Creating a model with completions¶
In instructor>1.0.0 we have a custom client, if you wish to use the raw response you can do the following
import instructor
from openai import OpenAI
from pydantic import BaseModel
client = instructor.from_openai(OpenAI())
class UserExtract(BaseModel):
name: str
age: int
user, completion = client.chat.completions.create_with_completion(
model="gpt-3.5-turbo",
response_model=UserExtract,
messages=[
{"role": "user", "content": "Extract jason is 25 years old"},
],
)
print(user)
#> name='Jason' age=25
print(completion)
"""
ChatCompletion(
id='chatcmpl-9TzoQBCR4ljqayllBj0U1PKfjGqiL',
choices=[
Choice(
finish_reason='stop',
index=0,
logprobs=None,
message=ChatCompletionMessage(
content=None,
role='assistant',
function_call=None,
tool_calls=[
ChatCompletionMessageToolCall(
id='call_Q5iev31AA2vUVoAdpBapGWK5',
function=Function(
arguments='{"name":"Jason","age":25}', name='UserExtract'
),
type='function',
)
],
),
)
],
created=1716936146,
model='gpt-3.5-turbo-0125',
object='chat.completion',
system_fingerprint=None,
usage=CompletionUsage(completion_tokens=9, prompt_tokens=82, total_tokens=91),
)
"""