Automate Fun Activity Suggestions with n8n and OpenAI

This unique n8n workflow automates suggesting personalized activities by combining OpenAI’s GPT-4o-mini model with the Bored API. It solves the problem of coming up with new activity ideas quickly, saving users time and helping break boredom.
chatTrigger
lmChatOpenAi
agent
+7
Workflow Identifier: 2452
NODES in Use: chatTrigger, lmChatOpenAi, memoryBufferWindow, executeWorkflowTrigger, informationExtractor, httpRequest, toolWorkflow, aggregate, set, agent

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1. Opening Problem Statement

Meet Sarah, a community manager who regularly hosts virtual gatherings and workshops. She often faces a common challenge — suggesting engaging activities that suit different group sizes and interests. Coming up with new ideas each time consumes hours and slows down her planning process. Constantly searching various websites and forums leads to inconsistent quality and mismatched suggestions, sometimes causing participants to lose interest.

This is exactly where our n8n workflow shines. It helps Sarah automate the process of generating personalized and relevant activity ideas instantly, saving her precious time and enhancing participant engagement.

2. What This Automation Does

When this workflow runs, it uses an interactive AI agent powered by OpenAI’s GPT-4o-mini to understand user requests and call a custom-built sub-workflow tool that fetches suggestions from the Bored API. Here’s what happens specifically:

  • Automatic chat trigger: User messages like “I’m bored, suggest something to do” activate the workflow.
  • AI understanding: The AI agent processes the chat input, identifies the type of activity and the number of participants using an information extraction node.
  • Custom tool call: The sub-workflow uses the Bored API to fetch real activity ideas matching user preferences.
  • Aggregated response: The workflow combines API results and formats them into a clear suggestion.
  • Context retention: Memory nodes help the AI keep track of conversation context for future interactions.
  • Interactive chat experience: Users get prompt, relevant activity ideas on demand.

Overall, this automation can save multiple hours per week typically spent brainstorming and researching activities, and it consistently delivers quality, tailored suggestions.

3. Prerequisites ⚙️

  • n8n account (cloud or self-hosted) 🔌
  • OpenAI account with API key for GPT-4o-mini access 🔑
  • No additional external services needed beyond the free Bored API
  • Basic familiarity with n8n interface for workflow import and credential setup

For those considering self-hosting, platforms like Hostinger offer seamless options.

4. Step-by-Step Guide

Step 1: Import the Workflow into n8n

In your n8n dashboard, click on WorkflowsImport and upload the provided JSON file. You should see the workflow named “AI agent using custom tool” loaded with multiple nodes connected.

Common mistake: Forgetting to import all nodes can break connections, so ensure full import.

Step 2: Set OpenAI API Credentials

Navigate to SettingsAPI Credentials, add a new credential for OpenAI. Paste your API key and save.

Visual: The “OpenAI Chat Model” and “OpenAI Chat Model1” nodes will display credential assignment fields.

Common mistake: Using invalid or expired keys will cause authentication errors.

Step 3: Understand the Trigger – “When chat message received”

This is a Chat Trigger node from n8n’s Langchain integrations. It listens for chat messages via webhook. Copy the webhook URL and set it up in your chatbot front-end or testing tool.

Expected: Upon sending the message, the workflow auto-starts.

Step 4: AI Agent Node Setup

The “AI Agent” node coordinates the AI model, memory, and tools. It is connected to:

  • “OpenAI Chat Model” node running GPT-4o-mini.
  • “Simple Memory” node which stores conversation context.
  • “Activity Tool” node — a tool workflow representing the sub-workflow that calls the Bored API.

Common mistake: Disconnecting these nodes will break AI agent functionality.

Step 5: Sub-Workflow “Activity Tool” Explained

This tool is actually the same main workflow but called as a sub-workflow. It receives input, extracts activity preferences, calls the Bored API, aggregates results, and returns suggestions.

Step 6: Information Extractor Node Configuration

Named “Work out activity type and number of people1,” this node extracts:

  • Type of activity desired (e.g., educational, recreational).
  • Number of participants.

This extraction is based on a JSON schema specified inside the node, ensuring data accuracy.

Step 7: HTTP Request to Bored API

The “Call the API” HTTP Request node sends a GET request to:

https://bored-api.appbrewery.com/filter with query parameters:

  • type = extracted activity type
  • participants = extracted participant count

Note: There is a typo in the query parameter name in the JSON: “participicants” which should be corrected to “participants” to work correctly.

Step 8: Aggregating and Formatting API Response

The “Combine” aggregate node gathers the API’s response activity data which is then passed to a “Set ‘response’ value” node that formats it as a single string for output.

Step 9: Chat Output Displays the Activity Suggestion

The AI Agent sends the formatted suggestion back through its chat interface to the user, completing the request cycle.

5. Customizations ✏️

  • Change AI Model: In the OpenAI Chat Model nodes, select a different GPT model like GPT-4o or GPT-3.5-turbo. This modifies response style and complexity.
  • Add More Activity Types: Edit the JSON schema in the Information Extractor node to recognize additional activity categories.
  • Expand API Sources: Replace or supplement the Bored API HTTP node with other activity suggestion APIs for richer variety.
  • Adjust Memory Capacity: Tweak the Simple Memory node settings to remember longer chat histories for more context-aware suggestions.
  • Modify Response Formatting: In the Set node, customize how suggestions are presented, add emojis or additional info.

6. Troubleshooting 🔧

Problem: “HTTP Request node returns empty or error response.”
Cause: Typo in query parameter or API downtime.
Solution: Fix the “participicants” parameter to “participants” in the HTTP Request node. Test API URL independently.

Problem: “AI Agent does not respond to chat messages.”
Cause: Webhook URL not configured properly or credentials missing.
Solution: Verify webhook is active, test messages trigger the workflow. Confirm OpenAI API key is set and valid.

7. Pre-Production Checklist ✅

  • Verify OpenAI API credentials are connected in all nodes requiring them.
  • Test chat trigger webhook by sending a sample message: “Hi! Please suggest something to do. I feel like learning something new.”
  • Ensure the sub-workflow calls return valid activity ideas from the Bored API.
  • Check that the AI Agent returns coherent, context-aware responses.
  • Backup your workflow export before deployment for quick rollback.

8. Deployment Guide

Activate the workflow by setting it live in your n8n environment. Connect your chat interface’s webhook to the “When chat message received” node’s webhook URL. Monitor usage logs in n8n for errors or rate limits.

For long-term use, consider setting alerts for API quota limits and periodically update OpenAI credentials as needed.

9. FAQs

Q: Can I use an alternative AI model instead of GPT-4o-mini?
A: Yes, n8n supports multiple OpenAI models. You can select any supported model in the “OpenAI Chat Model” nodes.

Q: Does calling the Bored API cost money?
A: No, the Bored API is free to use and does not require authentication.

Q: Is user data secure in this workflow?
A: Yes, all data flows securely within n8n environment and credentials are stored safely using n8n’s built-in secrets management.

10. Conclusion

By following this guide, you have implemented a powerful AI-driven activity suggestion bot using n8n and OpenAI. This workflow harnesses natural language understanding and a real-time activity API to generate personalized ideas that break boredom instantly. Sarah and many others will save hours weekly, reduce planning stress, and keep their communities engaged effortlessly.

Next steps could be expanding this bot to support event reminders, integrating calendar nodes, or creating a knowledge base for richer conversation context.

Keep experimenting with your automation journey — you’re building a smarter, more interactive future for your users!

Promoted by BULDRR AI

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