Block 1 - OpenAI Chat Model
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
- Config choices
- Version 1.3
Quick overview This workflow checks 48 hour forecasts from Open Meteo for multiple cities on a 6 hour schedule or via an on demand n8n form, scores conditions against courier impact thresholds, use...
@n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.chainllm, @n8n/n8n-nodes-langchain.lmchatgooglegemini, n8n-nodes-base.slack, n8n-nodes-base.code, n8n-nodes-base.form, n8n-nodes-base.switch, n8n-nodes-base.httprequest
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Mychel Garzon.
Original n8n.io sourceThis workflow checks 48-hour forecasts from Open-Meteo for multiple cities on a 6-hour schedule or via an on-demand n8n form, scores conditions against courier-impact thresholds, uses OpenAI (with Google Gemini fallback) to draft Slack-ready alerts, and posts operational updates to a Slack channel.
This workflow was built and tested on a self-hosted n8n instance (Oracle Cloud A1 Flex, Ubuntu 24.04) and is fully compatible with n8n Cloud.
Weather data is sourced exclusively from Open-Meteo (open-meteo.com), an open-source weather API requiring no authentication. Forecast accuracy follows Open-Meteo's standard model ensemble — verify critical alerts against local meteorological services before operational decisions.
Deduplication uses n8n workflow static data (global scope). Clearing static data manually or migrating the workflow to a new instance will reset the deduplication state, causing the next scheduled run to re-evaluate all cities as if no prior alerts have been sent.
The GPT-4o prompt includes city-relative climate context so the model understands that an alert in Nairobi means sustained flooding rain, while an alert in Helsinki means genuinely exceptional conditions beyond the Nordic baseline. This prevents generic alert copy across climatically different markets.
The form trigger is designed for Operations Managers with no technical background — no n8n access required. Share the webhook URL directly and they can force an immediate check from any browser.
Peak delivery windows (11:00-14:00 and 17:00-22:00 local time) are used to escalate severity scoring during high-order-volume periods. Adjust these in the Score + dedup node to match your market's actual peak hours.
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.
| Workflow | Monitor multi-city courier weather risk with Open-Meteo, GPT-4o, Gemini and Slack |
|---|---|
| Complexity | advanced |
| Nodes | 23 |
| Categories | DevOps, AI Summarization |
| Author | Mychel Garzon |
| Published | 21 Jun 2026 |
Use the JSON export at /data/workflows/16535/16535.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.
Quick overview This workflow checks 48 hour forecasts from Open Meteo for multiple cities on a 6 hour schedule or via an on demand n8n form, scores conditions against courier impact thresholds, use...
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 DevOps, AI Summarization use case.