Ai agent with Ollama for current weather and wiki

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This workflow template demonstrates how to create an AI powered agent that provides users with current weather information and Wikipedia summaries. By integrating n8n with Ollama's local Large Lang...

Best for

Personal Productivity automation workflows
AI Chatbot automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.manualchattrigger, @n8n/n8n-nodes-langchain.toolwikipedia, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.toolhttprequest, @n8n/n8n-nodes-langchain.lmchatollama

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Thomas Chan.

Original n8n.io source

1.1 Workflow description

Title: Ai agent with Ollama for current weather and wiki
Workflow name: Ai agent with Ollama for current weather and wiki

This workflow template demonstrates how to create an AI-powered agent that provides users with current weather information and Wikipedia summaries. By integrating n8n with Ollama's local Large Language Models (LLMs), this template offers a seamless and privacy-conscious solution for real-time data retrieval and summarization.

Who is this for?

Developers and Enthusiasts: Individuals interested in building AI-driven workflows without relying on external APIs. Privacy-Conscious Users: Those who prefer processing data locally to maintain control over their information. Educators and Students: Learners seeking hands-on experience with AI integrations and workflow automation.

What problem does this workflow solve?

Accessing up-to-date weather information and concise Wikipedia summaries typically requires multiple API calls to external services, which can raise privacy concerns and incur costs. This workflow addresses these issues by utilizing Ollama's self-hosted LLMs within n8n, enabling users to retrieve and process information locally.

What this workflow does:

User Input Capture: Begins with a chat interface where users can input queries. AI Processing: The input is sent to an AI Agent node configured with Ollama's LLMs, which interprets the query and determines the required actions. Weather Retrieval: For weather-related queries, the workflow fetches current weather data from a specified source. Wikipedia Summarization: For queries seeking information, it retrieves relevant Wikipedia content and generates concise summaries.

Setup:

Install Required Tools: Ollama: Install and run Ollama to manage local LLMs. Configure n8n Workflow: Import the provided workflow template into your n8n instance. Set up the AI Agent node to connect with Ollama's API. Ensure nodes responsible for fetching weather data and Wikipedia content are correctly configured. Run the Workflow: Start the workflow and interact with the chat interface to test various queries.

How to customize this workflow to your needs:

Automate Triggers: Set up scheduled triggers to provide users with regular updates, such as daily weather forecasts or featured Wikipedia articles.

1.2 Logical Blocks

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.

2. Block-by-Block Analysis

Block 1 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 2 - On new manual Chat Message

Type / Role: @n8n/n8n-nodes-langchain.manualChatTrigger - manualChatTrigger
Config choices: Version 1

Block 3 - Wikipedia

Type / Role: @n8n/n8n-nodes-langchain.toolWikipedia - toolWikipedia
Config choices: Version 1

Block 4 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 5 - Sticky Note6

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 6 - Window Buffer Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1

Block 7 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.6

Block 8 - Weather HTTP Request

Type / Role: @n8n/n8n-nodes-langchain.toolHttpRequest - toolHttpRequest
Config choices: Version 1.1

Block 9 - Ollama Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOllama - lmChatOllama
Config choices: Version 1

Block 10 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Ai agent with Ollama for current weather and wiki
Complexity	intermediate
Nodes	10
Categories	Personal Productivity, AI Chatbot
Author	Thomas Chan
Published	18 Feb 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/2931/2931.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

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.

Download workflow JSON Original n8n.io source Personal Productivity workflows AI Chatbot workflows

Frequently asked questions

What does Ai agent with Ollama for current weather and wiki do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

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, AI Chatbot use case.

Thomas Chan

1 workflow

Nodes

n8n-nodes-base.stickynote @n8n/n8n-nodes-langchain.manualchattrigger @n8n/n8n-nodes-langchain.toolwikipedia @n8n/n8n-nodes-langchain.memorybufferwindow @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.toolhttprequest @n8n/n8n-nodes-langchain.lmchatollama

Complexity

intermediate

Published 18 Feb 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/2931/2931.json

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Ai agent with Ollama for current weather and wiki

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Who is this for?

What problem does this workflow solve?

What this workflow does:

Setup:

How to customize this workflow to your needs:

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Sticky Note4

Block 2 - On new manual Chat Message

Block 3 - Wikipedia

Block 4 - Sticky Note3

Block 5 - Sticky Note6

Block 6 - Window Buffer Memory

Block 7 - AI Agent

Block 8 - Weather HTTP Request

Block 9 - Ollama Chat Model

Block 10 - Sticky Note

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions