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Needless to say I never had to actually say "n8n".
sentinel -> body -> sentinel (condition with backwards edge to first sentinel)
We aimed for feature parity with n8n and improved much of the workflow building experience along the way. We also added what we think agentic workflows needed (mentioned above). Would love your feedback.
- I want to check some input - pick one of your 138 blocks
- I want to extract a list of items from that input
- I want to check which items did I encounter before <- that's the key bit
- Do something for the items that have not been encountered before; bonus point for detecting updated and deleted items
It could be a row added to a CSV file, a list of issues pulled from a repo, or an RSS feed (Yahoo! Pipes, what a sweet memory).
How good is the support for such a case in Sim? And did it get better in n8n?
But the post bills the tool as an n8n alternative. Therefore, I am evaluating it as such. Solid basics before the AI wizzbang.
now, handling an integration to something like google sheets myself for a task this small is a nightmare, not to mention the separate table I'd need to keep to store the access token & refresh token and the permissions I'd need to get from google. on top of that, hosting it somewhere and then monitoring it.
I can't tell you whether it got better in n8n, but I can definitively say that this sounds like a great candidate workflow to build in sim :)
They recently added native tables, albeit still just a few data types, you can store stuff in and use in workflows.
Did you build your own agent engine? Why not LangGraph?
Say I was building a general chat app with LangGraph in the backend (as it provides a lot of infrastructure for highly reliable and interactive agents, all the way up to an API GUIs can use). Could I integrate with this for DIY workflows in a high quality fashion (high-precision updates and control)?
Are there ways to integrate with LangGraph, as in mixing and matching agents (using LangGraph agents in Sim workflows and vice versa)?
Say I’m building a
I do like the way they’ve been able to leverage Langgraph workflows to build agents - it seems like the right abstraction to me - and I also feel their middleware approach is very Django-y which I also like. Are you enjoying their stack?
I’m interested in LangGraph because it seems the closest to an industry standard - every use case seems to be addressed with a tutorial (both first and third party) and there’s an ecosystem of already available graphs/agents. I’m aiming for both high extensibility (new use cases should be easily implementable) and high reliability. The LangGraph docs do a pretty good job at convincing me that they got the latter pretty nailed down. It seems like a hard enough problem to question a new solution on this.
I want to build a (highly reliable & controllable) UI for agents more than I want to build the agents themselves, so my hope is that LangGraph has the biggest ecosystem I can plug into.
They do have some funky lock-in attempts, for instance the LangGraph CLI, which acts as a server for their agent protocol (https://github.com/langchain-ai/agent-protocol), is proprietary. However (and this is what I consider indicative of a strong ecosystem) there’s a free reimplementation named Aegra: https://www.aegra.dev/
2. this would kind of serve as a drop-in replacement for langgraph. you could build a workflow with an agent and some tools, perhaps some form of memory. then, just deploy that as an API, call it from your frontend, and consume the streamed response on your chat client and without the need to maintain any infra at all.
3. we have a generic code block and an api block used to call APIs for integrations that we may not have, and you can use those to plug (langgraph) agents into the Sim ecosystem.
4. we are adding in the ability to deploy your workflow as an MCP server in the next week, stay tuned :) in the meantime, you can deploy the workflow as an API and have the agent call it as a tool. moreover, you can use the workflow block in sim to call other agents/worklows as well, so its easy to encapsulate a lot of complexity in a `parent` workflow that you call that dynamically routes and uses different tools based on the task at hand
The only weird integration that Node-Red has is MQTT, but that isn't really anything IoT-specific, just a niche message broker.
N8n and its clones are attempts to copy and commercialize it with a closed-source license.
This is definitely going to be given a try tomorrow morning. I think first up will be something easy and personal like going through the collection of NPC character sheets in my recent campaign and ensuring all NPCs have the following sections with some content in them, and if not, flagging them for my review.
If we release a breaking change that requires a migration for existing local workflows, we release notice at least a few weeks ahead of time/bake it into the db migrations.
Incase there are significant changes made, everything is versioned so you opt-in to upgrading.
This is big. Thank you.
since the copilot is a managed service, you’d be setting those azure credentials in your .env and the copilot would call into your azure openai deployment.
1) Is there something that n8n does that's not possible on Sim? 2) Is there a node to create custom stuff like n8n's code node? Possibly nodejs and python 3) Is it easy to import packages from npm or pip
2) there is, we also have a code node that uses E2B to run code in isolated sandboxes. it supports python and ts/js
3) yes, in the code node you can use frameworks/libs since we do RCE
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