WhatsApp bot: A low-code guide to building your own
Step-by-step guide on building a WhatsApp bot with n8n: from setting up a Meta developer account to designing workflows and testing your bot.
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Google Gemini Chat Model and WhatsApp Business Cloud integration
Save yourself the work of writing custom integrations for Google Gemini Chat Model and WhatsApp Business Cloud 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 WhatsApp Business Cloud
- 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.
Step 2: Add and configure Google Gemini Chat Model and WhatsApp Business Cloud nodes
You can find Google Gemini Chat Model and WhatsApp Business Cloud 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 WhatsApp Business Cloud nodes one by one: input data on the left, parameters in the middle, and output data on the right.
Step 3: Connect Google Gemini Chat Model and WhatsApp Business Cloud
A connection establishes a link between Google Gemini Chat Model and WhatsApp Business Cloud (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.
Step 4: Customize and extend your Google Gemini Chat Model and WhatsApp Business Cloud 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 WhatsApp Business Cloud with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.
Step 5: Test and activate your Google Gemini Chat Model and WhatsApp Business Cloud 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 WhatsApp Business Cloud 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.
Popular Google Gemini Chat Model and WhatsApp Business Cloud workflows
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Respond to WhatsApp Messages with AI Like a Pro!
This n8n template demonstrates the beginnings of building your own n8n-powered WhatsApp chatbot! Under the hood, utilise n8n's powerful AI features to handle different message types and use an AI agent to respond to the user. A powerful tool for any use-case!
How it works
Incoming WhatsApp Trigger provides a way to get messages into the workflow.
The message received is extracted and sent through 1 of 4 branches for processing.
Each processing branch uses AI to analyse, summarize or transcribe the message so that the AI agent can understand it. The supported types are text, image, audio (voice notes) and video.
The AI Agent is used to generate a response generally and uses a wikipedia tool for more complex queries.
Finally, the response message is sent back to the WhatsApp user using the WhatsApp node.
How to use
Once you have setup and configured your WhatsApp account, you'll need to activate your workflow to start processing messages.
Good to know: Large media files may negatively impact workflow performance.
Requirements
WhatsApp Buisness account
Google Gemini for LLM. Gemini is used specifically because it can accept audio and video files whereas at time of writing, many other providers like OpenAI's GPT, do not.
Customising this workflow
For performance reasons, consider detecting large audio and video before sending to the LLM. Pre-processing such files may allow your agent to perform better.
Go beyond and create rich and engagement customer experiences by responding using images, audio and video instead of just text!
Build your own Google Gemini Chat Model and WhatsApp Business Cloud integration
Create custom Google Gemini Chat Model and WhatsApp Business Cloud 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.
Google Gemini Chat Model and WhatsApp Business Cloud integration details
Other integrations with Google Gemini Chat Model
Other integrations with WhatsApp Business Cloud
FAQs
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