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> Furthermore, the prompt has a spelling error (Let'w) and also overly focuses on the negative about identifying errors - which makes me skeptical that this prompt has been optimized or tested.
Fixed in https://github.com/langchain-ai/langchain/commit/7c6009b76f0...
We felt this 100% so we built a DSL (called BAML) to solve the "prompt transparency" problem (amongst other issues). We have a VSCode playground that always shows you the full prompt -- kinda like a markdown preview works.
We are still in beta (and open source) but feel free to check it out! https://docs.boundaryml.com/ .
Some of these frameworks like instructor use like 80% more tokens or only work with OpenAI so we aim to tackle all these problems from the ground up.
I wrote some code to annotate the image with the text of the prompt. I couldn't find a convenient way to do it in EXIF.
For Midjourney: https://github.com/ernop/social-ai/tree/main/SocialAI
This one just downloads and annotates all the images in a discord channel/server you have admin in, and can backfill.
For Dalle3 Api: https://github.com/ernop/cmdline-dalle3-csharp
Not sure it's related to function calling. GPT4 can do function calling without using the specific function-calling API just by injecting the schema you want into the prompt with directions and asking it to return JSON. It works like >99% of the time. Same with 3.5-turbo.
The problem is these libraries convert pydantic models into json schemas and inject them into the prompt, which uses up like 80% more tokens than just describing the schema using typescript type syntax for example. See https://microsoft.github.io/TypeChat/, where they prompt using typescript type descriptions to get json data from LLMs. It's similar to what we built but with more boilerplate.