Automated AI Chatbot for Slack with Webhook Integration
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This workflow enables you to build an AI-powered chatbot for Slack that responds to messages received via a secure webhook. It leverages AI models like Google Gemini to process queries and maintain conversation history for intelligent interactions.
About This Workflow
This n8n workflow empowers you to create a sophisticated AI chatbot integrated directly with your Slack workspace. It begins by setting up a secure POST webhook endpoint, designed to receive messages from Slack. These messages are then fed into an AI Agent, which utilizes powerful language models like Google Gemini to understand and process user queries. To ensure contextual awareness, the workflow incorporates memory management, storing conversation history to provide more relevant and intelligent responses. Finally, the AI's generated replies are sent back to Slack as new messages, creating a seamless and interactive chatbot experience. This solution is ideal for automating customer support, internal knowledge bases, or any task requiring intelligent message processing within Slack.
Key Features
- Secure Slack Integration: Utilizes POST webhooks for reliable message reception.
- AI-Powered Processing: Employs AI Agents and LLMs (e.g., Google Gemini) for intelligent query understanding and response generation.
- Conversation Memory: Maintains chat history for context-aware interactions.
- Customizable AI Persona: Define specific system messages to tailor the AI's behavior.
- Automated Response Relay: Seamlessly sends AI-generated replies back to Slack.
How To Use
- Configure the Webhook Node: Set up the 'Webhook to receive message' node with a secure path and ensure it's configured with an HTTPS wrapper, not
http://localhost:5678. - Set up the AI Agent: Connect the webhook output to the 'Agent' node. Configure the
systemMessageparameter to define the AI's persona and purpose (e.g., "You are Effibotics AI personal assistant..."). - Integrate AI Language Model: Connect your preferred AI model (e.g., 'Google Gemini Chat Model') to the 'Agent' node via the
ai_languageModelconnection. - Enable Conversation Memory: Connect the 'Agent' node to the 'Window Buffer Memory' node via the
ai_memoryconnection. Configure thesessionKeyusing a token from the incoming webhook body to manage chat sessions. - Configure Slack Response: Connect the 'Agent' node to the 'Send response back to slack channel' node. Customize the
textparameter to include user input and the AI's response, and ensure thechannelIdis dynamically set from the incoming webhook. - Deploy and Test: Ensure your webhook is accessible and test by sending messages to your Slack channel.
Apps Used
Workflow JSON
{
"id": "dd59ee50-da99-4457-a7fe-6acac654d6e6",
"name": "Automated AI Chatbot for Slack with Webhook Integration",
"nodes": 15,
"category": "Operations",
"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: dd59ee50-da99...
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