OpenRuna
Sign in
← Workflows

AI Agent with charts capabilities using OpenAI Structured Output

11 nodes · lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent

Engine
n8n
Nodes
11
Trigger
scheduled/triggered
Source file
1112_HTTP_Stickynote_Automation_Webhook.json

Workflow flow

IntegrationsLmChatOpenAiMemoryBufferWindowToolWorkflowExecuteWorkflowHTTPAgentChat@n8n/n8n-nodes-langchain.lmChatOpenAi@n8n/n8n-nodes-langchain.memoryBufferWindow@n8n/n8n-nodes-langchain.toolWorkflowSet@n8n/n8n-nodes-langchain.agent+1 more
100%

OpenAI Chat Model

@n8n/n8n-nodes-langchain.lmChatOpenAi

Window Buffer Memory

@n8n/n8n-nodes-langchain.memoryBufferWindow

Generate a chart

@n8n/n8n-nodes-langchain.toolWorkflow

TRIGGER

Execute "Generate a chart" tool

ExecuteWorkflow

TRIGGER

When chat message received

@n8n/n8n-nodes-langchain.chat

OpenAI - Generate Chart definition with Structured Output

HTTP

AI Agent

@n8n/n8n-nodes-langchain.agent

Set response

Set

8 steps · flows top to bottom, branches left to right

Browse by integration

lmChatOpenAimemoryBufferWindowtoolWorkflowexecuteWorkflowhttpRequestagentchat
Browse all integrations →
Download n8n JSONDownload sanitized JSONDownload flow graph

Import into n8n

  1. Download the n8n JSON file (full or sanitized).
  2. In n8n: Workflows → Import from file.
  3. Open each node and reconnect credentials to your accounts.
  4. Test with manual execution before enabling triggers.

Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.

View source corpus ↗

Overview

Free n8n workflow: AI Agent with charts capabilities using OpenAI Structured Output. 11 nodes across lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent, chat, with a downloadable JSON and a visual flow diagram on OpenRuna.

What this workflow does

This n8n workflow, "AI Agent with charts capabilities using OpenAI Structured Output", wires together lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent, chat in 11 nodes. 11 nodes · lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent A scheduled/triggered entry point kicks it off, and each node passes data to the next until the run completes. OpenRuna renders the node graph and offers the JSON export so you can import and adapt it in minutes. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

  • Fork it to add error handling, retries, or a notification step without designing the 11-node flow from scratch.
  • Benchmark it against your current lmChatOpenAi integration to spot missing steps or redundant nodes.
  • Import "AI Agent with charts capabilities using OpenAI Structured Output" into n8n, reconnect credentials for lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent, chat, and run the same automation in your own workspace.
  • Use it as a starting template when wiring lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent, chat — adjust node parameters to your accounts and record IDs.

Example output

Imported into n8n, "AI Agent with charts capabilities using OpenAI Structured Output" exposes 11 configured nodes. Trigger type: scheduled/triggered. Integrations: lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent, chat. Set your credentials on the lmChatOpenAi node, then verify each downstream node picks them up. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Ask Claude to turn the "AI Agent with charts capabilities using OpenAI Structured Output" JSON into a plain-English runbook, node by node. It can flag where lmChatOpenAi rate limits or missing retries might bite before you go live.

ChatGPT

Drop the workflow JSON or this OpenRuna page URL into ChatGPT and ask for a step-by-step runbook: triggers, branches, and which fields to customise for lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent, chat. Handy for onboarding teammates new to n8n.

Cursor

In Cursor, ask Agent mode to parameterise "AI Agent with charts capabilities using OpenAI Structured Output" — extract lmChatOpenAi IDs and secrets into environment variables without changing the 11-node structure.

Frequently asked questions

How do I import "AI Agent with charts capabilities using OpenAI Structured Output" into n8n?
Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
Which integrations does "AI Agent with charts capabilities using OpenAI Structured Output" use?
It uses: lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent, chat. The flow diagram above shows how each service connects across the 11 nodes. Filter OpenRuna by integration to find related workflows and tools.
Can I import a sanitized export without credentials?
Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own lmChatOpenAi and memoryBufferWindow credentials in n8n after import.
What trigger type does "AI Agent with charts capabilities using OpenAI Structured Output" use?
Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
Is "AI Agent with charts capabilities using OpenAI Structured Output" free to use?
OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for lmChatOpenAi, memoryBufferWindow, toolWorkflow, executeWorkflow, httpRequest, agent, chat.

Related resources