BLbluecoconut·May 8, 2023
I sorta did this, feel free to check it out and let me know your thoughts!
On the main langchain post (In January) that got the traction on hackernews, i left this comment: https://news.ycombinator.com/item?id=34422917 . It still remains true, a "simpler langchain"
> To offer this code-style interface on top of LLMs, I made something similar to LangChain, but scoped what i made to only focus on the bare functional interface and the concept of a "prompt function", and leave the power of the "execution flow" up to the language interpreter itself (in this case python) so the user can make anything with it.
I made a really lightweight wrapper over requests and call it lambdaprompt
https://github.com/approximatelabs/lambdaprompt It has served all of my personal use-cases since making it, including powering `sketch` (copilot for pandas) https:/
Read the rest
/github.com/approximatelabs/sketch
Core things it does: Uses jinja templates, does sync and async, and most importantly treats LLM completion endpoints as "function calls", which you can compose and build structures around just with simple python. I also combined it with fastapi so you can just serve up any templates you want directly as rest endpoints. It also offers callback hooks so you can log & trace execution graphs.
All together its only ~600 lines of python.
I haven't had a chance to really push all the different examples out there, so I think it hasn't seen much adoption outside of those that give it a try.
I hope to get back to it sometime in the next week to introduce local-mode (eg. all the open source smaller models are now available, I want to make those first-class)