Block 1 - Run Workflow Manually
- Type / Role
- n8n-nodes-base.manualTrigger - manualTrigger
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
What this template does This workflow builds a 120 minute local date course around your starting point by querying Google Places for nearby spots, selecting the top candidates, fetching real tim...
n8n-nodes-base.manualtrigger, n8n-nodes-base.stickynote, n8n-nodes-base.set, n8n-nodes-base.httprequest, n8n-nodes-base.function, n8n-nodes-base.merge, n8n-nodes-base.slack, n8n-nodes-base.deepl
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by noda.
Original n8n.io sourceπ§© What this template does
This workflow builds a 120-minute local date course around your starting point by querying Google Places for nearby spots, selecting the top candidates, fetching real-time weather data, letting an AI generate a matching emoji, and drafting a friendly itinerary summary with an LLM in both English and Japanese. It then posts the full bilingual plan with a walking route link and weather emoji to Slack.
π₯ Who itβs for
Makers and teams who want a plug-and-play bilingual local itinerary generator with weather awareness β no custom code required.
βοΈ How it works
Trigger β Manual (or schedule/webhook).
Discovery β Google Places nearby search within a configurable radius.
Selection β Rank by rating and pick the top 3.
Weather β Fetch current weather (via OpenWeatherMap).
Emoji β Use an AI model to match the weather with an emoji π€οΈ.
Planning β An LLM writes the itinerary in Markdown (JP + EN).
Route β Compose a Google Maps walking route URL.
Share β Post the bilingual itinerary, route link, and weather emoji to Slack.
π§° Requirements
n8n (Cloud or self-hosted)
Google Maps Platform (Places API)
OpenWeatherMap API key
Slack Bot (chat:write)
LLM provider (e.g., OpenRouter or DeepL for translation)
π Setup (quick)
Open Set β Fields: Config and fill in coords/radius/time limit.
Connect Credentials for Google, OpenWeatherMap, Slack, and your LLM.
Test the workflow and confirm the bilingual plan + weather emoji appear in Slack.
π Customize
Adjust ranking filters (type, min rating).
Modify translation settings (target language or tone).
Change output layout (side-by-side vs separated).
Tune emoji logic or travel mode.
Add error handling, retries, or logging for production use.
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 28 workflow blocks. Download the JSON for the full node graph.
| Workflow | Generate Weather-Based Date Itineraries with Google Places, OpenRouter AI, and Slack |
|---|---|
| Complexity | advanced |
| Nodes | 28 |
| Categories | Personal Productivity, Multimodal AI |
| Author | noda |
| Published | 28 Oct 2025 |
Use the JSON export at /data/workflows/10232/10232.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
What this template does This workflow builds a 120 minute local date course around your starting point by querying Google Places for nearby spots, selecting the top candidates, fetching real tim...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Personal Productivity, Multimodal AI use case.