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Comment by andy_xor_andrew | Hacker News Reader

I'm employed by Microsoft, but not in any relation to the authors of this tool or this post. First time I saw github.com/mirosoft/guidance was on the HN front page, actually :)

I've been waiting for a tool exactly like guidance, something that lets me compose prompts the way I think about prompts. Langchain was too much of a headache for me. Playing with guidance, it feels like this is how programmatically interacting with a llm should be. Also, really happy to see the MIT license.

I'd love to see ports to other languages.

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are we going to now invent a programming language that communicates with LLMs? I find that funny

I'm not an LLM, but I am a native English speaker and English is pretty awful for conveying information succinctly. The lengths you must go with prompts to ensure you're getting the right response is extremely similar to the lengths you go to when delegating something to someone or describing requirements to a project. I wonder if whatever language we end up using to "converse" with LLMs would have value within an organization/email/Jira.

> I’m not an LLM, but English is already pretty awful for conveying information succinctly. The lengths you must go with prompts to ensure you’re getting the right response is extremely similar to the lengths you go to when delegating something to someone or describing requirements to a project. I wonder if whatever language we end up using to “converse” with LLMs would have value within an organization/email/Jira.

People already adopt context-specific specialized languages in contexts like that for clarity, what will probably happen is that LLMs will get better at adapting or being adapted to specific contexts.

I prefix my longer prompts with glossaries. It lets me write more succinctly.

I would love an example of this.

It's pretty simple, I just add a glossary of terms at the top.

When asking for creative but well-structured output that requires specific definitions of certain words to be useful, I've found it works best to use words for your terms that don't actually exist. Otherwise it seems to focus a bit more on the broader word more than it should rather than your definition, especially if you use it a lot.

I'm normally the type of Google person with doing minus or using other tags.

I totally gave that up with chatgpt and the magic of it is that it understands it so so we'll.

Sometimes I also switch to German in the middle of a sentence or use very vague words to describe something if the word is missing in my head.

Why do you find that funny?

That's chatgpt main function. What if we introduced a language that could be converted to another language that uses tool to speak to chatgpt.

We can then train an LLM to generate it though

Check out https://lmql.ai/

Can someone please compare guidance with lmql? I don’t wanna learn multiple programming languages to handle LLMs as that defeats the whole point.

I've been thinking about this a lot recently. Communicating with LLMs using Lobjan for less ambiguity in text, or some LLM optimized language that can inject the most amount of meaning per token. Or writing in a AI Optimized Programming Language that is easier for it to parse and reason about

JS > asm.js > wasm all over again

langchain caused more problems than it fixed. Really ugly software.

Please elaborate. So far it seems promising to me, but I started using it just recently.

for example see this:

https://itsbehnam.com/DetachGPT-Switching-to-Open-Source-Unc...

And their "what's next?" links to a project that relies on langchain[0].

[0] https://github.com/imartinez/privateGPT

That just says "I got an error with it", hardly an indictment.

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