from typing import List
import rich
from pydantic import BaseModel
from openai import OpenAI
class Step(BaseModel):
explanation: str
output: str
class MathResponse(BaseModel):
steps: List[Step]
final_answer: str
client = OpenAI()
rsp = client.responses.parse(
input="solve 8x + 31 = 2",
model="gpt-4o-2024-08-06",
text_format=MathResponse,
)
for output in rsp.output:
if output.type != "message":
raise Exception("Unexpected non message")
for item in output.content:
if item.type != "output_text":
raise Exception("unexpected output type")
if not item.parsed:
raise Exception("Could not parse response")
rich.print(item.parsed)
print("answer: ", item.parsed.final_answer)
# or
message = rsp.output[0]
assert message.type == "message"
text = message.content[0]
assert text.type == "output_text"
if not text.parsed:
raise Exception("Could not parse response")
rich.print(text.parsed)
print("answer: ", text.parsed.final_answer)openai/openai-python
Publicmirrored fromhttps://github.com/openai/openai-pythonAvailable
examples/responses/structured_outputs.py
55lines · modepreview