Any valid Pydantic type should be supported (e.g. TypedDict)
ADR-007 opened this issue · comments
Is your feature request related to a problem? Please describe.
Currently, only Pydantic models are supported as response_model.
But in some cases, I want to use TypedDict instead. For example, I don't want to do massive refactoring, so I just want to add response schema validation to an existing job.
Describe the solution you'd like
I would like to able to use TypedDict as response_model. E.g.:
class MyModel(TypedDict):
my_key: str
result = client.chat.completions.create(
messages=[...],
response_model=MyModel,
)It is very simple to implement in Pydantic V2:
from pydantic import TypeAdapter
adapter = TypeAdapter(MyModel)
json_schema = adapter.json_schema()
result = prcess_llm(prompt, json_schema, ...)
my_model = adapter.validate_python(result)
Happy to take or for this in process response.
@ADR-007 just pushed up a PR which introduces this. Is this what you had in mind for your use case?
from typing_extensions import TypedDict
from openai import OpenAI
import instructor
class User(TypedDict):
name: str
age: int
client = instructor.from_openai(OpenAI())
print(
client.chat.completions.create(
model="gpt-3.5-turbo",
response_model=User,
messages=[
{
"role": "user",
"content": "Timothy is a man from New York who is turning 32 this year",
}
],
)
)
"""
name='Timothy' age=32
"""@ivanleomk yes, thank you!
Oh. That PR is not yet merged, so I should leave this issue open
I would really like to have this implemented. It is currently the only thing that blocks me from using this library :(
we're close!