Log Twitter Mentions in Notion with AI-Powered Vector Storage
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Automate the logging of Twitter mentions into Notion and store their embeddings in Weaviate. This workflow uses a Webhook Trigger to capture mentions, processes them with a Text Splitter and Embeddings node, and then utilizes a RAG Agent for intelligent storage and retrieval via Weaviate and a Vector Tool.
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About This Workflow
Overview
This n8n workflow automates the process of capturing Twitter mentions and storing them in a structured manner within Notion. It leverages AI capabilities by generating embeddings for the mentions and storing them in Weaviate, a vector database. This enables intelligent retrieval and analysis of Twitter mentions. The workflow is triggered via a Webhook, processes text data, generates embeddings, and then uses a RAG Agent to manage the interaction with the vector store and Notion.
Key Features
- Real-time Mention Capture: Utilizes a Webhook Trigger to receive Twitter mentions as they happen.
- AI-Powered Embeddings: Generates vector embeddings of mention content using Cohere's models.
- Vector Storage & Retrieval: Stores embeddings in Weaviate for efficient similarity search and context retrieval.
- Intelligent Agent: Employs a RAG Agent to process and manage data flow between different AI and storage nodes.
- Notion Integration: Logs the processed mentions into a Notion database for organized record-keeping.
- Error Handling: Includes a Slack Alert node to notify of any workflow failures.
How To Use
- Set up Webhook Trigger: Configure the Webhook node to receive incoming data from your Twitter mention source (e.g., via a custom integration or another service).
- Configure Text Splitter: Adjust the
chunkSizeandchunkOverlapparameters in the Text Splitter node to appropriately segment the incoming mention text. - Set up Embeddings: Ensure your Cohere API key is configured. The Embeddings node will automatically generate vector representations of the split text.
- Configure Weaviate: Set up your Weaviate instance and ensure the
indexNamein both theWeaviate InsertandWeaviate Querynodes matches your Weaviate index. - Configure RAG Agent: Define the system message and integrate the Vector Tool and Window Memory nodes as shown in the workflow for intelligent data handling.
- Set up Notion Integration: Provide the necessary credentials and specify the
SHEET_IDandsheetNamefor your Notion database in the Append Sheet node. - Configure Slack Alerts: Set up your Slack API credentials and specify the channel for receiving error notifications.
Apps Used
Workflow JSON
{
"id": "fd83b3d4-de49-4ddf-a7bc-6d077ffaf429",
"name": "Log Twitter Mentions in Notion with AI-Powered Vector Storage",
"nodes": 0,
"category": "Social Media Automation",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: fd83b3d4-de49...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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