AI-Powered Personalized Twitter Auto-DM for New Followers
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Automate the process of sending highly personalized direct messages to your new Twitter followers using advanced AI. This workflow leverages Retrieval Augmented Generation (RAG) with a vector database to craft context-aware welcome messages, improving engagement and saving you time.
About This Workflow
This sophisticated n8n workflow revolutionizes how you interact with new Twitter followers. Triggered by a new follower event, it orchestrates an intelligent AI pipeline: it uses Cohere for text embeddings, stores and retrieves knowledge from a Pinecone vector database, and employs an OpenAI Chat Model within a Langchain RAG Agent. This allows the AI to understand context, maintain memory, and generate personalized, relevant direct messages. The workflow also ensures robust operations by logging all activity to Google Sheets and sending instant Slack alerts for any errors, ensuring you're always informed and in control of your automated outreach.
Key Features
- AI-Powered Personalization: Generates contextually relevant and unique direct messages for each new follower using a sophisticated RAG Agent.
- Knowledge Base Integration: Leverages Pinecone vector database to store and retrieve specific information, ensuring the AI has a rich context for message creation.
- Conversational Memory: The Langchain Window Memory node allows the AI agent to maintain context across interactions, leading to more coherent and personalized dialogues.
- Automated Logging: Seamlessly logs all direct message activities and statuses to Google Sheets for easy tracking and analysis.
- Real-time Error Alerts: Integrates with Slack to provide immediate notifications for any workflow failures, enabling quick troubleshooting and ensuring continuous operation.
How To Use
- Configure Webhook Trigger: Set up this node to listen for incoming new Twitter follower events (e.g., from a Twitter API watcher or another external service that detects new followers). The path
auto-dm-new-twitter-followersshould be used. - Connect AI Services: Provide your API credentials for Cohere (for Embeddings) and OpenAI (for the Chat Model) in their respective credential fields.
- Set Up Pinecone: Link your Pinecone API credentials. Ensure a Pinecone index named
auto-dm_new_twitter_followersexists or create one, as it will be used for both inserting (your knowledge base) and querying relevant context for DMs. - Populate Your Knowledge Base (Optional but Recommended): Use the
Text Splitter,Embeddings, andPinecone Insertnodes to feed product information, FAQs, common replies, or brand guidelines into your Pinecone index. This enriches the RAG Agent's ability to personalize messages. - Customize the RAG Agent: Refine the
systemMessagewithin theRAG Agent(e.g., "You are a helpful assistant that crafts personalized welcome messages for new Twitter followers based on their profile and your brand's offerings.") to define the AI's persona and messaging style. - Integrate Logging and Alerts: Connect your Google Sheets account for the
Append Sheetnode to log the status of each auto-DM and your Slack account for theSlack Alertnode to receive notifications if any errors occur during execution.
Apps Used
Workflow JSON
{
"id": "789b0f00-af38-4399-84c4-c1a76bef2fb0",
"name": "AI-Powered Personalized Twitter Auto-DM for New Followers",
"nodes": 7,
"category": "Marketing",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 789b0f00-af38...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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