This workflow aims at providing data visualization to a native SQL Agent.
Together, they can help with fostering data analysis and data visualization within a team.
It uses the native SQL Agent that works well and adds some visualization capabilities thanks to OpenAI Structured Output and Quickchart.io.
How it works
The first part of the workflow is a regular SQL Agent: it connects to a Database and is able to query it and translate the response in a human format.
Then, the Text Classifier is deciding if the user would benefit from a chart, supporting the SQL Agent's response.
If it does, then it executes the subworkflow to dynamically generate a chart and append the chart to the response from the SQL Agent.
If it doesn't, then the SQL Agent response is directly outputted.
The sub-workflow calls OpenAI through the HTTP Request node to retrieve a chart definition.
In the "set response" node, the chart definition is added at the end of a quickchart.io URL - the URL to the chart image. It is sent back to the AI Agent.
How to use it
Use an existing or create a new database.
For example, I've used this Kaggle dataset and uploaded it to a Supabase DB.
Add the PostgreSQL or MySQL credentials.
Alternatively, you can use SQLite binary files (check this template).
Activate the workflow.
Start chatting with the AI SQL Agent.
If the Text Classifier considers a chart would be useful, it will generate a chart in addition to the response from the SQL Agent.
Notes
The full Quickchart.io specifications have not been integrated, thus there are some possible glitches (e.g., due to the size of the graph, radar graphs are not displayed properly).
Task:
Create a simple API endpoint using the Webhook and Respond to Webhook nodes
Why:
You can prototype or replace a backend process with a single workflow
Main use cases:
Replace backend logic with a workflow
Task:
Merge two datasets into one based on matching rules
Why:
A powerful capability of n8n is to easily branch out the workflow in order to process different datasets. Even more powerful is the ability to join them back together with SQL-like joining logic.
Main use cases:
Appending data sets
Keep only new items
Keep only existing items
This workflow will backup your workflows to Github. It uses the public api to export all of the workflow data using the n8n node.
It then loops over the data checks in Github to see if a file exists that uses the workflow name. Once checked it will then update the file on Github if it exists, Create a new file if it doesn't exist and if it's the same it will ignore the file.
Config Options
repo_owner - Github owner
repo_name - Github repository name
repo_path - Path within the Github repository
>This workflow has been updated to use the n8n node and the code node so requires at least version 0.198.0 of n8n
This creates a git backup of the workflows and credentials.
It uses the n8n export command with git diff, so you can run as many times as you want, but only when there are changes they will create a commit.
Setup
You need some access to the server.
Create a repository in some remote place to host your project, like Github, Gitlab, or your favorite private repo.
Clone the repository in the server in a place that the n8n has access. In the example, it's the ., and the repository name is repo. Change it in the commands and in the workflow commands (you can set it as a variable in the wokflow). Checkout to another branch if you won't use the master one.
cd .
git clone repository
Or you could git init and then add the remote (git remote add origin YOUR_REPO_URL), whatever pleases you more.
As the server, check if everything is ok for beeing able to commit. Very likely you'll need to setup the user email and name. Try to create a commit, and push it to upstream, and everything you need (like config a user to comit) will appear in way. I strong suggest testing with exporting the commands to garantee it will work too.
cd ./repo
git commit -c "Initial commmit" --allow-empty
-u is the same as --set-upstream
git push -u origin master
Testing to push to upstream with the first exported data
npx n8n export:workflow --backup --output ./repo/workflows/
npx n8n export:credentials --backup --output repo/credentials/
cd ./repo
git add .
git commit -c "manual backup: first export"
git push
After that, if everything is ok, the workflow should work just fine.
Adjustments
Adjust the path in used in the workflow. See the the git -C PATH command is the same as cd PATH; git ....
Also, adjust the cron to run as you need. As I said in the beginning, you can run it even for every minute, but it will create commits only when there are changes.
Credentials encryption
The default for exporting the credentials is to do them encrypted. You can add the flag --decrypted to the n8n export:credentials command if you need to save them in plain. But as general rule, it's better to save the encryption key, that you only need to do that once, and them export it safely encrypted.
This n8n workflow demonstrates how to build a simple uptime monitoring service using scheduled triggers.
Useful for webmasters with a handful of sites who want a cost-effective solution without the need for all the bells and whistles.
How it works
Scheduled trigger reads a list of website urls in a Google Sheet every 5 minutes
Each website url is checked using the HTTP node which determines if the website is either in the UP or DOWN state.
An email and Slack message are sent for websites which are in the DOWN state.
The Google Sheet is updated with the website's state and a log created.
Logs can be used to determine total % of UP and DOWN time over a period.
Requirements
Google Sheet for storing websites to monitor and their states
Gmail for email alerts
Slack for channel alerts
Customising the workflow
Don't use Google Sheets? This can easily be exchanged with Excel or Airtable.
Using n8n a lot?
Soar above the limitations of the default n8n dashboard! This template gives you an overview of your workflows, nodes, and tags โ all in one place. ๐ช
Built using XML stylesheets and the Bootstrap 5 library, this workflow is self-contained and does not depend on any third-party software. ๐ It generates a comprehensive overview JSON that can be easily integrated with other BI tools for further analysis and visualization. ๐
Reach out to Eduard if you need help adapting this workflow to your specific use-case!
๐ Benefits:
Workflow Summary** ๐: Instant overview of your workflows, active counts, and triggers.
Left-Side Panel** ๐: Quick access to all your workflows, nodes, and tags for seamless navigation.
Workflow Details** ๐ฌ: Deep dive into each workflow's nodes, timestamps, and tags.
Node Analysis** ๐งฉ: Identify the most frequently used nodes across your workflows.
Tag Organization** ๐๏ธ: Workflows are grouped according to their tags.
Visually Stunning** ๐จ: Clean, intuitive, and easy-to-navigate dashboard design.
XML & Bootstrap 5** ๐ ๏ธ: Built using XML stylesheets and Bootstrap 5, ensuring a self-contained and responsive dashboard.
No Dependencies** ๐: The workflow does not rely on any third-party software. Bootstrap 5 files are loaded via CDN but can be delivered directly from your server.
โ ๏ธ Important note for cloud users
Since the cloud version doesn't support environmental variables, please make the following changes:
get-nodes-via-jmespath node. Update the instance_url variable: enter your n8n URL instead of {{$env["N8N_PROTOCOL"]}}://{{$env["N8N_HOST"]}}
Create HTML node. Please provide the n8n instance URL instead of {{ $env.WEBHOOK_URL }}
๐Example:
Check out our other workflows:
n8n.io/creators/eduard
n8n.io/creators/yulia
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.
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.
โ๏ธ๐ ๏ธ๐๐ค๐ฆพ
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** โ 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.
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.
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
This n8n workflow template lets teams easily generate a custom AI chat assistant based on the schema of any Notion database. Simply provide the Notion database URL, and the workflow downloads the schema and creates a tailored AI assistant designed to interact with that specific database structure.
Set Up
Watch this quick set up video ๐
Key Features
Instant Assistant Generation**: Enter a Notion database URL, and the workflow produces an AI assistant configured to the database schema.
Advanced Querying**: The assistant performs flexible queries, filtering records by multiple fields (e.g., tags, names). It can also search inside Notion pages to pull relevant content from specific blocks.
Schema Awareness**: Understands and interacts with various Notion column types like text, dates, and tags for accurate responses.
Reference Links**: Each query returns direct links to the exact Notion pages that inform the assistantโs response, promoting transparency and easy access.
Self-Validation**: The workflow has logic to check the generated assistant, and if any errors are detected, it reruns the agent to fix them.
Ideal for
Product Managers**: Easily access and query product data across Notion databases.
Support Teams**: Quickly search through knowledge bases for precise information to enhance support accuracy.
Operations Teams**: Streamline access to HR, finance, or logistics data for fast, efficient retrieval.
Data Teams**: Automate large dataset queries across multiple properties and records.
How It Works
This AI assistant leverages two HTTP request toolsโone for querying the Notion database and another for retrieving data within individual pages. Itโs powered by the Anthropic LLM (or can be swapped for GPT-4) and always provides reference links for added transparency.