# Node-red and vs-code integration

**URL:** <https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672>\
**Category:** Dashboard\
**Tags:** node-red-dashboard, function-node, dashboard-2\
**Created:** [17 June 2025 18:37 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672 "2025-06-17T18:37:57Z")\
**Posts on this page:** 9\
**Page:** 3

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**Author:** ![daniel-payne](https://sea2.discourse-cdn.com/flex026/user_avatar/discourse.nodered.org/daniel-payne/32/100479_2.png) [@daniel-payne](https://discourse.nodered.org/u/daniel-payne)\
**Post date:** [29 July 2025 10:59 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672/41 "2025-07-29T10:59:00Z")

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have been a bit snowed under with work, I am just about to do a release that also does On Start and On Stop functions (as have been doing a lot of integration with LangGraph AI). Just want to do a bit more testing, will post here this week.

here is a ref to the work : [AI Agents in Node-Red. This post is an explanation of how to… | by Daniel Payne | Jul, 2025 | Medium](https://daniel-payne-keldan-systems.medium.com/ai-agents-in-node-red-313420a6405b)

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**Author:** ![daniel-payne](https://sea2.discourse-cdn.com/flex026/user_avatar/discourse.nodered.org/daniel-payne/32/100479_2.png) [@daniel-payne](https://discourse.nodered.org/u/daniel-payne)\
**Post date:** [29 July 2025 16:31 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672/42 "2025-07-29T16:31:33Z")

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### **Just upgraded the code base to version 1.0.7**

Added extract and collect for functions

| **Function Node** | **File Name** |
| --- | --- |
| On Start | \*.initialise.js |
| On End | \*.fininalise.js |
| Description | \*.info.md |

Added extract and collect for dashboard 2 templates

| **Template Node** | **File Name** |
| --- | --- |
| Description | \*.info.md |

**Nesting in vs-code**

These are the nesting patterns I add in vs-code to group my node-red files togther

\*.js

`${capture}.test.js, ${capture}.finalize.js, ${capture}.initialize.js, ${capture}.info.md`

\*.vue

`${capture}.test.vue, ${capture}.info.md`

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**Author:** ![gNeandr](https://sea2.discourse-cdn.com/flex026/user_avatar/discourse.nodered.org/gneandr/32/73947_2.png) [@gNeandr](https://discourse.nodered.org/u/gNeandr)\
**Post date:** [29 July 2025 16:35 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672/43 "2025-07-29T16:35:01Z")

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**GREAT!**  
Will go for testing it, but atm I need to setup a new PC. Will come back later.

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**Author:** ![dceejay](https://sea2.discourse-cdn.com/flex026/user_avatar/discourse.nodered.org/dceejay/32/38_2.png) [@dceejay](https://discourse.nodered.org/u/dceejay)\
**Post date:** [29 July 2025 19:14 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672/44 "2025-07-29T19:14:38Z")

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Great article… as it happens - is just what I need next week !

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**Author:** ![joepavitt](https://sea2.discourse-cdn.com/flex026/user_avatar/discourse.nodered.org/joepavitt/32/59722_2.png) [@joepavitt](https://discourse.nodered.org/u/joepavitt)\
**Post date:** [30 July 2025 17:55 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672/45 "2025-07-30T17:55:33Z")

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For what it’s worth, at FlowFuse, we’ve just published a new RAG Blueprint too, which, within the flow, is using LangGraph: [OpenAI RAG Chat Agent • FlowFuse](https://flowfuse.com/blueprints/ai/rag-chat-agent/)

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**Author:** ![TotallyInformation](https://sea2.discourse-cdn.com/flex026/user_avatar/discourse.nodered.org/totallyinformation/32/31_2.png) [@TotallyInformation](https://discourse.nodered.org/u/TotallyInformation)\
**Post date:** [30 July 2025 18:11 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672/46 "2025-07-30T18:11:20Z")

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Interesting. It would be interesting to see a follow-up article using a fully offline model as well. I suspect that this would be even more interesting in many specialist and niche market areas because there are a lot of people who will want and need specialist models where they will want to be totally certain that their data cannot end up in public models.

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**Author:** ![joepavitt](https://sea2.discourse-cdn.com/flex026/user_avatar/discourse.nodered.org/joepavitt/32/59722_2.png) [@joepavitt](https://discourse.nodered.org/u/joepavitt)\
**Post date:** [30 July 2025 18:26 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672/47 "2025-07-30T18:26:11Z")

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The nodes can be fairly “easily” subbed out, as only the OpenAI nodes are the “online” sections. I’ve also been exploring [Transformers.JS](https://huggingface.co/docs/transformers.js/en/index) and [Hugging Face](https://huggingface.co/) models for more offline capabilities in AI generally.

We are also about to ship (tomorrow) the [autocomplete functionality](https://www.linkedin.com/feed/update/urn:li:activity:7350912066255237120) in FlowFuse, which runs completely offline and uses a custom-trained model with [Web | onnxruntime](https://onnxruntime.ai/docs/tutorials/web/)

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<div class="post-metadata">

**Author:** ![daniel-payne](https://sea2.discourse-cdn.com/flex026/user_avatar/discourse.nodered.org/daniel-payne/32/100479_2.png) [@daniel-payne](https://discourse.nodered.org/u/daniel-payne)\
**Post date:** [31 July 2025 14:11 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672/48 "2025-07-31T14:11:41Z")

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I have worked for a magic circle law firm, and they definitely don’t want to go out to the public web. I use OLLAMA a lot locally

if you use Langchain; use this instead in your function

```auto
// npm install @langchain/ollama @langchain/core @langchain/langgraph @langchain/community

const { ChatOllama } = require("@langchain/ollama");
const { BufferWindowMemory } = require("@langchain/community/memory");
const { ConversationChain } = require("langchain/chains");

// Define the LLM for the agent to use
const model = new ChatOllama({
    model: "llama3.1", // or your preferred Ollama model
    temperature: 0,
    baseUrl: "http://localhost:11434" // default Ollama endpoint
});

// Initialize memory with a window of 5 previous messages
const memory = new BufferWindowMemory({
    k: 5, // Keep last 5 exchanges
    returnMessages: true,
});

// Create the conversation chain
const chain = new ConversationChain({
    llm: model,
    memory: memory,
});

this.context.set('chain', chain);

```

if you are using the endpoint in HTTP, here are the endpoints in CURL, dont forget (i sometimes do) to PULL the model first using `ollama pull <MODEL_NAME>`

```auto
curl http://localhost:11434/api/generate -d '{
  "model": "llama3.2",
  "prompt": "Compose a poem on LLMs",
  "stream": false
}'

```

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<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/flex026/uploads/nodered/original/1X/d073cd938eafa2e558d7c2cd59003b3ef4963033.png) [@system](https://discourse.nodered.org/u/system)\
**Post date:** [30 August 2025 14:11 UTC](https://discourse.nodered.org/t/node-red-and-vs-code-integration/97672/49 "2025-08-30T14:11:46Z")

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Closed on 30 August 2025 14:11 UTC

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