Apologies for the scratchy audio at certain points in the video. I only noticed this during editing and didn't want to delay getting a video out to you guys.
Leon, I'm a huge fan of your tutorials! Your explanations and simple demonstrations have completely transformed my understanding of AI. Thank you so much for sharing all your amazing AI tutorials. I truly appreciate your hard work and dedication!
My favorite langchain learning channel because it's so efficiently explained. And I follow practically all AI tutors. Channel is very underrated at this point but it will exponentially grow its subs I'm sure. Leon, any thoughts on the limit of the number of tools? Meaning, would a model malfunction if ALL tools were added🤔 I heard another tutor say it would slow it down because the code would be too large.. but I'd like to hear it from you before I believe that. Thanks for your work.
Thank you for the feedback 🙏. I would recommend that you only load the tools that are required by the agent. I personally haven't tested the performance impact of assigning lots of tools, but I did see the bots get "confused" and started using tools when it wasn't needed.
@@ProminentFox I've been in contact with the Langflow team. They're releasing a major update any day now and asked me to hold off on doing the tutorial. Should release the new series soon 👍
what is the difference in connecting Calculator to a new openAI node instead of the existing one? does using a separate openAI node give it its own conversation instance?
I also have several mistakes whem tyring to run my application: 1. Error: Could not parse LLM output: `Hello! How can I assist you today?` 2. Error: One output key expected, got dict_keys(['output', 'intermediate_steps']) Any ideas why and how to solve? Thank you!
Looks cool. But there's no Auth. So how to host it on a server without any password protection? Can't understand that. And leaving it on a local device is useless for production needs.
You're jumping the gun a bit 🤣. We'll cover production deployment in a future video in this series. I trust you build and test in dev before deploying to prod.
Hmm.. this seems to be a major oversight on the Langflow side 🤣. I was hoping that we could set the credentials in the environment variables (like with Flowise), but that doesn't seem like an option at this stage. I will create a video as soon as this feature becomes available.
Hey another great one. look forward to the next langflow. Very interesting after flowise. I do like to see whats going on at the backend! Can I ask does langflow support API calls into other apps e.g. botpress? If so whats the easiest way to do this. I can do this in flowise via POST but not sure in langflow. Am a low coder! Thanks a lot
Glad you liked the video 👍. LangFlow does provide API support, but there is no way to protect these API routes yet using API keys. I've been holding off from creating tutorials on Langflow APIs (and deployment) because of this.
Hey Alton, I am fully onboard with that idea. Unfortunately the nodes are not defaulting the keys based on environment variables at this stage, but it would make sense that these tools implement that option at some point.
can you also provide multi-agent examples with local gpt4all/huggingface llm's (including one for the Calculator)? The OpenAPI examples are all not feasible for professional usage (data privacy etc.)
Thank you for the tutorial! By the way, do you happen to plan on making a video about AutoGPT in Flowise or LangFlow? It would be very timely, as there is absolutely no precise information anywhere on how to use it.
@@leonvanzyl Great! I'm developing an application that selects products from the internet based on a request, provides a link to them, and then compares them. I tried using other agents, connected them to the internet, they did a search, but did not provide very high-quality answers due to the number of iterations. It would be great if you show how to do it in Flowise
Great Video Series Leon! I have started playing with Langflow, wondering if it is only meant to create chatbots? My use case is feeding data into a LLM (i.e. 100 Products from a list) enrich it via the LLM and then write the results back to the list. If possible, can you do a video how to support this, writing output back to a list? Keep on the great work!
I would like to find out more about your use case, if you'd be interested in sharing. I'm working on an updated series on Langflow, but I think n8n might be a perfect match for you. Happy to create a tutorial on your scenario
@@leonvanzyl I am very happy to share my use case in detail - I think it is relevant for so many scenarios => enriching existing data with "LLM generated insights at scale".
Very good video! is it possible to create different type of agents and chain them? for example create Agent "Chef" that is really good at answering cooking questions and Agent "Hotel" which can answer any question regarding Hotel question. Chain them and have a bot that can be really good at both... this would make an amazing video! looking forward to it!
Thank you Carlos. I've only used one agent per project, but I'll look into this for you. As a rule, if I need two distinct agents, I would create them as seperate projects. I then tie them together using bot builders like Botpress or Voiceflow. I clearly need to create series on these bot builders 😁
Год назад
Thanks for this tutorial. It is very usefull. One question: when I click on "chat icon" my screen shows only the chat, there isn´t that left part with options (input variables). What do I need to do?
Fundamentally, Flowise uses the JS version of Langchain and Langflow uses the Python version of Langchain. Other than that, they are very similar. The Python library is slightly more advanced, but the JS library seems to be catching up.
Apologies for the scratchy audio at certain points in the video. I only noticed this during editing and didn't want to delay getting a video out to you guys.
it doesnt matter! ther is value all over the video! thank you
Thank you kindly 🙏
It's all good
Leon, I'm a huge fan of your tutorials! Your explanations and simple demonstrations have completely transformed my understanding of AI. Thank you so much for sharing all your amazing AI tutorials. I truly appreciate your hard work and dedication!
Incredible comment. Thank you very much 😊
Huge fan of your videos (todays discovery). Hope to see more Langflow tutorials.
Coming soon! Waiting for V1 to drop
My favorite langchain learning channel because it's so efficiently explained. And I follow practically all AI tutors. Channel is very underrated at this point but it will exponentially grow its subs I'm sure.
Leon, any thoughts on the limit of the number of tools?
Meaning, would a model malfunction if ALL tools were added🤔
I heard another tutor say it would slow it down because the code would be too large.. but I'd like to hear it from you before I believe that.
Thanks for your work.
Thank you for the feedback 🙏.
I would recommend that you only load the tools that are required by the agent.
I personally haven't tested the performance impact of assigning lots of tools, but I did see the bots get "confused" and started using tools when it wasn't needed.
amazing......we want more videos from you on langflow.
Will do 👍
When's the next langflow tutorial? 😊
@@ProminentFox I've been in contact with the Langflow team. They're releasing a major update any day now and asked me to hold off on doing the tutorial.
Should release the new series soon 👍
Keep going! Very good videos really practical! Hug from portugal
Thank you!
thanks you
You're welcome 🤗
Please do more videos on Langflow and how to incorporate chatbot into website
Will do. Just waiting for the latest release
Also, how to integrate the bots into Telegram or WhatsApp
need more flowise video please
They're coming 😄.
Awesome Leon
Thank you
what is the difference in connecting Calculator to a new openAI node instead of the existing one? does using a separate openAI node give it its own conversation instance?
Can you explain how to make a custom tool and thank you
I also have several mistakes whem tyring to run my application:
1. Error: Could not parse LLM output: `Hello! How can I assist you today?`
2. Error: One output key expected, got dict_keys(['output', 'intermediate_steps'])
Any ideas why and how to solve? Thank you!
Looks cool. But there's no Auth. So how to host it on a server without any password protection? Can't understand that. And leaving it on a local device is useless for production needs.
You're jumping the gun a bit 🤣. We'll cover production deployment in a future video in this series. I trust you build and test in dev before deploying to prod.
@@leonvanzyl looking forward! In flowise I can easily protect my account with password, but I failed to find it in Langflow
Hmm.. this seems to be a major oversight on the Langflow side 🤣.
I was hoping that we could set the credentials in the environment variables (like with Flowise), but that doesn't seem like an option at this stage.
I will create a video as soon as this feature becomes available.
Its a huge oversight! Someone said they are adding this soon!
@@leonvanzyl please create
langflow or flowise???
which is better
In my opinion, Flowise is way more production-ready than Langflow.
For example, you can't password protect Langflow apps in Prod.
Hey another great one. look forward to the next langflow. Very interesting after flowise. I do like to see whats going on at the backend! Can I ask does langflow support API calls into other apps e.g. botpress? If so whats the easiest way to do this. I can do this in flowise via POST but not sure in langflow. Am a low coder! Thanks a lot
Glad you liked the video 👍.
LangFlow does provide API support, but there is no way to protect these API routes yet using API keys.
I've been holding off from creating tutorials on Langflow APIs (and deployment) because of this.
Great content as always Leon - have you found any way to manage API keys in Langflow , like env file we would normally use in VS code?
Hey Alton, I am fully onboard with that idea.
Unfortunately the nodes are not defaulting the keys based on environment variables at this stage, but it would make sense that these tools implement that option at some point.
can you also provide multi-agent examples with local gpt4all/huggingface llm's (including one for the Calculator)? The OpenAPI examples are all not feasible for professional usage (data privacy etc.)
Hey there. I personally haven't seen good results using local models with Agents, but I'll definitely create a tutorial once I get it working 👍.
Thank you for the tutorial! By the way, do you happen to plan on making a video about AutoGPT in Flowise or LangFlow? It would be very timely, as there is absolutely no precise information anywhere on how to use it.
I'd be happy to make a tutorial on it. Do you have an example of why you would want to use AGPT in Flowise / Langflow?
@@leonvanzyl Great! I'm developing an application that selects products from the internet based on a request, provides a link to them, and then compares them. I tried using other agents, connected them to the internet, they did a search, but did not provide very high-quality answers due to the number of iterations. It would be great if you show how to do it in Flowise
Leon, quick question : Can we cite source URL link after every answer to flowise and Langflow?
Good question. I'll look into it.
o you think doing a short video to compare flowise and langflow would be a good idea?
I am most likely going to create a comparison video at some point.
Hey please make next video on it
Working on it 👍.
Great Video Series Leon! I have started playing with Langflow, wondering if it is only meant to create chatbots? My use case is feeding data into a LLM (i.e. 100 Products from a list) enrich it via the LLM and then write the results back to the list. If possible, can you do a video how to support this, writing output back to a list? Keep on the great work!
I would like to find out more about your use case, if you'd be interested in sharing.
I'm working on an updated series on Langflow, but I think n8n might be a perfect match for you. Happy to create a tutorial on your scenario
@@leonvanzyl I am very happy to share my use case in detail - I think it is relevant for so many scenarios => enriching existing data with "LLM generated insights at scale".
@@leonvanzyl Not sure how to directly connect - I sent you and invite on LinkedIn ;). Looking forward to exchange
An though on how to call API via flowise ? Theres a Get API option but no documentation around it. For example calling google places API via flowise
Since this is a series on Langflow, I assume you are referring to the API tool on Langflow. I'll look into it and create a video 👍
Very good video! is it possible to create different type of agents and chain them? for example create Agent "Chef" that is really good at answering cooking questions and Agent "Hotel" which can answer any question regarding Hotel question. Chain them and have a bot that can be really good at both... this would make an amazing video! looking forward to it!
Thank you Carlos.
I've only used one agent per project, but I'll look into this for you.
As a rule, if I need two distinct agents, I would create them as seperate projects. I then tie them together using bot builders like Botpress or Voiceflow.
I clearly need to create series on these bot builders 😁
Thanks for this tutorial. It is very usefull.
One question: when I click on "chat icon" my screen shows only the chat, there isn´t that left part with options (input variables). What do I need to do?
Thanks for the feedback.
That's a bit odd.. I'll look into it
@@leonvanzyl any update? I jave teh same issue
Please what's the difference between langflow and flowise?
Fundamentally, Flowise uses the JS version of Langchain and Langflow uses the Python version of Langchain. Other than that, they are very similar.
The Python library is slightly more advanced, but the JS library seems to be catching up.
very informative video, Thank you so much !
You're welcome