. It reads a specific sheet and filters the data based on the "ID POST" column, returning the first matching row. Setting the Prompt: The Set your prompt node extracts the PROMPT field from the Google Sheets data and assigns it to a variable for use in subsequent steps. Generating Content: The Generate article node uses an AI model (DeepSeek) to create an SEO-friendly article based on the prompt. The article includes an introduction, 2-3 chapters, and a conclusion, formatted in HTML. The Generate title node uses the same AI model to generate a concise, SEO-optimized title for the article. Publishing on WordPress: The Create post on WordPress node creates a new draft post on WordPress using the ge
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Analyse papers from Hugging Face with AI and store them in Notion
This workflow automates the process of retrieving Hugging Face paper summaries, analyzing them with OpenAI, and storing the results in Notion. Here’s a breakdown of how it works: ⏰ Scheduled Trigger: The flow is set to run automatically at 8 AM on weekdays. 📄 Fetching Paper Data: It fetches Hugging Face paper summaries using their API. 🔍 Data Check: Before processing, the workflow checks if the paper already exists in Notion to avoid duplicates. 🤖 Content Analysis with OpenAI: If the paper is new, it extracts the summary and uses OpenAI to analyze the content. 📥 Store Results in Notion: After analysis, the summarized data is saved in Notion for easy reference. ⚙️ Set Up Steps for Automation Follow these steps to set up this automated workflow with Hugging Face, OpenAI, and Notion integration: 🔑 Obtain API Tokens: You’ll need the Notion and OpenAI API tokens to authenticate and connect these services with n8n. 🔗 Integration in n8n: Link Hugging Face, OpenAI, and Notion by configuring the appropriate nodes in n8n. 🔧 Configure Workflow Logic: Set up a cron trigger for automatic execution at 8 AM on weekdays. Use an HTTP request node to fetch Hugging Face paper data. Add logic t
WGenerate Instagram Content from Top Trends with AI Image Generation
How it works This automated workflow discovers trending Instagram posts and creates similar AI-generated content. Here's the high-level process: 1. Content Discovery & Analysis Scrapes trending posts from specific hashtags Analyzes visual elements using AI Filters out videos and duplicates 2. AI Content Generation Creates unique images based on trending content Generates engaging captions with relevant hashtags Maintains brand consistency while being original 3. Automated Publishing Posts content directly to Instagram Monitors publication status Sends notifications via Telegram Set up steps Setting up this workflow takes approximately 15-20 minutes: 1. API Configuration (7-10 minutes) Instagram Business Account setup Telegram Bot creation API key generation (OpenAI, Replicate, Rapid Api) 2. Database Setup (3-5 minutes) Create required database table Configure PostgreSQL credentials 3. Workflow Configuration (5-7 minutes) Set scheduling preferences Configure notification settings Test connection and permissions Detailed technical specifications and configurations are available in sticky notes within the workflow.
Zoom AI Meeting Assistant creates mail summary, ClickUp tasks and follow-up call
Update 19-04-2025 Change from OpenAI to Claude 3.7 Sonnet module Adding the Think Tool The update enables significantly better results to be achieved. This is particularly noticeable during longer meetings! What this workflow does This workflow retrieves the Zoom meeting data from the last 24 hours. The transcript of the last meeting is then retrieved, processed, a summary is created using AI and sent to all participants by email. AI is then used to create tasks and follow-up appointments based on the content of the meeting. Important: You need a Zoom Workspace Pro account and must have activated Cloud Recording/Transcripts! This workflow has the following sequence: manual trigger (Can be replaced by a scheduled trigger or a webhook) retrieval of of Zoom meeting data filter the events of the last 24 hours retrieval of transcripts and extract of the text creating a meeting summary, format to html and send per mail create tasks and follow-up call (if discussed in the meeting) in ClickUp/Outlook (can be replaced by Gmail, Airtable, and so forth) via sub workflow Requirements: Zoom Workspace (via API and HTTP Request): Documentation Microsoft Outlook: Documentation ClickUp: Documentati
WAI-Powered Information Monitoring with OpenAI, Google Sheets, Jina AI and Slack
Check Legal Regulations: This workflow involves scraping, so ensure you comply with the legal regulations in your country before getting started. Better safe than sorry! 📌 Purpose This workflow enables automated and AI-driven topic monitoring, delivering concise article summaries directly to a Slack channel in a structured and easy-to-read format. It allows users to stay informed on specific topics of interest effortlessly, without manually checking multiple sources, ensuring a time-efficient and focused monitoring experience. To get started, copy the Google Sheets template required for this workflow from here. 🎯 Target Audience This workflow is designed for: Industry professionals** looking to track key developments in their field. Research teams** who need up-to-date insights on specific topics. Companies** aiming to keep their teams informed with relevant content. ⚙️ How It Works Trigger: A Scheduler initiates the workflow at regular intervals (default: every hour). Data Retrieval: RSS feeds are fetched using the RSS Read node. Previously monitored articles are checked in Google Sheets to avoid duplicates. Content Processing: The article relevance is assessed using OpenAI (GPT
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Scrape Trustpilot Reviews with DeepSeek, Analyze Sentiment with OpenAI
Workflow Overview This workflow automates the process of scraping Trustpilot reviews, extracting key details, analyzing sentiment, and saving the results to Google Sheets. It uses OpenAI for sentiment analysis and HTML parsing for review extraction. How It Works 1. Scrape Trustpilot Reviews HTTP Request**: Fetches review pages from Trustpilot (https://it.trustpilot.com/review/{{company_id}}). Paginates through pages (up to max_page limit). HTML Parsing**: Extracts review URLs using CSS selectors Splits the URLs into individual review links. 2. Extract Review Details Information Extractor**: Uses DeepSeek to extract structured data from the review: Author: Name of the reviewer. Rating: Numeric rating (1-5). Date: Review date in YYYY-MM-DD format. Title: Review title. Text: Full review text. Total Reviews: Number of reviews by the user. Country: Reviewer’s country (2-letter code). 3. Sentiment Analysis Sentiment Analysis Node**: Uses OpenAI to classify the review text as Positive, Neutral, or Negative. Example output: { "category": "Positive", "confidence": 0.95 } 4. Save to Google Sheets Google Sheets Node**: Appends or updates the extracted data to a Google Sheet Set Up Steps 1. Co
CWCreate a Branded AI-Powered Website Chatbot
Create a Branded AI Website Chatbot Engage website visitors with an intelligent chat widget powered by OpenAI. This template includes: 💬 Natural conversation handling 📅 Microsoft Outlook calendar integration 📝 Lead capture and information gathering 🔄 Human handoff capabilities Simply add a JavaScript snippet to your website and configure the workflow to match your needs. Follow our detailed setup guide to get started in minutes. > Note: Widget includes a "Powered By" affiliate link
DPersonal Shopper Chatbot for WooCommerce with RAG using Google Drive and openAI
This workflow combines OpenAI, Retrieval-Augmented Generation (RAG), and WooCommerce to create an intelligent personal shopping assistant. It handles two scenarios: Product Search: Extracts user intent (keywords, price ranges, SKUs) and fetches matching products from WooCommerce. General Inquiries: Answers store-related questions (e.g., opening hours, policies) using RAG and documents stored in Google Drive. How It Works 1. Chat Interaction & Intent Detection Chat Trigger**: Starts when a user sends a message ("When chat message received"). Information Extractor**: Uses OpenAI to analyze the message and determine if the user is searching for a product or asking a general question. Extracts: search (true/false). keyword, priceRange, SKU, category (if product-related). Example: { "search": true, "keyword": "red handbags", "priceRange": { "min": 50, "max": 100 }, "SKU": "BAG123", "category": "women's accessories" } 2. Product Search (WooCommerce Integration) AI Agent**: If search: true, routes the request to the personal_shopper tool. WooCommerce Node: Queries the WooCommerce store using extracted parameters (keyword, priceRange, SKU). Filters products in stock (stockStatus: "instock"
CAI marketing report (Google Analytics & Ads, Meta Ads), sent via email/Telegram
What this workflow does This workflow retrieves Online Marketing data (Google Analytics for several domains, Google Ads, Meta Ads) from the last 7 days and the same period in the previous year. The data is then prepared by AI as a table, analyzed and provided with a small summary. The summary is then sent by email to a desired address and, shortened and summarized again, sent to a Telegram account. This workflow has the following sequence: time trigger (e.g. every Monday at 7 a.m.) retrieval of Online Marketing data from the last 7 days (via sub workflows) assignment and summary of the data retrieval of Online Marketing data from the same time period of the previous year allocation and summary of the data preparation in tabular form and brief analysis by AI. sending the report as an email preparation in short form by AI for Telegram (optional) sending as Telegram message. Requirements The following accesses are required for the workflow: Google Analytics (via Google Analytics API): Documentation Google Ads (via HTTP Request -> Google Ads API):Documentation Meta Ads (via Facebook Graph API): Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) SMTP access da
WAutomated End-to-End Fine-Tuning of OpenAI Models with Google Drive Integration
1. How it Works This n8n workflow automates fine-tuning OpenAI models through these key steps: Manual Trigger**: Starts with the "When clicking ‘Test workflow’" event to initiate the process. Downloads a .jsonl file from Google Drive Upload to OpenAI**: Uploads the .jsonl file to OpenAI via the "Upload File" node (with purpose "fine-tune"). Create Fine-tuning Job**: Sends a POST request to the endpoint https://api.openai.com/v1/fine_tuning/jobs with: { "training_file": "{{ $json.id }}", "model": "gpt-4o-mini-2024-07-18" } OpenAI automatically starts training the model based on the provided file. Interaction with the Trained Model**: An "AI Agent" uses the custom model (e.g., ft:gpt-4o-mini-2024-07-18:n3w-italia::XXXX7B) to respond to chat messages. 2. Set up Steps To configure the workflow: Prepare the Training File: Create a .jsonl file following the specified syntax (e.g., travel assistant Q/A examples). Upload it to Google Drive and update the ID in the "Google Drive" node. Configure Credentials: Google Drive: Connect an account via OAuth2 (googleDriveOAuth2Api). OpenAI: Add your API key in the "OpenAI Chat Model" and "Upload File" nodes. Customize the Model: In the "OpenAI Chat
AI Data Extraction with Dynamic Prompts and Baserow
This n8n template introduces the Dynamic Prompts AI workflow pattern which are incredible for certain types of data extraction tasks where attributes are unknown or need to remain flexible. The general idea behind this pattern is that the prompts for requested attributes to be extracted live outside the template and so can be changed at any time - without needing to edit the template. This seriously cuts down on maintainance requirements and is reusable for any number of tables at little cost. Check out the n8n Studio Episode here: https://www.youtube.com/watch?v=_fNAD1u8BZw Community post here: https://community.n8n.io/t/dynamic-prompts-with-n8n-baserow-and-airtable/72052 Looking for the Airtable Version? https://n8n.io/workflows/2771-ai-data-extraction-with-dynamic-prompts-and-airtable/ How it works Given we have an "input" field for context and a number of fields for the data we want to extract, this template will run in the background to react to any changes to either the "input" or fields and automatically update the rows accordingly. The key is that Baserow fields have a special property called the "field description". In this pattern, we use this property to allow the user t
🐋DeepSeek V3 Chat & R1 Reasoning Quick Start
This n8n workflow demonstrates multiple ways to harness DeepSeek's AI models in your automation pipeline! 🌟 Core Features Multiple Integration Methods 🔌 Local deployment using Ollama for DeepSeek-R1 Direct API integration with DeepSeek Chat V3 Conversational agent with memory buffer HTTP request implementation with both raw and JSON formats Model Options 🧠 DeepSeek Chat V3 for general conversation DeepSeek-R1 for advanced reasoning Memory-enabled agent for persistent context Quick Setup 🛠️ API Configuration Base URL: https://api.deepseek.com Get your API key from platform.deepseek.com/api_keys Local Setup 💻 Install Ollama for local deployment Set up DeepSeek-R1 via Ollama Configure local credentials in n8n Implementation Details 🔧 Conversational Agent Window Buffer Memory for context Customizable system messages Built-in error handling with retries API Endpoints 🌐 Chat completions for V3 and R1 models OpenAI API format compatibles
BCWAI Data Extraction with Dynamic Prompts and Airtable
This n8n template introduces the Dynamic Prompts Ai workflow pattern which are incredible for certain types of data extraction tasks where attributes are unknown or need to remain flexible. The general idea behind this pattern is that the prompts for requested attributes to be extracted live outside the template and so can be changed at any time - without needing to edit the template. This seriously cuts down on maintainance requirements and is reusable for any number of tables at little cost. Check out the video demo I did for n8n Studio here: https://www.youtube.com/watch?v=_fNAD1u8BZw Check out the example Airtable here: https://airtable.com/appAyH3GCBJ56cfXl/shrXzR1Tj99kuQbyL Looking for the Baserow Version? https://n8n.io/workflows/2780-ai-data-extraction-with-dynamic-prompts-and-baserow/ How it works Given we have an "input" field for context and a number of fields for the data we want to extract, this template will run in the background to react to any changes to either the "input" or fields and automatically update the rows accordingly. The key is that Airtable fields have a special property called the "field description". In this pattern, we use this property to allow the
🤖🔍 The Ultimate Free AI-Powered Researcher with Tavily Web Search & Extract
🔍 This n8n workflow integrates Tavily's search and extract APIs with AI summarization capabilities to process web content efficiently. Quick Setup Get your Tavily API key from https://app.tavily.com/home Replace tvly-YOUR_API_KEY in the "Tavily API Key" node Connect your OpenAI credentials to the "OpenAI Chat Model" node Deploy the workflow and start the chat trigger Core Features Search & Extract 🎯 Intelligent web searching with relevance filtering Automated content extraction from top results AI-powered content summarization in markdown format User Interaction 💬 Chat-based search topic input Real-time processing pipeline Structured markdown output The workflow demonstrates practical implementation of Tavily's API endpoints while handling the complete process from search to summarization in a single automated pipeline.
AI-Driven Lead Management and Inquiry Automation with ERPNext & n8n
Overview This workflow template automates lead management and customer inquiry processing by integrating ERPNext, AI agents, and email notifications. It streamlines the process of capturing leads, analyzing inquiries, and generating actionable responses. The workflow uses ERPNext to capture inquiries, analyzes them with AI, and notifies the appropriate team or individual, all while maintaining a professional approach. What This Template Does ERPNext Webhook Integration: Captures leads and inquiries through ERPNext webhooks. Triggers the workflow when a new lead is created. AI-Powered Inquiry Analysis: Uses AI to extract key details from lead notes (e.g., customer name, organization, inquiry summary). Classifies inquiries as valid or invalid based on relevance to products, services, or solutions. Contact Assignment: Matches inquiries to the appropriate contact(s) using a Google Sheets database or ERPNext contact information. Handles multiple contacts if required. Email Notifications: Generates professional email notifications for valid inquiries. Sends emails to the appropriate contact(s) with inquiry details and action steps. Invalid Lead Handling: Identifies invalid inquiries (e.g
AI-Powered Candidate Shortlisting Automation for ERPNext
Template Guide for Employee Shortlisting AI Agent Automation Overview This template automates the process of shortlisting job applicants using ERPNext, n8n, and AI-powered decision-making tools like Google Gemini and OpenAI. It reduces manual effort, ensures fast evaluations, and provides justifiable decisions about applicants. This is ideal for businesses aiming to streamline their recruitment process while maintaining accuracy and professionalism. YouTube Tutorial:** For a full walkthrough of this template, visit: Integrate AI in ERPNext: Automate Recruitment Job Applicant Shortlisting in Seconds! What Does This Template Do? Webhook Integration with ERPNext: Automatically triggers the workflow when a job application is created in ERPNext. Resume Validation: Ensures resumes are attached and correctly processes various file formats like PDF and DOC. AI-Powered Evaluation: Uses AI to compare resumes against job descriptions and provides a: Fit Level (Strong, Moderate, or Weak) Score (0–100) Justification for the decision. Automated Decision Making: Based on AI-generated scores: Candidates with a score of 80 or higher are Accepted. Candidates below 80 are Rejected. Applications missi
WHR & IT Helpdesk Chatbot with Audio Transcription
An intelligent chatbot that assists employees by answering common HR or IT questions, supporting both text and audio messages. This unique feature ensures employees can conveniently ask questions via voice messages, which are transcribed and processed just like text queries. How It Works Message Capture: When an employee sends a message to the chatbot in WhatsApp or Telegram (text or audio), the chatbot captures the input. Audio Transcription: For audio messages, the chatbot transcribes the content into text using an AI-powered transcription service (e.g., Whisper, Google Cloud Speech-to-Text). Query Processing: The transcribed text (or directly entered text) is sent to an AI service (e.g., OpenAI) to generate embeddings. These embeddings are used to search a vector database (e.g., Supabase or Qdrant) containing the company’s internal HR and IT documentation. The most relevant data is retrieved and sent back to the AI service to compose a concise and helpful response. Response Delivery: The chatbot sends the final response back to the employee, whether the input was text or audio. Set Up Steps Estimated Time**: 20–25 minutes Prerequisites**: Create an account with an AI provider (e
🤖 Telegram Messaging Agent for Text/Audio/Images
🤖 This n8n workflow creates an intelligent Telegram bot that processes multiple types of messages and provides automated responses using AI capabilities. The bot serves as a personal assistant that can handle text, voice messages, and images through a sophisticated processing pipeline. Core Components Message Reception and Validation 📥 🔄 Implements webhook-based message reception for real-time processing 🔐 Features a robust user validation system that verifies sender credentials 🔀 Supports both testing and production webhook endpoints for development flexibility Message Processing Pipeline ⚡ 🔄 Uses a smart router to detect and categorize incoming message types 📝 Processes three main message formats: 💬 Text messages 🎤 Voice recordings 📸 Images with captions AI Integration 🧠 🤖 Leverages OpenAI's GPT-4 for message classification and processing 🗣️ Incorporates voice transcription capabilities for audio messages 👁️ Features image analysis using GPT-4 Vision API for processing visual content Technical Architecture Webhook Management 🔌 🌐 Maintains separate endpoints for testing and production environments 📊 Implements automatic webhook status monitoring ⚡ Provides real-ti
CProxmox AI Agent with n8n and Generative AI Integration
Proxmox AI Agent with n8n and Generative AI Integration This template automates IT operations on a Proxmox Virtual Environment (VE) using an AI-powered conversational agent built with n8n. By integrating Proxmox APIs and generative AI models (e.g., Google Gemini), the workflow converts natural language commands into API calls, enabling seamless management of your Proxmox nodes, VMs, and clusters. Buy My Book: Mastering n8n on Amazon Full Courses & Tutorials: http://lms.syncbricks.com Watch Video on Youtube How It Works Trigger Mechanism The workflow can be triggered through multiple channels like chat (Telegram, email, or n8n's built-in chat). Interact with the AI agent conversationally. AI-Powered Parsing A connected AI model (Google Gemini or other compatible models like OpenAI or Claude) processes your natural language input to determine the required Proxmox API operation. API Call Generation The AI parses the input and generates structured JSON output, which includes: response_type: The HTTP method (GET, POST, PUT, DELETE). url: The Proxmox API endpoint to execute. details: Any required payload parameters for the API call. Proxmox API Execution The structured output is used to