Build an AI-Powered Slack Bot with NeurochainAI & Make: Low-Code Knowledge Required

In this guide, we’ll walk you through the steps to create a simple yet powerful AI-powered Slack bot using NeurochainAI and Make. This bot will automatically read messages in a public Slack channel, send them to NeurochainAI for processing, and post back AI-generated replies in real-time. Whether you're automating team communication or enhancing your Slack experience, this bot is a great starting point for integrating AI into your workflows. Let's dive into the setup!

Step 1: Monitor Slack Messages

Add the Slack - Watch Public Channel Messages Module:some text

1. • Drag the Slack - Watch Public Channel Messages module to your scenario.

     • Connect Your Slack Account: Follow the prompts to authorize Make to access your Slack workspace.

     • Select the Channel: Choose the channel you want the bot to monitor for new messages.

Whenever a new message is posted in the selected channel, this module will trigger the workflow and pass the message data to the next step.

Step 2: Process the Message with NeurochainAI

Next, use the HTTP Request module to send the captured message to NeurochainAI for processing.

1. Add the HTTP Request Module:some text

   • Drag the HTTP Request module into your scenario.

2. Configure the HTTP Request Module:some text

   • Method: POST

   • URL: ncmb.neurochain.io/tasks/message

3. Headers: Add the required headers for authentication and data format:some text

   • Name: Authorization
     Value: Bearer YOUR-API-KEY-HERE
     (Replace YOUR-API-KEY-HERE with your actual NeurochainAI API key.)

   • Name: Content-Type
     Value: application/json

4. Body Type: Select RAW.

Request Content: Use the following JSON payload:
{

"model": "Meta-Llama-3.1-8B-Instruct-Q6_K.gguf",

"prompt": "You must respond directly to the user's message, and the message the user sent you is the following message: {{4.text}}",

"max_tokens": 1024,

"temperature": 0.6,

"top_p": 0.95,

"frequency_penalty": 0,

"presence_penalty": 1.1

}

5. some text

   • Replace {{4.text}} with the variable corresponding to the message text from the Slack Trigger module. Use Make’s drag-and-drop mapping feature to link this dynamically.

6. Enable Parse Response:some text

   • Activate the Parse Response option in the HTTP Request module settings.

   • This ensures that NeurochainAI’s JSON response is automatically processed, allowing you to map the output easily in the next step.

Step 3: Send the AI-Generated Response Back to Slack

Now, use the Slack - Create a Message module to post NeurochainAI’s response back to the Slack channel.

1. Add the Slack - Create a Message Module:some text

   • Drag this module into your scenario.

2. Configure the Module:some text

   • Connect Your Slack Account: Use the same account connection as the trigger module.

   • Select the Channel: Choose the same channel monitored in Step 1.

Text Field: Map the AI-generated response to this field. Typically, it will look like this:

{{10.data.choices[].text}}

Once configured, this module will send NeurochainAI’s response to the Slack channel as a message.

How the Slack AI Bot Works

When the scenario runs:

1. Slack messages posted in the monitored channel trigger the workflow.

2. The HTTP Request module sends the message to NeurochainAI for processing.

3. NeurochainAI generates a response based on the message and sends it back.

4. The Slack module posts the AI-generated response in the same channel.

Happy Creation!