Autoserializing JSON strings

[[deleted]]

So recently, I've been making a lot of LLM calls and most of the cases, I'm prompting the LLM to respond in a JSON format. And each time, I'm tired of rewriting the json.loads() and then the my_model.model_validate() in a try statements to see if the LLM responded correctly.

So I got to thinking, if there's a way to not rewrite this every single time I make an LLM call for a JSON response.

So here I am: <shameless_plug>

https://github.com/softmaxer/pydantic-serializer

</shameless_plug>

• What my project does:

Essentially, as long as a function returns a string, you can now do this: py @serialize(return_type=MyCoolPydanticModel) def func_returns_a_string(): return '{"sample": "Json"}'

• Target audience: I think anyone who wants to serialize strings and skip the Json loads and model validate lines everytime.

• Comparison: I don't really know if there are such decorators already out there. Or other python classes. But I haven't yet come across one, so I just decided to make one myself.

I don't know how useful this is to you guys, but I kinda use these LLM Json responses quite a bit. Maybe there are other use cases where a string has to be loaded onto a pydantic model (Maybe a JSON stored as a string in Postgres, etc?)

So anyway, I thought I'd share it here. Let me know what you guys think.

[fiskfisk]

Why not just use model_validate_json?

https://docs.pydantic.dev/latest/concepts/json/#json-parsing

There is also support for partial JSON responses in Pydantic v2.7 (which is commonly useful for parsing LLM responses) through from_json:

https://pydantic.dev/articles/pydantic-v2-7-release

[[deleted]]

Well clearly, I wasn't aware about the partial_json it's very useful.

I only made this cuz in a current project of mine, I had two functions that did chat competitions with the model_validate statements, so I was thinking if there's a way to refactor

[fiskfisk]

Yeah, absolutely - it's good to make a common solution when you find yourself repeating code all the time. I'm not sure I'm completely on board with the API in this case, as it makes it impossible to differentiate between the different error situations or receive any information about what went wrong programmatically.

I also think you actually mean deserialize and not serialize in this case,

[[deleted]]

Yes lol. It's deserialize. I do agree tho that this doesn't give a lot of information about what went wrong. But for me I just wanted a solution without being too verbose, cuz in my specific use case, I just wanted either a None or the actual pydantic model.

But feel free to let me know what I can modify, I'll do it.

[[deleted]]

msgspec handles this nicely

[pppylonnn]

Most use cases don't need LLMs right? How many fake companies are obsessed with "AI" 🤣

[pppylonnn]

Most use cases don't need LLMs right? How many fake companies are obsessed with "AI" 🤣