Encountering a 500 error when calling responses.parse on a schema containing decimal.Decimal fields.

Fermée
  • Quelque chose ne va pas ?
#2,718 1 commentaire 0 réactions 0 personnes assignées Voir sur GitHub

Les mainteneurs répondent en général sous 1 jour

Personne n'a encore pris cette issue.

  • #2733 par @yashwantbezawada — fermée sans fusion

Évaluation

Difficulté
4/5
Temps estimé
3-5 jours
Accessibilité débutants
35/100
Type d'issue
Bug
Clarté
À clarifier
Activité
À l'abandon
Stack technique
python
Domaine
api

Piste de recherche

Commencez par reproduire le script fourni et comparez responses.parse avec StringModel, FloatModel et DecimalModel, en particulier le schéma Pydantic généré pour les champs Decimal. Suivez la manière dont la bibliothèque gère ce schéma et ajoutez un test de régression ; le travail sera terminé lorsque DecimalModel fonctionnera avec gpt-5 sans l’erreur 500 signalée.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Description

api bug
Confirm this is an issue with the Python library and not an underlying OpenAI API
  • This is an issue with the Python library
Describe the bug

The responses.parse() method fails when the Pydantic model contains decimal.Decimal type fields.

To Reproduce

Run this test script below


import logging
from decimal import Decimal
from typing import Optional
from pydantic import BaseModel, Field
from openai import OpenAI

# Set up logger
logging.basicConfig(level=logging.INFO, format='%(message)s')
logger = logging.getLogger(__name__)

# Define test models
class DecimalModel(BaseModel):
    """Model with Decimal fields."""
    premium: Optional[Decimal] = Field(default=None, description="Premium amount")
    amount: Optional[Decimal] = Field(default=None, description="Total amount")

class FloatModel(BaseModel):
    """Model with float fields."""
    premium: Optional[float] = Field(default=None, description="Premium amount")
    amount: Optional[float] = Field(default=None, description="Total amount")

class StringModel(BaseModel):
    """Model with string fields."""
    premium: Optional[str] = Field(default=None, description="Premium amount")
    amount: Optional[str] = Field(default=None, description="Total amount")

# Initialize client and test data
client = OpenAI()
test_content = "The premium is $5,000.00 and the total amount is $5,500.50"

request_model = "gpt-5"
# request_model = "gpt-5-mini" # Uncomment to test with a mini
# Test String Model
try:
    response = client.responses.parse(
        model=request_model,
        input=[
            {"role": "system", "content": "Extract the financial amounts."},
            {"role": "user", "content": test_content}
        ],
        text_format=StringModel,
    )
    logger.info(f"StringModel: WORKS. Data: {response.output_parsed.model_dump_json()}")
except Exception as e:
    logger.error(f"StringModel: FAILED - {type(e).__name__}")
    logger.exception(e)

# Test Float Model
try:
    response = client.responses.parse(
        model=request_model,
        input=[
            {"role": "system", "content": "Extract the financial amounts."},
            {"role": "user", "content": test_content}
        ],
        text_format=FloatModel,
    )
    logger.info(f"FloatModel: WORKS. Data: {response.output_parsed.model_dump_json()}")
except Exception as e:
    logger.error(f"FloatModel: FAILED - {type(e).__name__}")
    logger.exception(e)

# Test Decimal Model
try:
    response = client.responses.parse(
        model=request_model,
        input=[
            {"role": "system", "content": "Extract the financial amounts."},
            {"role": "user", "content": test_content}
        ],
        text_format=DecimalModel,
    )
    logger.info(f"DecimalModel: WORKS. Data: {response.output_parsed.model_dump_json()}")
except Exception as e:
    logger.error(f"DecimalModel: FAILED - {type(e).__name__}")
    logger.exception(e)

Output with gpt-5

> python test_decimal_extraction.py
HTTP Request: POST https://api.openai.com/v1/responses "HTTP/1.1 200 OK"
StringModel: WORKS. Data: {"premium":"$5,000.00","amount":"$5,500.50"}
HTTP Request: POST https://api.openai.com/v1/responses "HTTP/1.1 200 OK"
FloatModel: WORKS. Data: {"premium":5000.0,"amount":5500.5}
HTTP Request: POST https://api.openai.com/v1/responses "HTTP/1.1 500 Internal Server Error"
Retrying request to /responses in 0.459931 seconds
HTTP Request: POST https://api.openai.com/v1/responses "HTTP/1.1 500 Internal Server Error"
Retrying request to /responses in 0.893894 seconds
HTTP Request: POST https://api.openai.com/v1/responses "HTTP/1.1 500 Internal Server Error"
DecimalModel: FAILED - InternalServerError
Error code: 500 - {'error': {'message': 'An error occurred while processing your request. You can retry your request, or contact us through our help center at help.openai.com if the error persists. Please include the request ID req_2e82ffe03e6d45f38ad7ff9b98a62ec4 in your message.', 'type': 'server_error', 'param': None, 'code': 'server_error'}}

Works as expected with gpt-5-mini

> python test_decimal_extraction.py
HTTP Request: POST https://api.openai.com/v1/responses "HTTP/1.1 200 OK"
StringModel: WORKS. Data: {"premium":"$5,000.00","amount":"$5,500.50"}
HTTP Request: POST https://api.openai.com/v1/responses "HTTP/1.1 200 OK"
FloatModel: WORKS. Data: {"premium":5000.0,"amount":5500.5}
HTTP Request: POST https://api.openai.com/v1/responses "HTTP/1.1 200 OK"
DecimalModel: WORKS. Data: {"premium":"5000.00","amount":"5500.50"}
Code snippets
OS

Debian GNU/Linux

Python version

3.12.10

Library version

openai v1.109.1

Langage dominant
Python
Étoiles
32k
Forks
6.7k
Merge moyen
16 h 48 min
PR mergées (30 j)
185

Préparer son environnement

Ouvrir dans Codespaces

Lance le conteneur de développement du projet dans votre navigateur, avec votre propre compte GitHub.

Par où commencer

  1. Lisez l'issue en entier, puis le guide de contribution du projet.
  2. Signalez en commentaire que vous la prenez — cela évite que deux personnes fassent le même travail.
  3. Forkez le dépôt et travaillez sur une branche.
  4. Ouvrez une pull request qui référence le numéro de l'issue.

Autres issues de openai/openai-python

Toutes les issues de openai/openai-python

Issues similaires

Plus d'issues Python

Recevez les nouvelles issues par e-mail

Un résumé court des issues GitHub adaptées aux débutants.