Earlier quoted context omitted.
My bad, I think I didnt explain correctly. Basically you have two options when a "," is missing (amongst other issues) in an LLM output which causes a parsing issue: - retry the request, which may take 30+ secs (if your LLM outputs are really long and you're using something like gpt4) - fix the parsing issue In our library we do the latter. The conversion from BAML types to Pydantic ones is a compile-time step unrela…
Thanks for the clarification. How do you handle dynamic types, ie types determined at runtime?
we recently added dynamic type support with this snippet! (docs coming soon!)
Python: https://github.com/BoundaryML/baml/blob/413fdf12a0c8c1ebb75c...
Typescript: https://github.com/BoundaryML/baml/blob/413fdf12a0c8c1ebb75c...
Snippet:
async def test_dynamic():
tb = TypeBuilder()
tb.Person.add_property("last_name", tb.string().list())
tb.Person.add_property("height", tb.float().optional()).description(
"Height in meters"
)
tb.Hobby.add_value("chess")
for name, val in tb.Hobby.list_values():
val.alias(name.lower())
tb.Person.add_property("hobbies", tb.Hobby.type().list()).description(
"Some suggested hobbies they might be good at"
)
# no_tb_res = await b.ExtractPeople("My name is Harrison. My hair is black and I'm 6 feet tall.")
tb_res = await b.ExtractPeople(
"My name is Harrison. My hair is black and I'm 6 feet tall. I'm pretty good around the hoop.",
{"tb": tb},
)
assert len(tb_res) > 0, "Expected non-empty result but got empty."
for r in tb_res:
print(r.model_dump())