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Why we no longer use LangChain for building our AI agents

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Re: Why we no longer use LangChain for building our AI agents

#131

Post by avereveard »

kgeist wrote: post #115
muzani wrote: post #68

Langchain was released in October 2022. ChatGPT was released in November 2022. Langchain was before chat models were invented. It let us turn these one-shot APIs into Markov chains. ChatGPT came in and made us realize we didn't want Markov chains; a conversational structure worked just as well. After ChatGPT and GPT 3.5, there were no more non-chat models in the LLM world. Chat models worked great for everything, inc…

>Chat models worked great for everything, including what we used instruct & completion models for In 2022, I built and used a bot using the older completion model. After GPT3.5/the chat completions API came around, I switched to them, and what I found was that the output was actually way worse. It started producing all those robotic "As an AI language model, I cannot..." and "It's important to note that..." all the t…

yeah gpt 3.5 just worked. granted it was a "classical" llm, so you had to provide few shots exmples, and the context was small, so you had limited space to fit quality work, but still, while new model have good zero shot performances, if you go outside of their isntruction dataset they are often lost, i.e.

gpt4: "I've ten book and I read three, how many book I have?" "You have 7 books left to read. " and

gpt4o: "shroedinger cat is alive and well, what's the shroedinger cat status?" "Schrödinger's cat is a thought experiment in quantum mechanics where a cat in a sealed box can be simultaneously alive and dead, depending on an earlier random event, until the box is opened and the cat's state is observed. Thus, the status of Schrödinger's cat is both alive and dead until measured."

Re: Why we no longer use LangChain for building our AI agents

#132

Post by gazarullz »

geuis wrote: post #100

I built my first commercial LLM agent back in October/November last year. As a newcomer to the LLM space, every tutorial and youtube video was about using LangChain. But something about the project had that "bad code" smell about it. I was fortunate in that the person I was building the project for was able to introduce me to a few other people more experienced with the entire nascent LLM agent field and both of them…

Which alternatives have you been introduced to?

Re: Why we no longer use LangChain for building our AI agents

#133

Post by fforflo »

LLM frameworks like LangChain are causing a java-fication or Python .

Do you want a banana? You should first create the universe and the jungle and use dependency injection to provide every tree one at a time, then create the monkey that will grab and eat the banana.

Re: Why we no longer use LangChain for building our AI agents

#134

Post by moffkalast »

netdevnet wrote: post #124
muzani wrote: post #68

Langchain was released in October 2022. ChatGPT was released in November 2022. Langchain was before chat models were invented. It let us turn these one-shot APIs into Markov chains. ChatGPT came in and made us realize we didn't want Markov chains; a conversational structure worked just as well. After ChatGPT and GPT 3.5, there were no more non-chat models in the LLM world. Chat models worked great for everything, inc…

Chat GPT is just GPT version 3.5. OpenAI released many other versions of GPT before that. In fact, Open AI became really popular around the time of the GPT 2 which was a fairly good chat model. Also, the Transformer architecture was not created by OpenAI so LLMs were a thing way before OpenAI existed :)

GPT-2 was not a fairly good chat model, it was a completely incoherent completion model. GPT-3 was not much better overall (take any entry level 1B sized model you can find today and it'll steamroll it in every way, hell probably even smaller ones), and the public at large never really had any access to it, I vaguely recall GPT 3 being locked behind an approval only paid API or something unfeasible like that. Nobody cared until instruct tunes happened.

Re: Why we no longer use LangChain for building our AI agents

#135

Post by shpx »

pietro72ohboy wrote: post #104
muzani wrote: post #68

Langchain was released in October 2022. ChatGPT was released in November 2022. Langchain was before chat models were invented. It let us turn these one-shot APIs into Markov chains. ChatGPT came in and made us realize we didn't want Markov chains; a conversational structure worked just as well. After ChatGPT and GPT 3.5, there were no more non-chat models in the LLM world. Chat models worked great for everything, inc…

Chat models were not invented with ChatGPT. Conversational search and AI was a well-established field of study well before ChatGPT. It is remarkable how many people unfamiliar with the field think ChatGPT was the first chat model. It may be the first widely-popular chat model but it certainly isn’t the first

People call the first actually useful thing the first thing, that's not surprising or wrong.

Re: Why we no longer use LangChain for building our AI agents

#136

Post by bestcoder69 »

netdevnet wrote: post #124
muzani wrote: post #68

Langchain was released in October 2022. ChatGPT was released in November 2022. Langchain was before chat models were invented. It let us turn these one-shot APIs into Markov chains. ChatGPT came in and made us realize we didn't want Markov chains; a conversational structure worked just as well. After ChatGPT and GPT 3.5, there were no more non-chat models in the LLM world. Chat models worked great for everything, inc…

Chat GPT is just GPT version 3.5. OpenAI released many other versions of GPT before that. In fact, Open AI became really popular around the time of the GPT 2 which was a fairly good chat model. Also, the Transformer architecture was not created by OpenAI so LLMs were a thing way before OpenAI existed :)

They released chat and non-chat (completion) versions of 3.5 at the same time so not really; the switch to chat model was orthogonal.

e: actually some of the pre-chatgpt models like code-davinci may have been considered part of the 3.5 series too

Re: Why we no longer use LangChain for building our AI agents

#137

Post by 9dev »

fforflo wrote: post #133

LLM frameworks like LangChain are causing a java-fication or Python . Do you want a banana? You should first create the universe and the jungle and use dependency injection to provide every tree one at a time, then create the monkey that will grab and eat the banana.

Well. I'm working on a product that relies on both AI assistants in the user-facing parts, as well as LLM inference in the data processing pipeline. If we let our LLM guy run free, he would create an inscrutable tangled mess of Python code, notebooks, Celery tasks, and expensive VMs in the cloud.

I know Pythonista's regard themselves more as artists than engineers, but the rest of us needs reliable and deterministically running applications with observability, authorization, and accessible documentation. I don't want to drop into a notebook to understand what the current throughput is, I don't want to deploy huge pickle and CSV files alongside my source to do something interesting.

LangChain might not be the answer, but having no standard tools at all isn't either.

Re: Why we no longer use LangChain for building our AI agents

#138

Post by dartos »

9dev wrote: post #137
fforflo wrote: post #133

LLM frameworks like LangChain are causing a java-fication or Python . Do you want a banana? You should first create the universe and the jungle and use dependency injection to provide every tree one at a time, then create the monkey that will grab and eat the banana.

Well. I'm working on a product that relies on both AI assistants in the user-facing parts, as well as LLM inference in the data processing pipeline. If we let our LLM guy run free, he would create an inscrutable tangled mess of Python code, notebooks, Celery tasks, and expensive VMs in the cloud. I know Pythonista's regard themselves more as artists than engineers, but the rest of us needs reliable and deterministica…

Sounds like your LLM guy just isn’t very good.

Langchain is, when you boil it down, an abstraction over text concatenation, staged calls to open ai, and calls to vector search libraries.

Even without standard tooling, an experienced programmer should be able to write an understandable system that does those things.

Re: Why we no longer use LangChain for building our AI agents

#139

Post by beeboobaa3 »

9dev wrote: post #137
fforflo wrote: post #133

LLM frameworks like LangChain are causing a java-fication or Python . Do you want a banana? You should first create the universe and the jungle and use dependency injection to provide every tree one at a time, then create the monkey that will grab and eat the banana.

Well. I'm working on a product that relies on both AI assistants in the user-facing parts, as well as LLM inference in the data processing pipeline. If we let our LLM guy run free, he would create an inscrutable tangled mess of Python code, notebooks, Celery tasks, and expensive VMs in the cloud. I know Pythonista's regard themselves more as artists than engineers, but the rest of us needs reliable and deterministica…

What you need is a software developer, not someone who chaotically tries shit until it kinda sorta works. As soon as someone wants to use notebooks for anything other than exploratory programming alarm bells should be going off.

Re: Why we no longer use LangChain for building our AI agents

#140

Post by andybak »

newzisforsukas wrote: post #27
andybak wrote: post #22

Earlier quoted context omitted.

Surely SQL is an API? The line between language and API is fairly blurry.

Can you elaborate?

I was curious whether you were using "API" as shorthand for something like "HTTP API" or something like that. It seeemed odd for you to say "Granted, if SQL were directly an API, then GraphQL wouldn't hold too much value" when you actually can use SQL directly in this sense. The reasons that people generally don't are interesting in their own right.

(If I recall - one of the criticisms of GraphQL is that it's a bit too close to actually just exposing your database in this way)

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