LangGraph: Multi-Agent Workflows

LangGraph makes it easy to construct multi-agent workflows, where each agent is a node, and the edges define how they communicate. In this video we will walk through three examples of multi-agent workflows

[bqmac]

These videos never cease to impress me. Straight-forward and effective. Thank you, LangChain team!

[christopherscheidel]

Fantastic work as always. Thanks to the LangChain team.

[raphael]

Super helpful series. I delved a lot in langchain source code, docs to customize already well-established examples and started these series for LangGraph it's a great format thanks a lot.

[paraconscious]

This is a super helpful series, a quick starter, easy to follow along with practical examples, thanks so many Harrison! Starting to experiment right away!

[akashlives]

Thank you for constantly posting such videos.
So easy to use and adopt.

[ManiSaintVictor]

Thank you! Very helpful. I did the first 2 exercises. I'll be back for the 3rd.

[Sandheip]

LangGraph makes creating multi-agent processes easier. SymthOS is an essential viewing for anyone interested in cutting-edge AI frameworks. #AI #MultiAgentWorkflows #SymthOS

[Orcrambo]

Excited to get my hands dirty with langgraph. Hopping on now!

[johnvicente]

Great video. Can you PLS create an example in langgraph on how to use an SQL database tool and call the tool with an agent. More importantly do a RAG search with it. That would be helpful

[Mullheimer]

Great way of explaning. Thank you. Will dive into it sometime soon.

[adandrea]

Great video. One bit things I'm trying to figure out: how can the tools access the graph state? I mean custom tools. I really need them to have context of the conversation, user session metadata, etc, and I can't past them that info if the tools are called just with the parameters filled with syntetic data generated by the llm. I'm sure there is a way to do it but can't seem to fiture it out. Thanks!

[dvirbenor]

Very interesting and well explained! Thanks 👌

[ZhambylYermagambet]

Awesome! Thank you guys for great work

[free_thinker]

That would be great if you add a disclaimer at the beginning of the video mentionning that it's for intermediate and advanced levels because beginners will feel lost and sometimes more confused just like me

[glowstorm]

For anyone facing any error, there are the two error I have faced :


1: Make sure Matplotib is installed in your environment

2: Change the name of Chart Generator to Chart_Genenrator, this fixes an error which the regex does not recognize the name of Chart Generator.

[rahulvb]

In the supervisor example, the model returns,
{
"function_call" : {
"arguments" : "{"next", "Coder"}",
"name" : "route"
}

How is this used to determine the next agent.
Or how is Agentstate populated with next : Coder after getting the above out put from model. I can see a JsonOutputFunctionsParser. But i cant understand, how next value is determined from that

[waneyvin]

great job! please advise how if I wanna add reward or policy into the state for further decision making sake.

[estebanmunoz]

I can't make this example work using AzureOpenAI, I am receiving the error: 'create() got an unexpected keyword argument 'functions''

after executing:

result = agent.invoke({"input": "what's the weather in SF?", "intermediate_steps": []})

Are Agents supported using AzureOpenAI? I have been trying different formulas but I cannot make my agents work using AzureOpenAI

[ragsAI]

Hi! Is Langchain integratable/compatible with redshift/databricks? (especially the text-to-sql framework)? Thank you.

[adityagaurav]

I tried to implement supervisor based multi agent framework for my use case but after my workers return something to supervisor, supervisor doesn't call FINISH and get into a loop of calling the same worker again and again. Has anyone faced this issue ? or know how to fix this ?