OpenAI Automation Workflows
899 ready-made OpenAI workflows for n8n, Make, Zapier, Activepieces, and Pipedream. GPT-powered enrichment, generation, and classification inside your automations.
Customer Support Chatbot with RAG Using OpenAI and Pinecone
# Simple RAG Customer Support Chatbot ## Overview This intelligent customer support chatbot leverages Retrieval-Augmented Generation (RAG) to provide accurate, contextual responses by combining your knowledge base with AI capabilities. The system automatically retrieves relevant documents from your Pinecone vector store and uses them to generate informed responses through OpenAI's language models. ## Quick Setup 1. **Import Workflow** - Import this workflow template into your n8n instance. 2. **Configure Credentials** - Add the following API credentials: - OpenAI API Key: For chat completions and embeddings. - Pinecone API Key: For vector database operations. - Google Drive: For document auto ingestion. 3. **Initialize Vector Store** - Use the "Insert documents into Pinecone" workflow to populate your knowledge base. 4. **Activate Workflow** - Enable the main chat workflow to start receiving requests. ## How it Works **Main Chat Flow (Agent Workflow)** User Message → Memory Retrieval → Vector Search → Context Assembly → AI Response → Memory Update → Response **Process Flow:** - Message Reception: Webhook receives user chat messages with session management. - Memory Retrieval: Loads conversation history for context continuity. - Semantic Search: Queries Pinecone vector store for relevant documents. - Context Assembly: Combines retrieved documents with conversation history. - AI Generation: OpenAI generates contextual response using assembled context. - Memory Storage: Updates conversation memory for future interactions. - Response Delivery: Returns formatted response to user interface. **Document Ingestion Flow** Document Source → Text Extraction → Chunking → Embedding → Vector Storage **Process Flow:** - Document Trigger: Google Drive or manual file upload detection. - Content Extraction: Extracts text from various file formats (PDF, DOC, X). - Text Chunking: Splits documents into optimal chunks for embedding. - Embedding Generation: Creates vector embeddings using OpenAI. - Vector Storage: Stores embeddings in Pinecone with metadata. - Index Update: Updates search index for immediate availability.
n8n$9.99Query PDF Content Using Weaviate and OpenAI for Document Q&A
Upload a PDF and ask questions about its content using Weaviate and OpenAI in n8n. This workflow serves as a template for implementing Retrieval-Augmented Generation (RAG) over your documents.
n8n$14.99Automate AI-Driven Engineering Department with OpenAI Agents
Leverage AI agents to create a comprehensive engineering department, orchestrated by a CTO agent for efficient software development and technical operations.
n8n$14.99Deploy an AI-Powered WhatsApp Chatbot with OpenAI and Qdrant
This n8n workflow sets up an AI-powered chatbot for WhatsApp using OpenAI and Qdrant to enhance customer interactions with retrieval-augmented generation capabilities.
n8n$14.99Build a Company Policy Chatbot Using RAG, Pinecone, and OpenAI
Create a chatbot that answers company policy questions by integrating n8n with Pinecone and OpenAI for context-aware responses.
n8n$14.99Automate Research-Based Article Generation with OpenAI and Web Search
This workflow automates the creation of research-backed articles by integrating OpenAI and web search capabilities. Ideal for content marketers and SEO teams, it streamlines the process of generating high-quality, SEO-optimized content with minimal manual input.
n8n$24.99High-Speed AI Chat with OpenAI's GPT-oss-120B Model via Cerebras Inference
## Overview This n8n workflow provides seamless integration with Cerebras' high-performance inference platform to leverage OpenAI's open-source GP-OSS-120B model. With industry-leading speeds of thousands of tokens per second and ultra-low latency under 0.5 seconds, this template enables developers and businesses to build responsive AI applications without the complexity of managing infrastructure or dealing with slow response times that plague traditional AI integrations. ## How it works This streamlined workflow establishes a direct connection to Cerebras' inference API through four simple nodes. When a chat message is received, the workflow processes it through the configured API key, sends it to the Cerebras endpoint with your specified parameters (temperature, completion tokens, top P, reasoning effort), and returns the AI-generated response. ## Detailed Workflow Explanation **1. When chat message received**: This trigger node initiates the workflow whenever a new chat message is detected. It captures the user's input and passes it to the next node in the chain, supporting various input formats and message sources. **2. Set API Key**: A manual configuration node where you securely store your Cerebras API key. This node handles authentication and ensures your requests are properly authorized when communicating with the Cerebras inference API. **3. Cerebras endpoint**: The core HTTP request node that communicates with Cerebras' chat completions API. This node is pre-configured to work with the GP-OSS-120B model and includes parameter settings for temperature, completion tokens, top P, and reasoning effort that can be customized based on your specific needs. **4. Return Output**: The final node that processes and formats the AI response, delivering the generated text back to your application or user interface in a clean, usable format. ## Who is it for **Developers** building real-time chat applications, conversational AI systems, or interactive web applications who need consistent sub-second response times without managing complex AI infrastructure. **Content creators** and marketing teams who require rapid text generation for blogs, social media content, product descriptions, or marketing copy, enabling faster content production cycles and improved productivity. **Businesses** implementing customer service automation, lead qualification systems, or interactive FAQ solutions where response latency directly impacts user experience and conversion rates. **SaaS companies** looking to integrate AI features into existing products without the overhead of training models or managing inference servers, allowing them to focus on core business logic. **Researchers and data scientists** experimenting with high-performance language models for prototyping, A/B testing different prompting strategies, or conducting performance benchmarks against other AI providers. **Startups and small teams** seeking enterprise-grade AI capabilities without the infrastructure costs or technical complexity typically associated with large language model deployment. ## Comprehensive Setup Instructions **1. Cerebras Account Setup** - Visit Cerebras and create a new account. - Complete email verification and profile setup. - Navigate to the API Keys section in your dashboard. - Generate a new API key and securely store it. - Review the rate limits for free tier accounts and upgrade if needed. **2. N8N Workflow Configuration** - Import the template into your n8n instance. - Click on the Set API Key node and enter your Cerebras API key. - Configure the trigger node based on your input source (webhook, manual, scheduled). - Test the workflow using the built-in execution feature. **3. Parameter Customization** - Open the Cerebras endpoint node to access the parameter configuration. - Adjust temperature, completion tokens, top P, and reasoning effort based on your use case. - Save and test the workflow to ensure proper functionality. ## Customization and Configuration Guide **Model Parameters in the Cerebras Endpoint Node**: - **Temperature** (0.0-2.0): Lower values (0.1-0.3) for factual, consistent responses; higher values (0.7-1.5) for creative, varied content. - **Completion Tokens**: Set based on expected response length - 150 for short answers, 500+ for detailed explanations, 1000+ for long-form content. - **Top P** (0.1-1.0): Controls response diversity; 0.9 works well for most applications, lower values for more focused responses. - **Reasoning Effort**: Adjusts the model's computational effort for complex reasoning tasks; higher values for analytical or problem-solving queries. **Use Case Specific Configurations**: - **Customer Support**: Temperature 0.2, moderate completion tokens, consistent helpful responses. - **Creative Writing**: Temperature 1.0-1.2, higher completion tokens for diverse, imaginative content. - **Technical Documentation**: Temperature 0.3, structured output with examples and code snippets. - **Casual Conversation**:
n8n$4.99Search Outlook Emails Using Natural Language with OpenAI Integration
This workflow enables you to search your Outlook mailbox using natural language queries. By leveraging OpenAI, it transforms your query into a search term, retrieves relevant emails, and presents them in a ranked table format.
n8n$14.99Automate Email Campaign Analysis & Smart Follow-ups with Bright Data & OpenAI
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically tracks email campaign performance metrics and triggers smart follow-up actions based on engagement data. It saves you time by eliminating the need to manually monitor campaign reports and provides intelligent re-engagement strategies for improving email marketing ROI. ## Overview This workflow automatically scrapes email service provider (ESP) reports to extract campaign performance metrics like open rates, click-through rates, and bounce rates. It uses AI to analyze the data and automatically sends targeted follow-up emails to re-engage subscribers who opened but didn't click, maximizing campaign effectiveness. ## Tools Used - **n8n**: The automation platform that orchestrates the workflow - **Bright Data**: For scraping ESP campaign reports without being blocked - **OpenAI**: AI agent for intelligent campaign data analysis and decision making - **Gmail**: For sending automated follow-up engagement emails ## How to Install 1. **Import the Workflow**: Download the .json file and import it into your n8n instance. 2. **Configure Bright Data**: Add your Bright Data credentials to the MCP Client node. 3. **Set Up OpenAI**: Configure your OpenAI API credentials. 4. **Configure Gmail**: Connect your Gmail account for sending follow-up emails. 5. **Customize**: Set ESP report URLs and define engagement thresholds for triggering follow-ups. ## Use Cases - **Email Marketing**: Automatically optimize campaign performance with smart follow-ups. - **Marketing Automation**: Trigger re-engagement campaigns based on behavior data. - **Performance Tracking**: Monitor email metrics without manual ESP login. - **Customer Retention**: Re-engage subscribers who showed interest but didn't convert. ## 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 #emailmarketing #campaigntracking #brightdata #webscraping #emailautomation #n8nworkflow #workflow #nocode #emailcampaigns #marketingautomation #emailperformance #campaignanalysis #emailmetrics #reengagement #marketingdata #emailoptimization #campaignmonitoring #emailanalytics #digitalmarketing #performancetracking #emailstrategy #conversionoptimization #marketinganalytics #emailroi #campaigninsights #emailengagement #marketingefficiency #automatedemail
n8n$14.99Build a ServiceNow Knowledge Chatbot with OpenAI and Qdrant RAG
### **1. Data Ingestion Workflow (Left Panel - Pink Section)** This part collects data from the ServiceNow Knowledge Article table, processes it into embeddings, and stores it in Qdrant. #### **Steps:** 1. **Trigger: When clicking "Execute workflow"** - The workflow starts manually when you click *Execute workflow* in n8n. 2. **Get Many Table Records** - Fetches multiple records from the ServiceNow Knowledge Article table. Each record typically contains knowledge article content that needs to be indexed. 3. **Default Data Loader** - Takes the fetched data and structures it into a format suitable for text splitting and embedding generation. 4. **Recursive Character Text Splitter** - Splits large text (e.g., long knowledge articles) into smaller, manageable chunks for embeddings. This step ensures that each text chunk can be properly processed by the embedding model. 5. **Embeddings OpenAI** - Uses OpenAI's Embeddings API to convert each text chunk into a high-dimensional vector representation. These embeddings are essential for semantic search in the vector database. 6. **Qdrant Vector Store** - Stores the generated embeddings along with metadata (e.g., article ID, title) in the Qdrant vector database. This database will later be used for similarity searches during chatbot interactions. --- ### **2. RAG Chatbot Workflow (Right Panel - Green Section)** This section powers the Retrieval-Augmented Generation (RAG) chatbot that retrieves relevant information from Qdrant and responds intelligently. #### **Steps:** 1. **Trigger: When chat message received** - Starts when a user sends a chat message to the system. 2. **AI Agent** - Acts as the orchestrator, combining memory, tools, and LLM reasoning. Connects to the OpenAI Chat Model and Qdrant Vector Store. 3. **OpenAI Chat Model** - Processes user messages and generates responses, enriched with context retrieved from Qdrant. 4. **Simple Memory** - Stores conversational history or context to ensure continuity in multi-turn conversations. 5. **Qdrant Vector Store** - Performs a similarity search on stored embeddings using the user's query. Retrieves the most relevant knowledge article chunks for the chatbot. 6. **Embeddings OpenAI** - Converts user query into embeddings for vector search in Qdrant.
n8n$9.99Basic Automatic Gmail Email Labeling with OpenAI and Gmail API
## Description This workflow automates email categorization in Gmail using the Gmail API and OpenAI's language model. It periodically checks for new emails, reads their content, and categorizes them based on existing Gmail labels. If no matching label is found, the workflow creates a new label and assigns it to the email. ## Key Features - **Polling for Emails**: The workflow triggers every 5 minutes to check for new emails using the Gmail Trigger node. - **Reading Labels**: Existing Gmail labels are fetched to determine the most relevant match for email categorization. - **Dynamic Labeling**: If no existing label matches, a new label is created dynamically based on the email's content. - **OpenAI Integration**: The workflow uses OpenAI's Chat model to analyze email content and suggest or create appropriate labels. - **Email Categorization**: Labels are applied to emails, ensuring they are organized in Gmail's structure. The workflow also removes less relevant emails (e.g., ads) from the inbox. ## Nodes in Use 1. **Gmail Trigger**: Polls Gmail every 5 minutes for new emails. 2. **Gmail - Read Labels**: Fetches all existing Gmail labels. 3. **Gmail - Get Message**: Retrieves the full content of a specific email. 4. **Gmail - Add Label to Message**: Assigns a chosen label to the email. 5. **Gmail - Create Label**: Creates a new label if necessary. 6. **OpenAI Chat Model**: Analyzes email content for categorization. 7. **Memory Buffer**: Retains context for email analysis across multiple iterations. 8. **Wait Node**: Adds a buffer period to manage email processing. ## Prerequisites - **Gmail API Setup**: Ensure Gmail OAuth2 credentials are configured in n8n. - **OpenAI API Key**: Configure OpenAI credentials for email analysis. - **Labeling Standards**: Maintain a consistent Gmail label structure for better organization. ## Instructions 1. Add your Gmail API credentials to the Gmail nodes. 2. Add your OpenAI API credentials to the OpenAI Chat Model node. 3. Activate the workflow. It will start polling for new emails every 5 minutes. 4. Monitor and refine the categorization logic if necessary to ensure alignment with Gmail's organizational needs. ## Use Case Ideal for individuals or teams handling high email volumes who want to maintain an organized inbox and automate repetitive categorization tasks. Note: You can improve the prompt to get better results from the agent by giving it more personal rules on how to categorize.
n8n$9.99Automate Daily News Summaries with OpenAI and Perplexity AI via Zalo and Telegram
This n8n workflow automates the process of fetching, summarizing, and delivering daily news articles from multiple RSS feeds. It generates a concise summary using OpenAI and Perplexity AI, translating it into Vietnamese, and sends it via Zalo and Telegram.
n8n$14.99Automate Tailored Cover Letter Creation with Indeed and OpenAI
Streamline your job application process by automatically generating customized cover letters using Indeed job postings and OpenAI's language model.
n8n$9.99Automate Google Calendar Management with OpenAI Integration
This workflow enables automated management of Google Calendar events using OpenAI's language model. It supports listing, creating, and deleting events based on text inputs, enhancing productivity through seamless integration.
n8n$9.99Automate Cybersecurity News Filtering with OpenAI and Pinecone
This workflow automates the collection and filtering of cybersecurity news using OpenAI's RAG capabilities and Pinecone, ensuring you receive only the most relevant updates for your tech stack.
n8n$19.99Create a Browser-Based Voice Assistant with OpenAI and n8n
Build an interactive voice assistant interface using n8n and OpenAI, enabling users to engage with AI through voice commands directly in their browser.
n8n$9.99Automate Gmail Email Classification with OpenAI's GPT-5
Automatically classify and label Gmail emails using OpenAI's GPT-5 model to streamline inbox management and improve email organization.
n8n$4.99Automate Outlook Email Replies Using OpenAI
Streamline your email management by automating replies in Microsoft Outlook with OpenAI's language model. Customize the AI to match your tone and style for seamless communication.
n8n$9.99Automate Real Estate Lead Qualification with OpenAI, Gmail, and Airtable
Streamline your real estate lead qualification process by automatically scoring and filtering leads using OpenAI, with notifications via Gmail and CRM logging in Airtable.
n8n$9.99Automate Sentiment Analysis for Call Center Transcripts Using OpenAI and Google Sheets
This workflow streamlines sentiment analysis for call center transcripts by leveraging OpenAI's language model and Google Sheets. It provides structured feedback on various sentiment dimensions, enabling managers to enhance performance and training.
n8n$9.99Automate Daily Pipedrive Deal Summaries with OpenAI
This workflow retrieves deals and their notes from Pipedrive, translates stage IDs into names, aggregates the data, and utilizes OpenAI to generate a daily summary of your sales funnel.
n8n$9.99Generate & Schedule Social Posts with Gemini/OpenAI for Facebook and LinkedIn
## LinkedIn Content Machine - AI-Powered Post Generator & Scheduler for X and LinkedIn **How it works:** This end-to-end workflow automates your personal or brand content strategy by: - Using Google Gemini or OpenAI to generate engaging LinkedIn/X content from a title or trending posts. - Posting directly to LinkedIn and X (formerly Twitter). - Pulling high-performing LinkedIn posts to inspire new ideas. - Saving AI-generated drafts to Google Sheets for review. - Notifying your team on Slack when drafts are ready. **Steps to set up:** 1. Add your API keys for Google Gemini or OpenAI. 2. Set up your LinkedIn, X (Twitter), Google Sheets, and Slack credentials. 3. Customize prompt logic or post filters if needed. 4. Schedule the idea generation module or trigger it manually. 5. Start generating and posting consistent, high-quality content with zero manual effort!
n8n$9.99Automate Instagram DMs with OpenAI and ManyChat Integration
Streamline your Instagram direct messaging by integrating OpenAI with ManyChat to automatically respond to messages using AI-generated replies.
n8n$9.99Automate AI Image Creation with OpenAI and n8n
Effortlessly generate custom AI images using OpenAI's API within n8n. Define parameters, send requests, and convert images to downloadable files.
n8n$4.99
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