This n8n workflow creates an intelligent Slack chatbot capable of processing messages via a webhook, utilizing AI language models with memory to maintain context over conversations. When a user sends a message to a specified Slack channel, the workflow receives it through a POST webhook that is configured with HTTPS for security.
The message content, along with a unique session token, is passed to an AI language model (Google Gemini in this case) that processes the input based on a designated system prompt, which defines the bot as an assistant providing automation-related support.
To enable conversational continuity, the workflow stores chat history in a window buffer memory keyed by the session token. This memory allows the AI to refer to previous interactions, making responses more coherent.
After processing, the AI’s response is relayed back to the original Slack channel as a new message, maintaining engagement. The entire process is automated, providing a seamless, real-time conversational experience for users, ideal for customer support, internal assistance, or automation guidance within Slack.
This setup is practical for teams looking to automate responses, ensure context-aware interactions, and leverage powerful language models directly within Slack, all managed within an n8n environment.
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