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chore: import upstream snapshot with attribution
2026-07-13 13:36:38 +08:00

79 lines
1.4 KiB
Python

import instructor
from openai import OpenAI
from pydantic import BaseModel, Field
from typing import Optional
client = instructor.from_openai(OpenAI())
class UserDetail(BaseModel):
age: int
name: str
role: Optional[str] = Field(default=None)
MaybeUser = instructor.Maybe(UserDetail)
def get_user_detail(string) -> MaybeUser: # type: ignore
return client.chat.completions.create(
model="gpt-4o-mini",
response_model=MaybeUser,
messages=[
{
"role": "user",
"content": f"Get user details for {string}",
},
],
) # type: ignore
user = get_user_detail("Jason is 25 years old")
print(user.model_dump_json(indent=2))
"""
{
"user": {
"age": 25,
"name": "Jason",
"role": null
},
"error": false,
"message": null
}
"""
user = get_user_detail("Jason is a 25 years old scientist")
print(user.model_dump_json(indent=2))
"""
{
"user": {
"age": 25,
"name": "Jason",
"role": "scientist"
},
"error": false,
"message": null
}
"""
# ! notice that the string should not contain anything
# ! but a user and age was still extracted ?!
user = get_user_detail("User not found")
print(user.model_dump_json(indent=2))
"""
{
"user": null,
"error": true,
"message": "User not found"
}
"""
# ! due to the __bool__ method, you can use the MaybeUser object as a boolean
if not user:
print("Detected error")
"""
Detected error
"""