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integrationGoogle Gemini Chat Model node
integrationSlack node

Google Gemini Chat Model and Slack integration

Save yourself the work of writing custom integrations for Google Gemini Chat Model and Slack and use n8n instead. Build adaptable and scalable AI, Langchain, and Communication workflows that work with your technology stack. All within a building experience you will love.

How to connect Google Gemini Chat Model and Slack

  • Step 1: Create a new workflow
  • Step 2: Add and configure nodes
  • Step 3: Connect
  • Step 4: Customize and extend your integration
  • Step 5: Test and activate your workflow

Step 1: Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

Google Gemini Chat Model and Slack integration: Create a new workflow and add the first step

Step 2: Add and configure Google Gemini Chat Model and Slack nodes

You can find Google Gemini Chat Model and Slack in the nodes panel. Drag them onto your workflow canvas, selecting their actions. Click each node, choose a credential, and authenticate to grant n8n access. Configure Google Gemini Chat Model and Slack nodes one by one: input data on the left, parameters in the middle, and output data on the right.

Google Gemini Chat Model and Slack integration: Add and configure Google Gemini Chat Model and Slack nodes

Step 3: Connect Google Gemini Chat Model and Slack

A connection establishes a link between Google Gemini Chat Model and Slack (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.

Google Gemini Chat Model and Slack integration: Connect Google Gemini Chat Model and Slack

Step 4: Customize and extend your Google Gemini Chat Model and Slack integration

Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect Google Gemini Chat Model and Slack with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

Google Gemini Chat Model and Slack integration: Customize and extend your Google Gemini Chat Model and Slack integration

Step 5: Test and activate your Google Gemini Chat Model and Slack workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Google Gemini Chat Model to Slack or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.

Google Gemini Chat Model and Slack integration: Test and activate your Google Gemini Chat Model and Slack workflow

Creating a AI Slack Bot with Google Gemini

This is an example of how we can build a slack bot in a few easy steps

Before you can start, you need to o a few things

Create a copy of this workflow
Create a slack bot
Create a slash command on slack and paste the webhook url to the slack command

Note
Make sure to configure this webhook using a https:// wrapper and don't use the default http://localhost:5678 as that will not be recognized by your slack webhook.

Once the data has been sent to your webhook, the next step will be passing it via an AI Agent to process data based on the queries we pass to our agent.

To have some sort of a memory, be sure to set the slack token to the memory node. This way you can refer to other chats from the history.

The final message is relayed back to slack as a new message. Since we can not wait longer than 3000 ms for slack response, we will create a new message with reference to the input we passed.

We can advance this using the tools or data sources for it to be more custom tailored for your company.

Usage
To use the slackbot, go to slack and click on your set slash command eg /Bob and send your desired message.

This will send the message to your endpoint and get return the processed results as the message.

If you would like help setting this up, feel free to reach out to [email protected]

Nodes used in this workflow

Popular Google Gemini Chat Model and Slack workflows

Creating a AI Slack Bot with Google Gemini

This is an example of how we can build a slack bot in a few easy steps Before you can start, you need to o a few things Create a copy of this workflow Create a slack bot Create a slash command on slack and paste the webhook url to the slack command Note Make sure to configure this webhook using a https:// wrapper and don't use the default http://localhost:5678 as that will not be recognized by your slack webhook. Once the data has been sent to your webhook, the next step will be passing it via an AI Agent to process data based on the queries we pass to our agent. To have some sort of a memory, be sure to set the slack token to the memory node. This way you can refer to other chats from the history. The final message is relayed back to slack as a new message. Since we can not wait longer than 3000 ms for slack response, we will create a new message with reference to the input we passed. We can advance this using the tools or data sources for it to be more custom tailored for your company. Usage To use the slackbot, go to slack and click on your set slash command eg /Bob and send your desired message. This will send the message to your endpoint and get return the processed results as the message. If you would like help setting this up, feel free to reach out to [email protected]

Build your own Google Gemini Chat Model and Slack integration

Create custom Google Gemini Chat Model and Slack workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

Slack supported actions

Archive
Archives a conversation
Close
Closes a direct message or multi-person direct message
Create
Initiates a public or private channel-based conversation
Get
Get information about a channel
Get Many
Get many channels in a Slack team
History
Get a conversation's history of messages and events
Invite
Invite a user to a channel
Join
Joins an existing conversation
Kick
Removes a user from a channel
Leave
Leaves a conversation
Member
List members of a conversation
Open
Opens or resumes a direct message or multi-person direct message
Rename
Renames a conversation
Replies
Get a thread of messages posted to a channel
Set Purpose
Sets the purpose for a conversation
Set Topic
Sets the topic for a conversation
Unarchive
Unarchives a conversation
Get
Get Many
Get & filters team files
Upload
Create or upload an existing file
Delete
Get Permalink
Search
Send
Send and Wait for Approval
Update
Add
Adds a reaction to a message
Get
Get the reactions of a message
Remove
Remove a reaction of a message
Add
Add a star to an item
Delete
Delete a star from an item
Get Many
Get many stars of autenticated user
Get
Get information about a user
Get Many
Get a list of many users
Get User's Profile
Get a user's profile
Get User's Status
Get online status of a user
Update User's Profile
Update a user's profile
Create
Disable
Enable
Get Many
Update

FAQs

  • Can Google Gemini Chat Model connect with Slack?

  • Can I use Google Gemini Chat Model’s API with n8n?

  • Can I use Slack’s API with n8n?

  • Is n8n secure for integrating Google Gemini Chat Model and Slack?

  • How to get started with Google Gemini Chat Model and Slack integration in n8n.io?

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