The n8n team has officially announced: A completely new UI and UX is on the way! 🧠✨And this brings with it some exciting changes: 🆕 What can we expect in concrete terms? ✅ The new Flow Builder UI Editor is getting a fresh, modern design - with a better overview and clearer structure. This makes complex automations much easier to build and understand. ✅ Complete UX redesign is not just about looks - the entire user experience is being overhauled: more intuitive, faster, smarter. Whether you're just starting out or already a power user. ✅ Improved navigation & usabilityThe entire operation is more logical and fluid - from flow management to editing individual nodes. ✅ More speed & efficiencyThe new version is also designed to improve technical performance - a real boost, especially for large workflows and many active nodes. ⚡

Hi guys I'm either struggling with something dead-simple or near-impossible; I can't seem to figure out how to post a file or an image to model (Gemini or OpenAi or whatever) and interrogate it against a vector store. It's almost exactly the functionality found in ChatGPT's Projects area; you can add a bunch of files which gets turned into the project's vector store and then you can interrogate this vector store via chat alongside file uploads. In a perfect world there would be an agent that has access to a vector store and then pulls a file from Airtable and queries it. I'm not sure if this is possible though; if there other flows that make it happen I'm all ears..

Hi guys I have a general 'how to approach' things question re how best to structure vectorstores (Pinecone in this case): I have a Pinecone Index (knowledge_base) with a namespace in it (called 'docs'). It's constituted of 20+ PDFs that were ingested via an n8n pipeline. All good on that regard. The next step would be to query another handful of PDFs 'against' this index. I can run the same 'ingesting' flow for this query and now have 2 options: 1. Create a new vectorstore (query_1 etc) with these new info 2. Update the same vectorstore with namespace (query_1 etc) I can see on n8n that I can dynamically set either the ID of the index or the namespace of the index so on both counts it should be arbitrary to setup a tool for the query itself; as the tool for the knowledge_base is static and doesn't change. Which route would you suggest? Multiple indexes or one index with multiple namespaces?

Hello. Why can't I add the previous nodes info to create an output in the merge node?

I need to merge the output from one flow to the output of another: the one flow returns multiple items (with an email address) and the other a single item (with an email and an userID). I've tried every option I can think of but it either returns a non-merged output or empty.