The vast majority of people building LM apps with (or without) LangChain are using OpenAI.
I sincerely hope local LM tech like Galpaca (or vicuna/koala/etc) succeed but I don't understand why we are collectively pretending they are currently anywhere near gpt-3.5-turbo both in terms of speed and quality. Honestly the local models feel more like first generation BERT/GPT-1 models that have been fine-tuned for QA using RLHF.
The models now are probably closer to GPT-2, and gets very close to GPT-3 with decent hardware (larger param models) and effort.
They're certainly worse when it comes to 'knowledge' or memorized parts of the training data, but a decent bit of this is ameliorated by having "the pile" + other data locally available for reference.
There are some issues that arise from not having decent priors due to that lack of knowledge, which may or may not be important for the given task.
A (perhaps somewhat bad) example may be: if you ask me "what is a good one-liner in bash for parsing xml from a stream", I may give you an answer using xmlstarlet. However, this may not be the best answer - since Xalan can handle XSLT version 3, but xmlstarlet can't (XSLTv3 handles streams).
So if looking up information in the database, some things may be slightly missed like that - but this behavior would be close to what ChatGPT offers (ChatGPT is quite awful in this way most of the time).
You are right that it would miss GPT-4 by a good bit though in these cases, but most people aren't using GPT-4 for this anyway.
Ultimately both can be used. OpenAI can do things you really want it for, such as a programming assistant, or things that may require much more "reasoning" (not a proper word, but conveys the message) capabilities.
Local models can do the really useful base work of completely re-organizing or re-encoding files to free up space if you set it to do so, integrating with a HomeAssistant system, setting up a HomeAssistant system if you want one, answering your vocal 'Alexa/Siri'-like questions completely offline, setting up backup solutions for all your computers, setting up servers that perform more tasks that you may want - essentially a complete personal assistant. OpenAI shouldn't be needed for this, and it is highly desired to not have them do any of this (due to costs and the number of credentials it would give to them).
I sincerely hope local LM tech like Galpaca (or vicuna/koala/etc) succeed but I don't understand why we are collectively pretending they are currently anywhere near gpt-3.5-turbo both in terms of speed and quality. Honestly the local models feel more like first generation BERT/GPT-1 models that have been fine-tuned for QA using RLHF.