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Since last year, before I heard about langchain, I've been building my own stack of tooling for my own LLM projects that probably now covers about 10-20% of Lan
by dereg 3y ago
Since last year, before I heard about langchain, I've been building my own stack of tooling for my own LLM projects that probably now covers about 10-20% of Langchain's functionality. I heard about Langchain earlier this year and groaned, thinking that I did a lot of work for nothing..
..Then I actually used langchain. I was shocked at how poorly performant the code is. Some operations took 10x longer than how I did it, and all the while producing worse results. As tempting as it is to just roll with langchain from day one, I'd highly advise against it. Think deeply about what you're actually trying to accomplish and instead of just injecting langchain in the middle of everything as this messy, amorphous glue code thing.
- deleted 3y ago[deleted]
- FemmeAndroid 3y agoI had this exact same experience. I was happy to move to something good, but I couldn’t find a lot of benefit. Maybe I’m missing something, but the added complexity is not worth it to me for what it provides.
- Tostino 3y agoYeah I've got a few thousand lines of langchain code now for a data cleaning pipeline... I've been fighting it every step of the way. Trying to replace sections of the pipeline to use a local LLM instead of OpenAI has had me have to replace the templates entirely, the chat based templates won't allow me to assign the proper user/assistant names, so the performance for the local LLM is terrible (stupid). They have zero actual composibility when you look at it slightly differently than they expect. It's a useless abstraction for every single purpose I've actually tried it for. Will be extricating it from my code base as soon as I find something else that works any better.
- sandGorgon 3y agoI have an attempt in the same domain, would love feedback We think - Generative AI is config management. We model it on top of config management grammar that is proven to work at K8s/Terraform scale - jsonnet. https://github.com/arakoodev/EdgeChains/blob/main/Examples/redis-chat.jsonnet https://github.com/arakoodev/EdgeChains/blob/main/Examples/r... Prompts live outside the code. We didnt invent a new markup - we used jsonnet which is used in large scale kubernetes and has a grammar that has been well tested for config mgmt.
- Tostino 3y agoOh man, something written in a language I actually know and use?! Will check it out.
- pkc_official 3y agoWe thought the same thing with https://neum.ai https://neum.ai - config management/infra as code for your LLM app, using plain JSON, though we are abstracting even more what LangChain does. Not suitable for the audience here given the level of customizations some folks want.
- nbbaier 3y agoDo you have your stack described somewhere?