Code Workflows
445 Ergebnisse — ausschließlich quellenverknüpfte n8n-Referenzen
🤖 AI Powered RAG Chatbot for Your Docs + Google Drive + Gemini + Qdrant
🤖 AI-Powered RAG Chatbot with Google Drive Integration This workflow creates a powerful RAG (Retrieval-Augmented Generation) chatbot that can process, store, and interact with documents from Google Drive using Qdrant vector storage and Google's Gemini AI. How It Works Document Processing & Storage 📚 Retrieves documents from a specified Google Drive folder Processes and splits documents into manageable chunks Extracts metadata using AI for enhanced search capabilities Stores document vectors in Qdrant for efficient retrieval Intelligent Chat Interface 💬 Provides a conversational interface powered by Google Gemini Uses RAG to retrieve relevant context from stored documents Maintains chat history in Google Docs for reference Delivers accurate, context-aware responses Vector Store Management 🗄️ Features secure delete operations with human verification Includes Telegram notifications for important operations Maintains data integrity with proper version control Supports batch processing of documents Setup Steps Configure API Credentials: Set up Google Drive & Docs access Configure Gemini AI API Set up Qdrant vector store connection Add Telegram bot for notifications Add OpenAI Api Ke
W✍️🌄 Your First Wordpress + AI Content Creator - Quick Start
✍️🌄 WordPress + AI Content Creator This workflow automates the creation and publishing of multi-reading-level content for WordPress blogs. It leverages AI to generate optimized articles, automatically creates featured images, and provides versions of the content at different reading levels (Grade 2, 5, and 9). How It Works Content Generation & Processing 🎯 Starts with a manual trigger and a user-defined blog topic Uses AI to create a structured blog post with proper HTML formatting Separates and validates the title and content components Saves a draft version to Google Drive for backup Multi-Reading Level Versions 📚 Automatically rewrites the content for different reading levels: Grade 9: Sophisticated language with appropriate metaphors Grade 5: Simplified with light humor and age-appropriate examples Grade 2: Basic language with simple metaphors and child-friendly explanations WordPress Integration 🌐 Creates a draft post in WordPress with the Grade 9 version Generates a relevant featured image using Pollinations.ai Automatically uploads and sets the featured image Sends success/error notifications via Telegram Setup Steps Configure API Credentials 🔑 Set up WordPress API conn
🎦🚀 YouTube Video Comment Analysis Agent
🎦🚀 YouTube Video Comment Analysis Agent This n8n workflow is designed to help YouTube creators analyze video details and comments to generate a comprehensive and actionable report. The workflow provides insights into video performance, audience engagement, and viewer feedback, helping creators identify trends, interests, and opportunities for future content creation. ✨ Key Features Video Performance Analysis: Extracts metrics like views, likes, and comments to evaluate the video's success. Comment Sentiment Analysis: Determines the tone of comments (positive, neutral, or negative) to understand audience sentiment. Recurring Themes Detection: Identifies common topics or questions in comments to highlight viewer interests. Engagement Drivers: Pinpoints what aspects of the video resonated most with viewers. Actionable Recommendations: Offers strategies for creating follow-up content or improving future videos. Keyword Suggestions: Extracts frequently mentioned terms for better discoverability on YouTube. Collaboration Opportunities: Suggests potential partnerships based on viewer feedback or related channels. 🛠️ How to Use Set Up Workflow Variables: Add your GOOGLE_API_KEY and the
Free YouTube Video Analyzer with AI-Powered Summaries & Email Alerts
This workflow is designed to analyze YouTube videos by extracting their transcripts, summarizing the content using AI models, and sending the analysis via email. This workflow is ideal for content creators, marketers, or anyone who needs to quickly analyze and summarize YouTube videos for research, content planning, or educational purposes. How It Works: Trigger: The workflow starts with a manual trigger, allowing you to test it by clicking "Test workflow." You can also set a YouTube video URL manually or dynamically. YouTube Video ID Extraction: The workflow extracts the YouTube video ID from the provided URL using a custom JavaScript function. This ID is necessary for fetching the transcript. Transcript Generation: The video ID is sent via an HTTP request to generate the transcript. You need to replace APIKEY with a free API key from the service. Transcript Validation: The workflow checks if a transcript exists for the video. If a transcript is available, it proceeds; otherwise, it stops. Full Text Extraction: If a transcript exists, the workflow combines all transcript segments into a single text variable for further analysis. AI-Powered Analysis: The full transcript is passed t
CW⚡📽️ Ultimate AI-Powered Chatbot for YouTube Summarization & Analysis
🎥 YouTube Video AI Agent Workflow This n8n workflow template allows you to interact with an AI agent that extracts details and the transcript of a YouTube video using a provided video ID. Once the details and transcript are retrieved, you can chat with the AI agent to explore or analyze the video's content in a conversational and insightful manner. 🌟 How the Workflow Works 🔗 Input Video ID: The user provides a YouTube video ID as input to the workflow. 📄 Data Retrieval: The workflow fetches essential details about the video (e.g., title, description, upload date) and retrieves its transcript using YouTube's Data API and additional tools for transcript extraction. 🤖 AI Agent Interaction: The extracted details and transcript are processed by an AI-powered agent. Users can then ask questions or engage in a conversation with the agent about the video's content, such as: Summarizing the transcript. Analyzing key points. Clarifying specific sections. 💬 Dynamic Responses: The AI agent uses natural language processing (NLP) to generate contextual and accurate responses based on the video data, ensuring a smooth and intuitive interaction. 🚀 Use Cases 📊 Content Analysis**: Quickly an
SChat with your event schedule from Google Sheets in Telegram
What it is Chat with your event schedule from Google Sheets in Telegram: "When is the next meetup?" "How many events are there next month?" "Who presented most often?" "Which future meetups have no presenters yet?" This workflow lets you chat with a telegram bot about past, present and future events that are scheduled in a Google Spreadsheet. (Info: This proof-of-concept was created as a demo for a hackathon of an AI & Developer Meetup in Da Nang (Vietnam) that uses a telegram group to organize) Who it is for If you want an easy way for your audience to get information about your events, you can us this workflow for the same purpose, or easily adapt it to your needs and different use-cases where you want to query smaller amounts of tabular data in natural language. How it works Upon getting triggered by a chat message to a telegram bot, the schedule of meetups is retrieved from Google Spreadsheets, converted into a markdown table syntax and fed into the system prompt of an LLM (we're using OpenRouter in this example), whose output is posted back as answer into the same telegram chat. Setup steps TO REVIEWING IN ACTION As the reviewer of this workflow, you can temporarily use it via
BCWHacker News Job Listing Scraper and Parser
This automated workflow scrapes and processes the monthly "Who is Hiring" thread from Hacker News, transforming raw job listings into structured data for analysis or integration with other systems. Perfect for job seekers, recruiters, or anyone looking to monitor tech job market trends. How it works Automatically fetches the latest "Who is Hiring" thread from Hacker News Extracts and cleans relevant job posting data using the HN API Splits and processes individual job listings into structured format Parses key information like location, role, requirements, and company details Outputs clean, structured data ready for analysis or export Set up steps Configure API access to [Hacker News](https://github.com/HackerNews/API ) (no authentication required) Follow the steps to get your cURL command from https://hn.algolia.com/ Set up desired output format (JSON structured data or custom format) Optional: Configure additional parsing rules for specific job listing information Optional: Set up integration with preferred storage or analysis tools The workflow transforms unstructured job listings into clean, structured data following this pattern: Input: Raw HN thread comments Process: Extract,
Detect hallucinations using specialised Ollama model bespoke-minicheck
Fact-Checking Workflow Documentation Overview This workflow is designed for automated fact-checking of texts. It uses AI models to compare a given text with a list of facts and identify potential discrepancies or hallucinations. Components 1. Input The workflow can be initiated in two ways: a) Manually via the "When clicking 'Test workflow'" trigger b) By calling from another workflow via the "When Executed by Another Workflow" trigger Required inputs: facts: A list of verified facts text: The text to be checked 2. Text Preparation The "Code" node splits the input text into individual sentences Takes into account date specifications and list elements 3. Fact Checking Each sentence is individually compared with the given facts Uses the "bespoke-minicheck" Ollama model for verification The model responds with "Yes" or "No" for each sentence 4. Filtering and Aggregation Sentences marked as "No" (not fact-based) are filtered The filtered results are aggregated 5. Summary A larger language model (Qwen2.5) creates a summary of the results The summary contains: Number of incorrect factual statements List of incorrect statements Final assessment of the article's accuracy Usage Ensure the "
CUTM Link Creator & QR Code Generator with Scheduled Google Analytics Reports
UTM Link Creator & QR Code Generator with Scheduled Google Analytics Reports This workflow enables marketers to generate UTM-tagged links, convert them into QR codes, and automate performance tracking in Google Analytics with scheduled reports every 7 days. This solution helps monitor traffic sources from different marketing channels and optimize campaign performance based on analytics data. Prerequisites Before implementing this workflow, ensure you have the following: Google Analytics 4 (GA4) Account & Access Ensure you have a GA4 property set up. Access to the GA4 Data API to schedule performance tracking. Refer to the Google Analytics Data API Overview for more information. Airtable Account & API Key Create an Airtable base to store UTM links, QR codes, and analytics data. Obtain an Airtable API key from your Account Settings. Detailed instructions are available in the Airtable API Authentication Guide. Step-by-Step Guide to Setting Up the Workflow 1. Generate UTM Links Create a form or interface to input: Base URL** (e.g., https://example.com) Campaign Name** (utm_campaign) Source** (utm_source) Medium** (utm_medium) Term** (Optional: utm_term) Content** (Optional: utm_content
Fetch Dynamic Prompts from GitHub and Auto-Populate n8n Expressions in Prompt
Who Is This For? This workflow is designed for AI engineers, automation specialists, and content creators who need a scalable system to dynamically manage prompts stored in GitHub. It eliminates manual updates, enforces required variable checks, and ensures that AI interactions always receive fully processed prompts. 🚀 What Problem Does This Solve? Manually managing AI prompts can be inefficient and error-prone. This workflow: ✅ Fetches dynamic prompts from GitHub ✅ Auto-populates placeholders with values from the setVars node ✅ Ensures all required variables are present before execution ✅ Processes the formatted prompt through an AI agent 🛠 How This Workflow Works This workflow consists of three key branches, ensuring smooth prompt retrieval, variable validation, and AI processing. 1️⃣ Retrieve the Prompt from GitHub (HTTP Request → Extract from File → SetPrompt) The workflow starts manually or via an external trigger. It fetches a text-based prompt stored in a GitHub repository. The Extract from File Node retrieves the content from the GitHub file. The SetPrompt Node stores the prompt, making it accessible for processing. 📌 Note: The prompt must contain n8n expression format v
Open Deep Research - AI-Powered Autonomous Research Workflow
Open Deep Research - AI-Powered Autonomous Research Workflow Description This workflow automates deep research by leveraging AI-driven search queries, web scraping, content analysis, and structured reporting. It enables autonomous research with iterative refinement, allowing users to collect, analyze, and summarize high-quality information efficiently. How it works 🔹 User Input The user submits a research topic via a chat message. 🧠 AI Query Generation A Basic LLM generates up to four refined search queries to retrieve relevant information. 🔎 SERPAPI Google Search The workflow loops through each generated query and retrieves top search results using the SerpAPI API. 📄 Jina AI Web Scraping Extracts and summarizes webpage content from the URLs obtained via SerpAPI. 📊 AI-Powered Content Evaluation An AI Agent evaluates the relevance and credibility of the extracted content. 🔁 Iterative Search Refinement If the AI finds insufficient or low-quality information, it generates new search queries to improve results. 📜 Final Report Generation The AI compiles a structured markdown report, including sources with citations. Set Up Instructions 🚀 Estimated setup time: ~10-15 minutes ✅ Re
Host Your Own AI Deep Research Agent with n8n, Apify and OpenAI o3
This template attempts to replicate OpenAI's DeepResearch feature which, at time of writing, is only available to their pro subscribers. > An agent that uses reasoning to synthesize large amount of online information and complete multi-step research tasks for you. Source Though the inner workings of DeepResearch have not been made public, it is presumed the feature relies on the ability to deep search the web, scrape web content and invoking reasoning models to generate reports. All of which n8n is really good at! Using this workflow, n8n users can enjoy a variation of the Deep Research experience for themselves and their teams at a fraction of the cost. Better yet, learn and customise this Deep Research template for their businesses and/or organisations. Check out the generated reports here: https://jimleuk.notion.site/19486dd60c0c80da9cb7eb1468ea9afd?v=19486dd60c0c805c8e0c000ce8c87acf How it works A form is used to first capture the user's research query and how deep they'd like the researcher to go. Once submitted, a blank Notion page is created which will later hold the final report and the researcher gets to work. The user's query goes through a recursive series of web serc
WAuthor and Publish Blog Posts From Google Sheets
What it is: An automation to plan→draft→finalize and publish your textual blog post ideas to your wordpress blog Works in stages and hand back control to you in between those You can use a Google Spreadsheet for planning topics and configuring LLM models and prompts What it does: plans→drafts→finalizes blog post topics you specify in a Google Spreadsheet using an LLM with prompts that also ar configured in that spreadsheet (even which model to use) savs the results in the corresponding columns of the "Schedule" sheet in the spreadsheet hands control back to the user for inspecting or changing the results and for setting the next "Action" for th workflow Finally publishes the blog post to your Wordpress instance Limitations Probably slightly over-engineered ;-) No media generation yet some LLM models don't work because of their output format How it works: The Workflow is triggered manually or scheduled every hour It ingests a Google Spreadsheet to get Config for prompts/context tc Blog-Topics and their status and next action Depending on each blog topics "Status" and "Action" it then either uses an LLM for th next action ("plan"→"draft"→"final" actions) or publishes the written cont
RAG:Context-Aware Chunking | Google Drive to Pinecone via OpenRouter & Gemini
Workflow based on the following article. https://www.anthropic.com/news/contextual-retrieval This n8n automation is designed to extract, process, and store content from documents into a Pinecone vector store using context-based chunking. The workflow enhances retrieval accuracy in RAG (Retrieval-Augmented Generation) setups by ensuring each chunk retains meaningful context. Workflow Breakdown: 🔹 Google Drive - Retrieve Document: The automation starts by fetching a source document from Google Drive. This document contains structured content, with predefined boundary markers for easy segmentation. 🔹 Extract Text Content - Once retrieved, the document’s text is extracted for processing. Special section boundary markers are used to divide the text into logical sections. 🔹 Code Node - Create Context-Based Chunks: A custom code node processes the extracted text, identifying section boundaries and splitting the document into meaningful chunks. Each chunk is structured to retain its context within the entire document. 🔹 Loop Node - Process Each Chunk: The workflow loops through each chunk, ensuring they are processed individually while maintaining a connection to the overall document c
CAutomate Pinterest Analysis & AI-Powered Content Suggestions With Pinterest API
Automate Pinterest Analysis & AI-Powered Content Suggestions With Pinterest API This workflow automates the collection, analysis, and summarization of Pinterest Pin data to help marketers optimize content strategy. It gathers Pinterest Pin performance data, analyzes trends using an AI agent, and delivers actionable insights to the Marketing Manager via email. This setup is ideal for content creators and marketing teams who need weekly insights on Pinterest trends to refine their content calendar and audience engagement strategy. Prerequisites Before setting up this workflow, ensure you have the following: Pinterest API Access & Developer Account Sign up at Pinterest Developers and obtain API credentials. Ensure you have access to both Organic and Paid Pin data. Airtable Account & API Key Create an account at Airtable and set up a database. Obtain an API key from Account Settings. AI Agent for Trend Analysis An AI-powered agent (such as OpenAI's GPT or a custom ML model) is required to analyze Pinterest trends. Ensure integration with your workflow automation tool (e.g., Zapier, Make, or a custom Python script). Email Automation Setup Configure an SMTP email service (e.g., Gmail, Ou
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
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.
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
AI Fitness Coach Strava Data Analysis and Personalized Training Insights
Detailed Title "Triathlon Coach AI Workflow: Strava Data Analysis and Personalized Training Insights using n8n" Description This n8n workflow enables you to build an AI-driven virtual triathlon coach that seamlessly integrates with Strava to analyze activity data and provide athletes with actionable training insights. The workflow processes data from activities like swimming, cycling, and running, delivers personalized feedback, and sends motivational and performance improvement advice via email or WhatsApp. Workflow Details Trigger: Strava Activity Updates Node:** Strava Trigger Purpose:** Captures updates from Strava whenever an activity is recorded or modified. The data includes metrics like distance, pace, elevation, heart rate, and more. Integration:** Uses Strava API for real-time synchronization. Step 1: Data Preprocessing Node:** Code Purpose:** Combines and flattens the raw Strava activity data into a structured format for easier processing in subsequent nodes. Logic:** A recursive function flattens JSON input to create a clean and readable structure. Step 2: AI Analysis with Google Gemini Node:** Google Gemini Chat Model Purpose:** Leverages Google Gemini's advanced langu
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
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