IT Ops AI Slack Workflow - knowledge base chat
Explore this Workflow. Built for next generation AI app & agent building.
Summary Description:
The "IT Department Q&A Workflow" streamlines and automates the process of handling IT-related inquiries from employees via Slack. When an employee sends a direct message (DM) to the IT department's Slack channel, this workflow is triggered. First, the "Receive DMs" node listens for new messages, and upon receiving one, the workflow verifies the webhook by responding to Slack's challenge request to ensure secure communication.
After verifying the webhook, the workflow checks if the sender is a bot using the "Check if Bot" node. If the sender is identified as a bot, the workflow stops to avoid unnecessary actions. If the sender is a human, an acknowledgment message, such as "On it!" is sent to the user via the "Send Initial Message" node to confirm receipt of their query.
The core functionality is handled by the "AI Agent" node, which utilizes the OpenAI GPT-4 model to interpret and respond to the user's question. To maintain context, the "Window Buffer Memory" node stores the last five messages from each user, allowing the AI agent to provide relevant, context-aware answers.
Additionally, the workflow integrates with a custom Knowledge Base (KB) tool (see that tool template here), allowing the AI to search the company's internal KB for information. After generating the response, the workflow removes the initial acknowledgment message with the "Delete Initial Message" node to keep the conversation clean. Finally, the response is sent back to the user through the "Send Message" node, delivering the requested information or assistance. This workflow effectively automates IT support, improving response times and efficiency.
To quickly deploy the Knowledge Ninja app in Slack, use the app manifest below, replacing the two sample URLs:
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