Back to Integrations
integrationWebhook node
integrationBaserow node

Webhook and Baserow integration

Save yourself the work of writing custom integrations for Webhook and Baserow and use n8n instead. Build adaptable and scalable Development, Core Nodes, and Data & Storage workflows that work with your technology stack. All within a building experience you will love.

How to connect Webhook and Baserow

  • 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.

Webhook and Baserow integration: Create a new workflow and add the first step

Step 2: Add and configure Webhook and Baserow nodes

You can find Webhook and Baserow 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 Webhook and Baserow nodes one by one: input data on the left, parameters in the middle, and output data on the right.

Webhook and Baserow integration: Add and configure Webhook and Baserow nodes

Step 3: Connect Webhook and Baserow

A connection establishes a link between Webhook and Baserow (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.

Webhook and Baserow integration: Connect Webhook and Baserow

Step 4: Customize and extend your Webhook and Baserow 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 Webhook and Baserow with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

Webhook and Baserow integration: Customize and extend your Webhook and Baserow integration

Step 5: Test and activate your Webhook and Baserow workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Webhook to Baserow 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.

Webhook and Baserow integration: Test and activate your Webhook and Baserow workflow

All-in-One Telegram/Baserow AI Assistant 🤖🧠 Voice/Photo/Save Notes/Long Term Mem

Telegram Personal Assistant with Long-Term Memory & Note-Taking

This n8n workflow transforms your Telegram bot into a powerful personal assistant that handles voice, photo, and text messages. The assistant uses AI to interpret messages, save important details as long-term memories or notes in a Baserow database, and recall information for future interactions.

🌟 How It Works

Message Reception & Routing
Telegram Integration: The workflow is triggered by incoming messages on your Telegram bot.
Dynamic Routing: A switch node inspects the message to determine whether it's voice, text, or photo (with captions) and routes it for the appropriate processing.

Content Processing
Voice Messages: Audio files are retrieved and sent to an AI transcription node to convert spoken words into text.
Text Messages: Text is directly captured and prepared for analysis.
Photos: If an image is received, the bot fetches the file (and caption, if provided) and uses an AI-powered image analysis node to extract relevant details.

AI-Powered Agent & Memory Management
The core AI agent (powered by GPT-4o-mini) processes the incoming message along with any previous conversation history stored in PostgreSQL memory buffers.
Long-Term Memory: When a message contains personal or noteworthy information, the assistant uses a dedicated tool to save this data as a long-term memory in Baserow.
Note-Taking: For specific instructions or reminders, the assistant saves concise notes in a separate Baserow table.
The AI agent follows defined rules to decide which details are saved as memories and which are saved as notes.

Response Generation
After processing the message and updating memory/notes as needed, the AI agent crafts a contextual and personalized response.
The response is sent back to the user via Telegram, ensuring smooth and natural conversation flow.

🚀 Key Features

Multimodal Input:**
Seamlessly handles voice, photo (with captions), and text messages.

Long-Term Memory & Note-Taking:**
Uses a Baserow database to store personal details and notes, enhancing conversational context over time.

AI-Driven Contextual Responses:**
Leverages an AI agent to generate personalized, context-aware replies based on current input and past interactions.

User Security & Validation:**
Incorporates validation steps to verify the user's Telegram ID before processing, ensuring secure and personalized interactions.

Easy Baserow Setup:**
Comes with a clear setup guide and sample configurations to quickly integrate Baserow for managing memories and notes.

🔧 Setup Guide

Telegram Bot Setup:
Create your bot via BotFather and obtain the Bot Token.
Configure the Telegram webhook in n8n with your bot's token and URL.

Baserow Database Configuration:
Memory Table:
Create a workspace titled "Memories and Notes".
Set up a table (e.g., "Memory Table") with at least two fields:
Memory (long text)
Date Added (US date format with time)
Notes Table:
Duplicate the Memory Table and rename it to "Notes Table".
Change the first field's name from "Memory" to "Notes".

n8n Workflow Import & Configuration:
Import the workflow JSON into your n8n instance.
Update credentials for Telegram, Baserow, OpenAI, and PostgreSQL (for memory buffering) as needed.
Adjust node settings if you need to customize AI agent prompts or memory management rules.

Testing & Deployment:
Test your bot by sending various message types (text, voice, photo) to confirm that the workflow processes them correctly, updates Baserow, and returns the appropriate response.
Monitor logs to ensure that memory and note entries are correctly stored and retrieved.

✨ Example Interactions

Voice Message Processing:**
User sends a voice note requesting a reminder.
Bot Response: "Thanks for your message! I've noted your reminder and saved it for future reference."

Photo with Caption:**
User sends a photo with the caption "Save this recipe for dinner ideas."
Bot Response: "Got it! I've saved this recipe along with the caption for you."

Text Message for Memory Saving:**
User: "I love hiking on weekends."
Bot Response: "Noted! I’ll remember your interest in hiking."

Retrieving Information:**
User asks: "What notes do I have?"
Bot Response: "Here are your latest notes: [list of saved notes]."

🛠️ Resources & Next Steps

Telegram Bot Configuration:** Telegram BotFather Guide
n8n Documentation:** n8n Docs
Community Forums:** Join discussions and share your customizations!

This workflow not only streamlines message processing but also empowers users with a personal AI assistant that remembers details over time. Customize the rules and responses further to fit your unique requirements and enjoy a more engaging, intelligent conversation experience on Telegram!

Nodes used in this workflow

Popular Webhook and Baserow workflows

+2

All-in-One Telegram/Baserow AI Assistant 🤖🧠 Voice/Photo/Save Notes/Long Term Mem

Telegram Personal Assistant with Long-Term Memory & Note-Taking This n8n workflow transforms your Telegram bot into a powerful personal assistant that handles voice, photo, and text messages. The assistant uses AI to interpret messages, save important details as long-term memories or notes in a Baserow database, and recall information for future interactions. 🌟 How It Works Message Reception & Routing Telegram Integration: The workflow is triggered by incoming messages on your Telegram bot. Dynamic Routing: A switch node inspects the message to determine whether it's voice, text, or photo (with captions) and routes it for the appropriate processing. Content Processing Voice Messages: Audio files are retrieved and sent to an AI transcription node to convert spoken words into text. Text Messages: Text is directly captured and prepared for analysis. Photos: If an image is received, the bot fetches the file (and caption, if provided) and uses an AI-powered image analysis node to extract relevant details. AI-Powered Agent & Memory Management The core AI agent (powered by GPT-4o-mini) processes the incoming message along with any previous conversation history stored in PostgreSQL memory buffers. Long-Term Memory: When a message contains personal or noteworthy information, the assistant uses a dedicated tool to save this data as a long-term memory in Baserow. Note-Taking: For specific instructions or reminders, the assistant saves concise notes in a separate Baserow table. The AI agent follows defined rules to decide which details are saved as memories and which are saved as notes. Response Generation After processing the message and updating memory/notes as needed, the AI agent crafts a contextual and personalized response. The response is sent back to the user via Telegram, ensuring smooth and natural conversation flow. 🚀 Key Features Multimodal Input:** Seamlessly handles voice, photo (with captions), and text messages. Long-Term Memory & Note-Taking:** Uses a Baserow database to store personal details and notes, enhancing conversational context over time. AI-Driven Contextual Responses:** Leverages an AI agent to generate personalized, context-aware replies based on current input and past interactions. User Security & Validation:** Incorporates validation steps to verify the user's Telegram ID before processing, ensuring secure and personalized interactions. Easy Baserow Setup:** Comes with a clear setup guide and sample configurations to quickly integrate Baserow for managing memories and notes. 🔧 Setup Guide Telegram Bot Setup: Create your bot via BotFather and obtain the Bot Token. Configure the Telegram webhook in n8n with your bot's token and URL. Baserow Database Configuration: Memory Table: Create a workspace titled "Memories and Notes". Set up a table (e.g., "Memory Table") with at least two fields: Memory (long text) Date Added (US date format with time) Notes Table: Duplicate the Memory Table and rename it to "Notes Table". Change the first field's name from "Memory" to "Notes". n8n Workflow Import & Configuration: Import the workflow JSON into your n8n instance. Update credentials for Telegram, Baserow, OpenAI, and PostgreSQL (for memory buffering) as needed. Adjust node settings if you need to customize AI agent prompts or memory management rules. Testing & Deployment: Test your bot by sending various message types (text, voice, photo) to confirm that the workflow processes them correctly, updates Baserow, and returns the appropriate response. Monitor logs to ensure that memory and note entries are correctly stored and retrieved. ✨ Example Interactions Voice Message Processing:** User sends a voice note requesting a reminder. Bot Response: "Thanks for your message! I've noted your reminder and saved it for future reference." Photo with Caption:** User sends a photo with the caption "Save this recipe for dinner ideas." Bot Response: "Got it! I've saved this recipe along with the caption for you." Text Message for Memory Saving:** User: "I love hiking on weekends." Bot Response: "Noted! I’ll remember your interest in hiking." Retrieving Information:** User asks: "What notes do I have?" Bot Response: "Here are your latest notes: [list of saved notes]." 🛠️ Resources & Next Steps Telegram Bot Configuration:** Telegram BotFather Guide n8n Documentation:** n8n Docs Community Forums:** Join discussions and share your customizations! This workflow not only streamlines message processing but also empowers users with a personal AI assistant that remembers details over time. Customize the rules and responses further to fit your unique requirements and enjoy a more engaging, intelligent conversation experience on Telegram!

Convert Baserow rich text markdown field to HTML

Sometimes you need the rich text field to be in HTML instead of Markdown. This template either syncs a single record or all records at once. Youtube tutorial

User Enablement Demo

This workflow was originally presented at the February 2022 n8n Meetup. Requirements In order to use this workflow, you will need the following in place: A configured Baserow account A group in Baserow called User Empowerment Demo A database in the User Empowerment Demo called Office Shopping List Inside the Office Shopping List database, you will need two tables: Shopping List: Column 1 - Single line text column named Item Shopper: Column 1 - Single line text column named Name Column 2 - Email column named Email An email account for sending out alerts Customization To make this workflow work for you, please customize the following items: All Baserow nodes will need to be updated with your own credentials, database, tables and fields The Send Shopping List node will need to be configured with your email credentials and email addresses The Create Shopper Form Set node will need to have the code in the HTML value modified to reflect your Production URL from the Submit Shopper node (See instructions below) The Cron node will need to be modified to reflect the timing that you wish to use Modifying the Webform The webform is the piece that people normally want to customize but is often the most complex because it is raw HTML. Here are some quick tips for making changes to the form. Webform Nodes There are two nodes that control what you see in the form: Create Shopper Form - displays the form and submits it to the correct webhook Create Response Page - displays the results when the form is submitted Editing the Webform The easiest way that I have found to edit the webform is to: Open up the Set node (Create Shopper Form or Create Response Page) that contains the HTML you wish to edit. Copy the contents of the HTML value to your favourite HTML editor Make your changes Paste the updated HTML back into the Set node Changing the Webhook URL the Webform Posts To In order for the webform to work properly, do the following: Determine the Production URL for the Submit Shopper webhook node In the Create Shopper Form node, look for the following line in the HTML value: form action="https://tephlon.app.n8n.cloud/webhook/submit-shopper" method="POST" Replace https://tephlon.app.n8n.cloud/webhook/submit-shopper with your Production URL Changing the Webform Image The image that is in the webform is actually embedded in the HTML in each of the Create Shopper Form or Create Response Page Set nodes and can be modified from there using these steps: Open up the appropriate Set node In the HTML value, find the line that starts with background-image:. It will be followed by a long string that looks like random characters Using a tool like Image to Base64 Converter, upload your image and generate a new CSS background source Replace the original background-image: line (including all the "random" characters) with the new generated CSS background source

Build your own Webhook and Baserow integration

Create custom Webhook and Baserow 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.

Baserow supported actions

Create
Create a row
Delete
Delete a row
Get
Retrieve a row
Get Many
Retrieve many rows
Update
Update a row

Webhook and Baserow integration details

integrationWebhook node
Webhook

Webhooks are automatic notifications that apps send when something occurs. They are sent to a certain URL, which is effectively the app's phone number or address, and contain a message or payload. Polling is nearly never quicker than webhooks, and it takes less effort from you.

Use case

Save engineering resources

Reduce time spent on customer integrations, engineer faster POCs, keep your customer-specific functionality separate from product all without having to code.

Learn more

FAQs

  • Can Webhook connect with Baserow?

  • Can I use Webhook’s API with n8n?

  • Can I use Baserow’s API with n8n?

  • Is n8n secure for integrating Webhook and Baserow?

  • How to get started with Webhook and Baserow integration in n8n.io?

Need help setting up your Webhook and Baserow integration?

Discover our latest community's recommendations and join the discussions about Webhook and Baserow integration.
Benjamin Hatton
Albert Ashkhatoyan
Víctor González
Salomão
sg tech

Looking to integrate Webhook and Baserow in your company?

Over 3000 companies switch to n8n every single week

Why use n8n to integrate Webhook with Baserow

Build complex workflows, really fast

Build complex workflows, really fast

Handle branching, merging and iteration easily.
Pause your workflow to wait for external events.

Code when you need it, UI when you don't

Simple debugging

Your data is displayed alongside your settings, making edge cases easy to track down.

Use templates to get started fast

Use 1000+ workflow templates available from our core team and our community.

Reuse your work

Copy and paste, easily import and export workflows.

Implement complex processes faster with n8n

red iconyellow iconred iconyellow icon