LangChain Agents - Joining Tools and Chains with Decisions

In this we look at LangChain Agents and how they enable you to use multiple Tools and Chains in a LLM app, by allowing your LLM to decide on the next input tool to use based on the user's input.

My Links:

Github:

#LangChain #BuildingAppswithLLMs

[macbros]

No bullshit here straight to the point, clearly the goal is to improve viewers understanding of the subject first, really like your brand

[luiztauffer]

thanks for your LangChain playlist, it's definitely one of the best resources out there!
Would be awesome to have your review on custom tools and agents, I find it to be the trickiest part in LangChain but also it's greatest potential

[iyerpram]

Thanks for this very useful and descriptive video. I will start learning Lang chain

[jsonbourne]

Great tutorial ! I can finally make sense of Tools.

[kevinehsani]

Than you for the video, it seems that we need to use template as I tried to run without it and it could not answer "how are you today" and kept looping. I thought it could try to figure this out without a template. This is the message it kept outputting
"Action Input: None
Observation: None is not a valid tool, try another one.
Thought: I need to answer this question with a response."

[K.F-R]

Very helpful. Good deep dives on this topic are still rare. Thanks.

[dingruiwang]

Thanks for the great help regarding the clarification of the Langchain concepts!

[RapidExplainer]

Just wowed at your tutorial. Thank you!

[vanheerdena]

That was extremely helpful. Could you cover custom agents? I need a way of using the response to make a decision. For example. In a multi-user chat log, if the question is directed at the chatbot respond else do nothing. Another example is an interviewer agent that has to either decide to probe for more information or go to the next question. Could you give any guidance on these kind of forking chain or custom agent type scenarios?

[AP-hvdh]

Outstanding Sam! Please keep them coming! 🎉

[OmarASultan]

Would be great if we can have a video on the Custom Agents
Thank you so much for your videos, they are absolutely brilliant, really helped me

[sbacon]

excellent.
you should have a master class.

[shaunpx]

How can you add custom tools with the specfied tool like serp, wiki, terminal and such and how can you alter the prompt template

[Jay-Dub-Ay]

It looks like you’ve strayed away from titling videos in this playlist with “Langchain Basics Tutorial #N”
Is this a conversational buffer memory issue? 😂 but thank you for these videos! I’m really learning a lot 🙏❤️

[kirandas]

Can you explain zero-shot-react-description what's is that?

[constantinebimplis]

Amazing video! Finally I was able to understand and utilize agents. Thank you.
I'm always experimenting in using opensource models along with openai. The terminal and search agent examples you discussed with the video fail with "ValueError: Could not parse LLM output:" when tried with huggingface models. A google search revealed that models used with these agents must follow the template. Any ideas on which models would follow this template and would allow us to use openai alternatives? Thank you

[vincentyang]

Hi Sam, great work! Very helpful for me. I am curious about how folks think about the potential of LangChain!

[stanTrX]

Thanks. I will try it asap. How is it possible to end the conversation when it says "Finished Chain" i want to input user to Enter new prompt at this stage

[Satvik__Jain]

What if I want to use a custom tool that i made using a retriever
i loaded tools as
tools = load_tools(["serpapi", <retriever tool name>])

but it throws an error

[ispgeiq]

Hi Sam, Can we add chat memory buffer to agent for chat continuation?