This article provides a complete, practical walkthrough of the Splitout Code Automation Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Automating Daily Yoga Pose Reminders with AI and n8n: The YogiAI Workflow
   
   Meta Description:  
   Discover how YogiAI uses n8n, Google Sheets, and Azure OpenAI to automate personalized daily yoga pose messages via LINE. Learn how this innovative workflow helps you stay centered with consistent practice reminders.
   
   Keywords:  
   YogiAI, n8n workflow, Azure OpenAI, LINE Flex Message, yoga pose reminder, Google Sheets automation, daily yoga tips, AI yoga assistant, structured data parsing, automated messages
   
   Third-Party APIs Used:
   
   - Azure OpenAI API
   - Google Sheets API
   - LINE Messaging API
   
   Article:
   
   In an era where mindfulness and daily self-care routines are more valued than ever, automation technologies step in to help us keep our zen without breaking a sweat. Introducing YogiAI—an AI-powered daily yoga assistant built on n8n, which blends automation with the gentle art of yoga to deliver timely reminders and curated asana lists directly to your LINE messaging app.
   
   Let’s delve into how this intelligent and elegantly constructed workflow supports your yoga journey daily at 9:30 PM sharp.
   
   Anatomy of the YogiAI Workflow
   
   At its core, YogiAI is an automated workflow running on n8n, a powerful node-based automation tool. The workflow is designed to:
   
   1. Retrieve a set of yoga poses from Google Sheets.
   2. Process and enhance the data using Azure OpenAI's GPT model.
   3. Format it into a LINE-friendly Flex Message JSON structure.
   4. Push out visually engaging practice reminders to the user on LINE Messenger.
   5. Log all interactions to Google Sheets for tracking and future content optimization.
   
   ⏰ Scheduled Mindfulness with Precision
   
   The first node in the workflow is a schedule trigger, set to wake up daily at 21:30 (9:30 PM Bangkok Time). This daily execution guarantees consistency in practice—an essential element of yoga.
   
   📄 Pulling Pose Data Smoothly
   
   Using the Google Sheets API, the "Get PoseName" node fetches yoga poses along with their details such as image URLs and external references from a specified range in a shared sheet. This range is manually configured and draws directly from a credible source—PocketYoga.com.
   
   🧠 Natural Language Processing with Azure OpenAI
   
   Once the data is in, multiple Azure OpenAI Chat Model nodes use GPT-4o to do the heavy lifting. These nodes work collaboratively across the workflow to:
   
   - Generate an instructor-like tone for the day’s yoga theme (via WritePosesToday).
   - Add friendly formatting, such as emojis and splits for long messages for LINE chat compatibility (RewritePosesToday).
   - Convert the text into clean JSON structures suitable for LINE’s strict Flex Message format (via WriteJSONflex).
   - Parse and correct any inconsistencies (using Auto-fixing and Structured Output Parser nodes).
   
   💬 Crafting User-Friendly Line Messaging
   
   LINE messaging, known for its engaging "Flex Message" format, requires perfect JSON structures. Depending on the node, GPT formats the bubble structure of Flex messages, which includes:
   
   - Hero image (pose thumbnails),
   - Pose names and variations,
   - Clickable URLs to external pose descriptions.
   
   Through additional logic and parsers, YogiAI ensures the JSON payload adheres strictly to LINE's API requirements.
   
   🧪 Quality Assurance via AI Output Correction
   
   To avoid broken messages or failed API calls, YogiAI employs several LangChain output parser nodes that catch and fix poorly structured JSON. This self-healing mechanism ensures a seamless user experience every evening.
   
   📲 Personalized Delivery with LINE Messaging API
   
   The final combined message—including both motivational text and a pose carousel—is sent as a push message via the LINE Messaging API. The user receives both textual inspiration and clickable pose visuals. All messages are directed using the LINE UID, which can be configured individually.
   
   📊 Intelligent Logging for Continuous Improvement
   
   Post-delivery, the workflow logs two types of data back into Google Sheets:
   
   - The raw JSON and motivational text sent (YogaLog),
   - Each pose’s name and sequence (YogaLog2).
   
   This allows easy tracking of pose frequency, which can be later weighted to favor underutilized poses—adding diversity to practice routines.
   
   A Look Under the Hood: Why It Works
   
   What makes YogiAI brilliant is its modularity combined with intelligent data handling. It fuses AI capabilities with real-time data pipelines and user-friendly interfaces, creating a fully autonomous digital yoga coach.
   
   Not only does it craft engaging daily messages—it also maintains its own logs for constant improvement. By leveraging Azure OpenAI for linguistic generation and parsing, Google Sheets for data persistence, and LINE for end-user interaction, YogiAI stands as a testament to automation's role in lifestyle enhancement.
   
   Final Thoughts
   
   YogiAI goes beyond simple automation—it creates an experience. With just a setup of a few Google Sheets and API credentials, users can receive personalized, compelling yoga guidance every day. For yogis and developers alike, this workflow acts as a blueprint for blending AI, automation, and wellbeing.
   
   If you’re into yoga and tech, it's time to roll out your mat—and roll out this workflow.
   
   🧘 Namaste, with Automation.
   
   — End —

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.