Hi, unfortunately due to time constraints, we’re not currently taking on new clients to implement solutions. We have the blueprints available within our community that you might be able to work off and we also offer great support and live workshops if needed (we also offer paid private coaching calls if you need even more support). We also offer a jobs section in our community where you can post jobs, as well as our automators directory where you can get in contact with AI automation service providers that are in the community. Thanks for your interest, and apologies that we can be of more direct help in implementing the solution for you here! Alan
Huge respect to you for making this tutorial it should help to save tone of time pls make video on topic "Free whatsapp chatbot that chats with customers based on knowledge you provided of your field who comes to your whatsapp" pls brother ❤
Thanks for the kind words! I'll be doing a video on the WhatsApp trigger and response setup in the next week or two and we have more RAG / Knowledgeable content coming out for this type of WhatsApp chatbot use case so stay tuned!
Thanks for this amazing video. You mentioned flowise having a better way to let the agents go back and forth. May I ask you why n8n is your preferred system ? Thank you
Thanks ... And great question! I have three concerns over the Flowise Multi-agents. For refererence, here is the Flowise supervisor prompt "You are a supervisor tasked with managing a conversation between the following workers: {team_members}. Given the following user request, respond with the worker to act next. Each worker will perform a task and respond with their results and status. When finished, respond with FINISH. Select strategically to minimize the number of steps taken." The first is that it can't handle standard greetings. This is a weird one, but basically the Superviser agent is a master delegator. Even though it is an LLM, it can't actually respond itself without delegating the task. So in response to a "Hello, how are you?" - it delegates the task of forumlating a response to its various workers. And it ends up in this strange dialogue with its various workers, where theres a debate about how to respond to this!!! Eventually it surfaces a response and sometimes that response is not an answer to the original question, but to a question asked by a worker agent! Weird! - I tried to have a "Greetings & Small Talk" worker, to handle this but that didnt' really work! So it's not ideal for a conversational style interface like what you'd have in Whatsapp. The second is that the supervisor is just that ... a supervisor. It's not really a director. As you can see from the system prompt, its the workers that are having the dialog between themselves and the supervisor is faciliating it and deciding which worker agent to call next. I found that the amount of back and forth between the worker agents, through the supervisor can be extreme for simple use cases. There's basically too much dialog and too much delegation! There's also an element of trying to do everything possible to satisfy the users query - which can result in workers, calling every tool. The third is I hit a bug where the system glitched and triggers a tool 150 times in response to a question and crashed the Flowise instance. I got from that, that the Multi-agent features may be a little on the Beta side! I'd say this system is brilliant for certain use cases that require detailed chain of thought style back and forths between Workers to reach a conclusion. However for a production grade, converstaional style multi-agent system, I've found using Flowise Assistants (calling other Assistants via Tools) or N8N Agents (calling other Agents via Tools) to be more reliable. Both of these are as good as each other. The only reason I didn't use Flowise Assistants to build this is that the Cloud version has a 60 second timeout on tool calling. So you'd need to run your own server and change the Nginx settings to extend that timeout to allow the sub-agents to do what they need to do.
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Amazing. Have been waiting forts video. Ihaewanted geo dog this fr my business wow I can wait t start.
thank you for this, super useful!
Hi! is it possible to book a discovery call with you if we will request to set up this workflow on our small company?
Hi, unfortunately due to time constraints, we’re not currently taking on new clients to implement solutions. We have the blueprints available within our community that you might be able to work off and we also offer great support and live workshops if needed (we also offer paid private coaching calls if you need even more support). We also offer a jobs section in our community where you can post jobs, as well as our automators directory where you can get in contact with AI automation service providers that are in the community. Thanks for your interest, and apologies that we can be of more direct help in implementing the solution for you here! Alan
Huge respect to you for making this tutorial it should help to save tone of time pls make video on topic "Free whatsapp chatbot that chats with customers based on knowledge you provided of your field who comes to your whatsapp"
pls brother ❤
Thanks for the kind words! I'll be doing a video on the WhatsApp trigger and response setup in the next week or two and we have more RAG / Knowledgeable content coming out for this type of WhatsApp chatbot use case so stay tuned!
@TheAIAutomators so thanks dear
Thanks for this amazing video. You mentioned flowise having a better way to let the agents go back and forth. May I ask you why n8n is your preferred system ? Thank you
Thanks ... And great question! I have three concerns over the Flowise Multi-agents.
For refererence, here is the Flowise supervisor prompt
"You are a supervisor tasked with managing a conversation between the following workers: {team_members}.
Given the following user request, respond with the worker to act next.
Each worker will perform a task and respond with their results and status.
When finished, respond with FINISH.
Select strategically to minimize the number of steps taken."
The first is that it can't handle standard greetings. This is a weird one, but basically the Superviser agent is a master delegator. Even though it is an LLM, it can't actually respond itself without delegating the task. So in response to a "Hello, how are you?" - it delegates the task of forumlating a response to its various workers. And it ends up in this strange dialogue with its various workers, where theres a debate about how to respond to this!!! Eventually it surfaces a response and sometimes that response is not an answer to the original question, but to a question asked by a worker agent! Weird! - I tried to have a "Greetings & Small Talk" worker, to handle this but that didnt' really work! So it's not ideal for a conversational style interface like what you'd have in Whatsapp.
The second is that the supervisor is just that ... a supervisor. It's not really a director. As you can see from the system prompt, its the workers that are having the dialog between themselves and the supervisor is faciliating it and deciding which worker agent to call next. I found that the amount of back and forth between the worker agents, through the supervisor can be extreme for simple use cases. There's basically too much dialog and too much delegation! There's also an element of trying to do everything possible to satisfy the users query - which can result in workers, calling every tool.
The third is I hit a bug where the system glitched and triggers a tool 150 times in response to a question and crashed the Flowise instance. I got from that, that the Multi-agent features may be a little on the Beta side!
I'd say this system is brilliant for certain use cases that require detailed chain of thought style back and forths between Workers to reach a conclusion.
However for a production grade, converstaional style multi-agent system, I've found using Flowise Assistants (calling other Assistants via Tools) or N8N Agents (calling other Agents via Tools) to be more reliable. Both of these are as good as each other.
The only reason I didn't use Flowise Assistants to build this is that the Cloud version has a 60 second timeout on tool calling. So you'd need to run your own server and change the Nginx settings to extend that timeout to allow the sub-agents to do what they need to do.
@@TheAIAutomators Wow thank you so much i really appreciate the detailed breakdown.Your insights are incredibly helpful. Keep up the great work