Slack node
Webhook node
+6

IT Ops AI SlackBot Workflow - Chat with your knowledge base

Published 2 months ago

Categories

Template description

ogimageaiwf14x8 1.png

Video Demo:

Click here to see a video of this workflow in action.

Summary Description:

The "IT Department Q&A Workflow" is designed to streamline and automate the process of handling IT-related inquiries from employees through Slack. When an employee sends a direct message (DM) to the IT department's Slack channel, the workflow is triggered. The initial step involves the "Receive DMs" node, which listens for new messages. Upon receiving a message, the workflow verifies the webhook by responding to Slack's challenge request, ensuring that the communication channel is active and secure.

Once the webhook is verified, the workflow checks if the message sender is a bot using the "Check if Bot" node. If the sender is identified as a bot, the workflow terminates the process to avoid unnecessary actions. If the sender is a human, the workflow sends an acknowledgment message back to the user, confirming that their query is being processed. This is achieved through the "Send Initial Message" node, which posts a simple message like "On it!" to the user's Slack channel.

The core functionality of the workflow is powered by the "AI Agent" node, which utilizes the OpenAI GPT-4 model to interpret and respond to the user's query. This AI-driven node processes the text of the received message, generating an appropriate response based on the context and information available. To maintain conversation context, the "Window Buffer Memory" node stores the last five messages from each user, ensuring that the AI agent can provide coherent and contextually relevant answers.

Additionally, the workflow includes a custom Knowledge Base (KB) tool (see that tool template here) that integrates with the AI agent, allowing it to search the company's internal KB for relevant information. After generating the response, the workflow cleans up the initial acknowledgment message using the "Delete Initial Message" node to keep the conversation thread clean. Finally, the generated response is sent back to the user via the "Send Message" node, providing them with the information or assistance they requested. This workflow effectively automates the IT support process, reducing response times and improving efficiency.

To quickly deploy the Knowledge Ninja app in Slack, use the app manifest below and don't forget to replace the two sample urls:

{
    "display_information": {
        "name": "Knowledge Ninja",
        "description": "IT Department Q&A Workflow",
        "background_color": "#005e5e"
    },
    "features": {
        "bot_user": {
            "display_name": "IT Ops AI SlackBot Workflow",
            "always_online": true
        }
    },
    "oauth_config": {
        "redirect_urls": [
            "Replace everything inside the double quotes with your slack redirect oauth url, for example: https://n8n.domain.com/rest/oauth2-credential/callback"
        ],
        "scopes": {
            "user": [
                "search:read"
            ],
            "bot": [
                "chat:write",
                "chat:write.customize",
                "groups:history",
                "groups:read",
                "groups:write",
                "groups:write.invites",
                "groups:write.topic",
                "im:history",
                "im:read",
                "im:write",
                "mpim:history",
                "mpim:read",
                "mpim:write",
                "mpim:write.topic",
                "usergroups:read",
                "usergroups:write",
                "users:write",
                "channels:history"
            ]
        }
    },
    "settings": {
        "event_subscriptions": {
            "request_url": "Replace everything inside the double quotes with your workflow webhook url, for example: https://n8n.domain.com/webhook/99db3e73-57d8-4107-ab02-5b7e713894ad",
            "bot_events": [
                "message.im"
            ]
        },
        "org_deploy_enabled": false,
        "socket_mode_enabled": false,
        "token_rotation_enabled": false
    }
}

Share Template

More AI workflow templates

OpenAI Chat Model node
SerpApi (Google Search) node

AI agent chat

This workflow employs OpenAI's language models and SerpAPI to create a responsive, intelligent conversational agent. It comes equipped with manual chat triggers and memory buffer capabilities to ensure seamless interactions. To use this template, you need to be on n8n version 1.50.0 or later.
n8n-team
n8n Team
HTTP Request node
Merge node
+7

Scrape and summarize webpages with AI

This workflow integrates both web scraping and NLP functionalities. It uses HTML parsing to extract links, HTTP requests to fetch essay content, and AI-based summarization using GPT-4o. It's an excellent example of an end-to-end automated task that is not only efficient but also provides real value by summarizing valuable content. Note that to use this template, you need to be on n8n version 1.50.0 or later.
n8n-team
n8n Team
HTTP Request node
Markdown node
+5

AI agent that can scrape webpages

⚙️🛠️🚀🤖🦾 This template is a PoC of a ReAct AI Agent capable of fetching random pages (not only Wikipedia or Google search results). On the top part there's a manual chat node connected to a LangChain ReAct Agent. The agent has access to a workflow tool for getting page content. The page content extraction starts with converting query parameters into a JSON object. There are 3 pre-defined parameters: url** – an address of the page to fetch method** = full / simplified maxlimit** - maximum length for the final page. For longer pages an error message is returned back to the agent Page content fetching is a multistep process: An HTTP Request mode tries to get the page content. If the page content was successfuly retrieved, a series of post-processing begin: Extract HTML BODY; content Remove all unnecessary tags to recude the page size Further eliminate external URLs and IMG scr values (based on the method query parameter) Remaining HTML is converted to Markdown, thus recuding the page lengh even more while preserving the basic page structure The remaining content is sent back to an Agent if it's not too long (maxlimit = 70000 by default, see CONFIG node). NB: You can isolate the HTTP Request part into a separate workflow. Check the Workflow Tool description, it guides the agent to provide a query string with several parameters instead of a JSON object. Please reach out to Eduard is you need further assistance with you n8n workflows and automations! Note that to use this template, you need to be on n8n version 1.19.4 or later.
eduard
Eduard

More IT Ops workflow templates

HTTP Request node
Merge node
+3

Backup n8n workflows to Google Drive

Temporary solution using the undocumented REST API for backups using Google drive. Please note that there are issues with this workflow. It does not support versioning, so please know that it will create multiple copies of the workflows so if you run this daily it will make the folder grow quickly. Once I figure out how to version in Gdrive I'll update it here.
djangelic
Angel Menendez
HTTP Request node
Redis node
+8

Advanced Telegram Bot, Ticketing System, LiveChat, User Management, Broadcasting

A robust n8n workflow designed to enhance Telegram bot functionality for user management and broadcasting. It facilitates automatic support ticket creation, efficient user data storage in Redis, and a sophisticated system for message forwarding and broadcasting. How It Works Telegram Bot Setup: Initiate the workflow with a Telegram bot configured for handling different chat types (private, supergroup, channel). User Data Management: Formats and updates user data, storing it in a Redis database for efficient retrieval and management. Support Ticket Creation: Automatically generates chat tickets for user messages and saves the corresponding topic IDs in Redis. Message Forwarding: Forwards new messages to the appropriate chat thread, or creates a new thread if none exists. Support Forum Management: Handles messages within a support forum, differentiating between various chat types and user statuses. Broadcasting System: Implements a broadcasting mechanism that sends channel posts to all previous bot users, with a system to filter out blocked users. Blocked User Management: Identifies and manages blocked users, preventing them from receiving broadcasted messages. Versatile Channel Handling: Ensures that messages from verified channels are properly managed and broadcasted to relevant users. Set Up Steps Estimated Time**: Around 30 minutes. Requirements**: A Telegram bot, a Redis database, and Telegram group/channel IDs are necessary. Configuration**: Input the Telegram bot token and relevant group/channel IDs. Configure message handling and user data processing according to your needs. Detailed Instructions**: Sticky notes within the workflow provide extensive setup information and guidance. Live Demo Workflow Bot: Telegram Bot Link (Click here) Support Group: Telegram Group Link (Click here) Broadcasting Channel: Telegram Channel Link (Click here) Keywords: n8n workflow, Telegram bot, chat ticket system, Redis database, message broadcasting, user data management, support forum automation
nskha
Nskha
GitHub node
HTTP Request node
Merge node

Backup workflows to GitHub

Note: This workflow uses the internal API which is not official. This workflow might break in the future. The workflow executes every night at 23:59. You can configure a different time bin the Cron node. Configure the GitHub nodes with your username, repo name, and the file path. In the HTTP Request nodes (making a request to localhost:5678), create Basic Auth credentials with your n8n instance username and password.
harshil1712
ghagrawal17

Implement complex processes faster with n8n

red icon yellow icon red icon yellow icon