I've just started with the beginner's guide, so this is a bit more complex, but I'm amazed at the possibilities 😧
@Speedon193 ай бұрын
Thanks for the video Leo, but if you can do more example of Sequential, we would like it, for example like a conversation with a customer like for sales, but they want to purchase a product, so that the bot has the intention of seeing when it has to ask them. the client's data, of course I see that it is complex, but the most possible.
@KurtAnderson64Ай бұрын
Hi Leon, amazing work as always! Could you create a video on calling child flows from a main flow? The documentation on flowise is out of date I think, as the 'tool agent' seems to be deprecated, and the other options for this use are a bit confusing. Thanks mate!
@BadBite3 ай бұрын
You are a very awesome mentor! thank you! 🎉
@WayneBruton3 ай бұрын
Great Video Leon, a little more work with Sequential agents vs multi agents but I think the effort is well worth it unless you know the demands won't grow. I have been very keen on using Assistant API but this gives more flexibility. For a simple RAG Bot, its pretty hard to beat the Assistants I guess, quick output, quick money (esp with 40 Mini). But the sequential agents is so very powerful. Thank you.
@santiagoghione917712 күн бұрын
Muy buen canal y excelente contenido
@risosa12 ай бұрын
spot on, you are my go to for understanding flowise! Any chance you can do a tutorial on how to do an integrated code dev application using flowise...is this even possible? I want to achieve something like open interpreter, but with all the flowise no-code / flexible flow. Maybe you could build on your earlier multi agent sw dev tutorial to actually debug and review the code?
@leonvanzyl2 ай бұрын
Thank you for the suggestion. I'll look into this 👍. Thank you very much for the super! It helps a lot 🙏
@faridullahkhan13 ай бұрын
Leon van Zyl, thank you for your valuable videos, very informative. I learned alot from your content. I wanted to ask, are you able to make a video that shows how to use N8N with Flowise and host them both in own cloud? thank you,
@leonvanzyl3 ай бұрын
That's actually my favourite stack! I have both Flowise and n8n running on Render with some automation. I'll create a video on this.
@royal.allen_3 ай бұрын
I just deployed this last night in AWS. Quick note, make sure you use more than a 8gb disk (I ran out of space, worked when I used 28gb) and also use the Docker instructions (NPM froze on me installing both for some reason).
@ward_jl3 ай бұрын
@@leonvanzyl very much looking forward to this.
@faridullahkhan13 ай бұрын
@@leonvanzyl I have some workflows written in langgraph, which is better no code framework to use instead of langgraph ? Or can I use langgraph via api with n8n ? Thank you
@free_thinker49583 ай бұрын
Thank you for your high value content ❤💯🙏 looking forward for the n8n tutoriels too 🎉
@leonvanzyl3 ай бұрын
You're welcome 🤗.
@chillwinston8920Ай бұрын
Thanks for your tutorials! I can't seem to see multi or sequential agents. Is this a version issue?
@juanpcadile3 ай бұрын
Great video! I see you use both Flowise and Langflow. Which one is your favorite? For production use
@borislemaire31433 ай бұрын
In Python it is possible chat with Excel files using langchain and pandasai (storing the excel data into a SmartDataframe). Do you know if it is possible do something similar with flowise?
@royal.allen_3 ай бұрын
I would love to know how to send additional parameters (like "name") from Telegram to Flowise. I can currently only get sessionID to work (for Upstart Redis).
@WntrmuteAI3 ай бұрын
You can try adding variables inside of the "question" parameter when querying Flowise.
@WanderlustBabyАй бұрын
Hi Leo, really love your videos! Thanks for that! I was wondering if it is possible for a worker (or two) in an agentflow to create for example an instapost and the picture for it at the same time? Tried to connect the image creator tool to an worker, but can not make it running. Do you have any ideas?
@antoniomarf3 ай бұрын
awesome, another awesome video! looking forward to improved rag examples
@leonvanzyl3 ай бұрын
Coming SOON 😁
@rafabiton13 ай бұрын
Thanks for the video, one question: Where can I define the system context, for receive the user? Thank you so much
@choistella58633 ай бұрын
Awesome, Leon! Thanks so much! This is incredibly useful as always. I have a special use case I'd love to explore with sequential agents. I'm thinking of one agent tasked with collecting information from users (e.g., filling out a form with a defined number of variables) and another agent responsible for processing the information collected to provide any type of conclusion to the user :)
@LuisOrtizFX3 ай бұрын
@choistella5863, I am working on exactly the same, I could share my current flow, maybe it would help.
@choistella58633 ай бұрын
@@LuisOrtizFX Thanks so much for your answer !!! It would be amazing if you could share your flow :)
@jhonymonhol68513 ай бұрын
@@LuisOrtizFX I would like to take a look, how can you share this with us?
@LuisOrtizFX3 ай бұрын
@jhonymonhol6851 I'm cleaning up some sensitive data out of it,, and I will share as a gist today. I'm actually getting VERY CLOSE to making it work quite nice (but needs work), I'm sure we can collab and make it perfect!
@colibrideplaya3 ай бұрын
The Sequential agents are amazing! More videos about It please. PD: Also how to use Flowise and Langchain at the same time and the benefits of using both together ;) Thanks, Leooo!!
@KurtAnderson64Ай бұрын
Hi Leon, I've noticed that in the flowise cloud that having a node on the canvas without a connection always throws errors. Have you noticed that? It seems to have changed recently?
@florentromanet54393 ай бұрын
Really nice video once again Leon 😊 I was waiting for the final app running 😂 how did it go?
@leonvanzyl3 ай бұрын
Thank you for the feedback 🙏. Hahaha, I'm sure the code would have worked 😂
@bram1011123 ай бұрын
Thanks Leon! Great tutorial!
@leonvanzyl3 ай бұрын
Thank you 🙏
@Jonzybeatz2 ай бұрын
Hey leon, I just watched a video of Sam Altman talking about the five stages of AI development. The first stage is the chatbot. The second stage is the reasoner, (which is the stage we are currently in.) The third stage is the AI agent. The fourth stage is the innovator. And the fifth stage is the global organization. I would like to know, in this context, how you think it's interesting to learn FlowWise, given that the next stage is the development of autonomous agents. Is it still worth spending time learning FlowWise, or would it be better to wait for the next stage (which should arrive much faster than the first two stages?") Thanks
@leonvanzyl2 ай бұрын
Hey there! It's definitely worth learning tools like Flowise. Especially Agentflows, which gives you the low level building blocks to build autonomous agents.
@SoyPorteroYT3 ай бұрын
I would love if you showcase the code, to see if the results! And if the app works. Amazing content really 🙏
@leonvanzyl3 ай бұрын
Noted.
@SoyPorteroYT3 ай бұрын
@@leonvanzyl I meant to test the code in the video! Maybe I expressed wrongly
@umqualquerporai3 ай бұрын
What is this error about? Error buildAgentGraph - Cannot read properties of undefined (reading 'label') I set two agents with a retrieval tool connected to pinecone for each one. Followed the same steps as the video.
@Thecoolestcouple13 ай бұрын
Followed the video step-by-step and got that same error message Error buildAgentGraph - Cannot read properties of undefined (reading 'label') Wondering how you can debug Flowise when errors like this come up?
@lingzhang20612 ай бұрын
@@Thecoolestcouple1 I ran into the same issue. Wonder if you have figured out how to debug it? Thanks!
@lingzhang20612 ай бұрын
@umqualquerporai, I ran into the same issue. Wonder if you have figured out how to debug it? Thanks!
@aaronmcintyre2863 сағат бұрын
This is an issue with the variable used in LLM Node. Instructions are clear that you are supposed to use `$flow.output.` I think this is misunderstanding. From what I can tell. The structured JSON this is referring to is the output of the LLM directly which looks like the following. ``` { "content": 'Hello! How can I assist you today?', "name": "", "additional_kwargs": {}, "response_metadata": {}, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": {} } ``` The structured JSON output of the LLM we are supposed to use here seems to be within `$flow.output.content`
@sdcharly3 ай бұрын
Good one again @Leon.. Can i ask how LLM node and Condition Agent is different based on this video?.. might be a lame query :) or shall i put it like is LLM Node + Condition = Condition agent?
@leonvanzyl3 ай бұрын
Actually, that's a very good way to look at it. The LLM Node can return a structured output which a condition node can then use.
@tecnopadre3 ай бұрын
I think sequential is so complicated seeing that the previous squema does the same.. don't you think? What would be the advantages or disadvantages of both?
@tamashi8583 ай бұрын
Thanks for the video, Leon! I was wondering if it is possible with Sequential Agents to set a condition that "one agent finishes its task"? I want one agent to ask the user about 10-15 questions to gather a lot of information and then send it to another agent that will analyze the information before responding to the user. Do I need to create 10-15 nodes to store each piece of information? Thanks if you have time to answer, and thank you very much for all you videos! It helps a lot !!
@leonvanzyl3 ай бұрын
Thank you for the feedback! You could probably create your example using a normal agent in Flowise. I guess it depends on what the second agent in the chain needs to do. I would honestly suggest that you first try to create your example using a normal flow with a tool agent. Agentflows might not be a good match for collecting information from a user in a loop.
@GilbertMizrahi3 ай бұрын
Great video as always.
@leonvanzyl3 ай бұрын
Thank you
@Emanuel-Sampaio3 ай бұрын
Hey Leon... Why in both examples do you instructs the worker to pass the result to the other worker (12:25), but it always goes back to the supervisor (who takes care of it)!?
@leonvanzyl3 ай бұрын
I have found that the supervisor would sometimes end the flow early if you don't provide clear instructions.
@Emanuel-Sampaio3 ай бұрын
@@leonvanzyl Thank your!
@lazyjuan21978 күн бұрын
I noticed, currently there is no Multi Agents section available in flowise v1.4.12 anymore.
@leonvanzyl5 күн бұрын
You are using a very old version of FW. Multi Agents were introduced from v2.
@mikew28833 ай бұрын
Excellent tutorial! 👏 I've been trying to get Flowise API to work in an app much like a pipeline outside the chatbot. According to the documentation you can only stream output with a Chain or Tool Agent. I attempted to use a Sequential Agent like in your example but it only returns the final result and not the stream itself. Do you think you can do a video on how to correctly accomplish this? Thanks!
@leonvanzyl3 ай бұрын
I think the agentflows cannot be streamed at this stage.
@mikew28833 ай бұрын
@leonvanzyl I see. I even tried it with a Chain too but did not work as well.
@BirdManPhil12 күн бұрын
can you use both in hybrid setup
@user-uv3nv2bc6v3 ай бұрын
Very cool Leon. Do you have website where you share this flows? Or maybe we can buy some from you :-)
@leonvanzyl3 ай бұрын
Thank you. I'll see if I can share them on a GitHub repo or somewhere.
@claudi70093 ай бұрын
Have you ever tried with Azure open AI? It works similar?
@wEBMedPL3 ай бұрын
Maaaan you da MvP! Thanks
@JPBCDE3 ай бұрын
Thank you Leon. Great video. I can see so much potential for this. I did run into an issue however, duplicating your sequential workflow (exact, except for using ChatOllama, instead of ChatOpenAI). When I run the flow, the software developer is called, as it should, stating that the code needs to be reviewed, but then i get the error: Error buildAgentGraph - Error: No tool calls found in the response. and the flow just stops there. Any suggestions?
@leonvanzyl3 ай бұрын
You need to use an advanced model for multi-agents. If you're using Ollama, it will have to be the equivalent of the Llama 3.1 70b model.
@JPBCDE3 ай бұрын
@@leonvanzyl Ah great. Thank you. Will give that a go then (or use a non-local one).
@JPBCDE3 ай бұрын
@@leonvanzyl i just changed to GrogChat (llama 3.1 70b) and that seems to work better, although the software developer seems to think it has done a good enough job and does not need to do more, after the code review, even if the code reviewer suggested more changes :D
@musumo19083 ай бұрын
Hey how do I join your channel?….can’t see any options to be a member? Thx
@leonvanzyl3 ай бұрын
You should see a "Join" button somewhere on any of my vids.
@musumo19083 ай бұрын
@@leonvanzyl hey weirdly it’s not showing up on iPad…fine on android…FYI…
@brylie3 ай бұрын
Is it possible to loop back to the human for confirmation or feedback? I.e. human in the loop 😊
@leonvanzyl3 ай бұрын
I'm actually going to create a video on this. It's possible, but I think it requires a bit of explanation. Nothing too extreme though. Involves some state variables, LLM nodes, memory and conditions.
@brylie3 ай бұрын
@@leonvanzyl thank you so much! This is a really important architecture for many tasks, since the LLMs typically need human guidance and confirmation to promote better results.
@swift-immersive3 ай бұрын
Hey Leon, always incredible content. Are you avaiable for hire?
@leonvanzyl3 ай бұрын
Thank you. You can contact me via email (in about section) or my automation agency (in video description).
@swift-immersive3 ай бұрын
@@leonvanzyl Great, sent you an email.
@mzafarr2 ай бұрын
Not sure which one should be used when. Need some help in understanding it. Thanks.
@leonvanzyl2 ай бұрын
Start with Multi agents. If you feel that you need more control over the agents then switch over to sequential agents.
@JustinJ.3 ай бұрын
What are the system specs are you running these models on? It looks super snappy when they respond
@leonvanzyl3 ай бұрын
I'm using an OpenAI model in this video, so my specs don't really matter. If speed is impoyto you then I highly recommend giving Groq a try. I've got a dedicated video on Groq.
@md43003 ай бұрын
I really love your videos. This is no exception. Do you have a Discord or something? I am really interested in getting sequential agent working with Llama 3.1 but having issues. Again, awesome video and thanks.
@leonvanzyl3 ай бұрын
Thank you! I actually suggest joining the Flowise AI dievord directly.
@samuelmacaluso33672 ай бұрын
Am I crazy or is some of this out of date already? I can't find the start, LLM, or the state node... whats up?
@leonvanzyl2 ай бұрын
What version of FW are you on? These nodes were added with v2
@samuelmacaluso33672 ай бұрын
@@leonvanzyl If you get someone else who asks this... I was in Chatflow NOT Agentflow. User error in the biggest way.
@maniecronje2 ай бұрын
Hi Leon apologies if I already asked this in earlier videos… can FW handle calling JS function in the same way as shown here kzbin.info/www/bejne/fqS6qKyfpb-Bftksi=i8fHxMZmliGzBcwz
@leonvanzyl2 ай бұрын
Absolutely. The custom tools in FW run in a node environment, so you can add JavaScript code. I created a video on this. It's one of the older videos, but tools still work the same way. kzbin.info/www/bejne/lXycqX2nesyhqLc
@maniecronje2 ай бұрын
@@leonvanzyl Bakgat! Baie Dankie!
@maniecronje2 ай бұрын
@@leonvanzyl Thx, Leon is there a way to use GraphRAG with FW? if it is possible could you create tutorial on this or point me what you think would be good starting point, thx Manie
@RoniBliss3 ай бұрын
Until Flowise add streaming capabilities to AgentFlows and Sequential agents they are pretty much redundant. As through API the responses are delivered in one huge block of text. Making it unusable for production applications.
@leonvanzyl3 ай бұрын
I kinda agree with you to a smaller extent. Consider this: You could call the API from a frontend (like a chatbot) or via an automation / non client facing process. If you're using it as a chatbot via the web embed, then I agree. It would be a bit frustrating to wait for a response. Flowise will definitely add streaming for this, so it won't be an issue for long. If you're using it during a workflow or backend process then streaming really doesn't matter. For example, you could have some research team execute at 9am every morning using Make, Zapier or n8n. The final result will then be emailed to you or stored in a database. I suspect that this will be the most common use-case for Agentflows.