Upgrade to OpenAI Python SDK v1.X

Convert OpenAI from openai version to the v1 version.

Apply with the Grit CLI

grit apply openai

Change openai import to Sync

BEFORE

import openai

completion = openai.Completion.create(model="davinci-002", prompt="Hello world")
chat_completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

AFTER

from openai import OpenAI

client = OpenAI()

completion = client.completions.create(model="davinci-002", prompt="Hello world")
chat_completion = client.chat.completions.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

Change openai import to Async

BEFORE

import openai

completion = await openai.Completion.acreate(model="davinci-002", prompt="Hello world")
chat_completion = await openai.ChatCompletion.acreate(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

AFTER

from openai import AsyncOpenAI

aclient = AsyncOpenAI()

completion = await aclient.completions.create(model="davinci-002", prompt="Hello world")
chat_completion = await aclient.chat.completions.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

Change openai import to Both

BEFORE

import openai

completion = openai.Completion.create(model="davinci-002", prompt="Hello world")
chat_completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

a_completion = await openai.Completion.acreate(model="davinci-002", prompt="Hello world")
a_chat_completion = await openai.ChatCompletion.acreate(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

AFTER

from openai import OpenAI, AsyncOpenAI

client = OpenAI()
aclient = AsyncOpenAI()

completion = client.completions.create(model="davinci-002", prompt="Hello world")
chat_completion = client.chat.completions.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

a_completion = await aclient.completions.create(model="davinci-002", prompt="Hello world")
a_chat_completion = await aclient.chat.completions.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

Change different kinds of import

BEFORE

import openai
from openai import ChatCompletion

completion = openai.Completion.create(model="davinci-002", prompt="Hello world")
chat_completion = await ChatCompletion.acreate(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

AFTER

from openai import OpenAI, AsyncOpenAI

client = OpenAI()
aclient = AsyncOpenAI()

completion = client.completions.create(model="davinci-002", prompt="Hello world")
chat_completion = await aclient.chat.completions.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

Manual config required

BEFORE

import openai

if openai_proxy:
    openai.proxy = openai_proxy
    openai.api_base = self.openai_api_base

AFTER

import openai

if openai_proxy:
    # TODO: The 'openai.proxy' option isn't read in the client API. You will need to pass it when you instantiate the client, e.g. 'OpenAI(proxy=openai_proxy)'
    # openai.proxy = openai_proxy
    # TODO: The 'openai.api_base' option isn't read in the client API. You will need to pass it when you instantiate the client, e.g. 'OpenAI(base_url=self.openai_api_base)'
    # openai.api_base = self.openai_api_base

Remap errors

BEFORE

import openai

try:
    completion = openai.Completion.create(model="davinci-002", prompt="Hello world")
    chat_completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])
except openai.error.RateLimitError as err:
    pass

AFTER

import openai
from openai import OpenAI

client = OpenAI()

try:
    completion = client.completions.create(model="davinci-002", prompt="Hello world")
    chat_completion = client.chat.completions.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])
except openai.RateLimitError as err:
    pass

Mark deprecated api usage

BEFORE

import openai

completion = openai.Customer.create(model="davinci-002", prompt="Hello world")
chat_completion = openai.Deployment.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

AFTER

import openai

# TODO: The resource 'Customer' has been deprecated
# completion = openai.Customer.create(model="davinci-002", prompt="Hello world")
# TODO: The resource 'Deployment' has been deprecated
# chat_completion = openai.Deployment.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])

Migrate unittest

BEFORE

@patch('openai.Completion')
@patch('openai.Customer')
def test(MockClass1, MockClass2):
    with patch.object(openai.Completion, 'method', return_value=None):
        pass
    with patch.object(openai.Customer, 'method', return_value=None):
        pass
    with patch("openai.Engine.list"):
        pass
    pass

AFTER

@patch('openai.resources.Completions')
# TODO: The resource 'Customer' has been deprecated
# @patch('openai.Customer')
def test(MockClass1, MockClass2):
    with patch.object(openai.resources.Completions, 'method', return_value=None):
        pass
    # TODO: The resource 'Customer' has been deprecated
    # with patch.object(openai.Customer, 'method', return_value=None):
    #         pass
    # TODO: The resource 'Engine' has been deprecated
    # with patch("openai.Engine.list"):
    #         pass
    pass

Migrate pytest

BEFORE

@pytest.fixture
def mocked_GET_pos(monkeypatch):
    monkeypatch.setattr(openai.Completion, 'GET', lambda: True)
    monkeypatch.delattr(openai.Completion, 'PUT', lambda: True)

@pytest.fixture
def mocked_GET_neg(monkeypatch):
    monkeypatch.setattr(openai.Customer, 'GET', lambda: False)

@pytest.fixture
def mocked_GET_raises(monkeypatch, other):
    def raise_():
        raise Exception()
    monkeypatch.setattr(openai.Engine.list, 'GET', raise_)
    monkeypatch.delattr(openai.Engine.list, 'PUT', lambda: True)

AFTER

@pytest.fixture
def mocked_GET_pos(monkeypatch):
    monkeypatch.setattr(openai.resources.Completions, 'GET', lambda: True)
    monkeypatch.delattr(openai.resources.Completions, 'PUT', lambda: True)

@pytest.fixture
def mocked_GET_neg(monkeypatch):
    # TODO: The resource 'Customer' has been deprecated
    # monkeypatch.setattr(openai.Customer, 'GET', lambda: False)

@pytest.fixture
def mocked_GET_raises(monkeypatch, other):
    def raise_():
        raise Exception()
    # TODO: The resource 'Engine' has been deprecated
    # monkeypatch.setattr(openai.Engine.list, 'GET', raise_)
    # TODO: The resource 'Engine' has been deprecated
    # monkeypatch.delattr(openai.Engine.list, 'PUT', lambda: True)

Image creation has been renamed

The Image.create method has been renamed to image.generate.

BEFORE

import openai

openai.Image.create(file=file)

AFTER

from openai import OpenAI

client = OpenAI()

client.images.generate(file=file)

Use Azure OpenAI

If api_type is set to Azure before, you should now use the AzureOpenAI client.

BEFORE

import os
import openai

openai.api_type = "azure"
openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT")
openai.api_key = os.getenv("AZURE_OPENAI_KEY")
openai.api_version = "2023-05-15"

response = openai.ChatCompletion.create(
    engine="gpt-35-turbo",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
    ]
)

AFTER

import os
from openai import AzureOpenAI

client = AzureOpenAI(
  azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
  api_key=os.getenv("AZURE_OPENAI_KEY"),
  api_version="2023-05-15"
)


response = client.chat.completions.create(
  model="gpt-35-turbo",
  messages=[
    {"role": "system", "content": "You are a helpful assistant."},
  ]
)

Fix subscripting

The new API does not support subscripting on the outputs.

BEFORE

import openai

model, token_limit, prompt_cost, comp_cost = 'gpt-4-32k', 32_768, 0.06, 0.12

completion = openai.ChatCompletion.create(
    model=model,
    messages=[
        {"role": "system", "content": system},
        {"role": "user", "content":
         user + text},
    ]
)
output = completion['choices'][0]['message']['content']

prom = completion['usage']['prompt_tokens']
comp = completion['usage']['completion_tokens']

# unrelated variable
foo = something['else']

AFTER

from openai import OpenAI

client = OpenAI()

model, token_limit, prompt_cost, comp_cost = 'gpt-4-32k', 32_768, 0.06, 0.12

completion = client.chat.completions.create(model=model,
messages=[
    {"role": "system", "content": system},
    {"role": "user", "content":
     user + text},
])
output = completion.choices[0].message.content

prom = completion.usage.prompt_tokens
comp = completion.usage.completion_tokens

# unrelated variable
foo = something['else']

Fix completion streaming

BEFORE

import openai

completion = openai.ChatCompletion.create(
    model=model,
    messages=[
        {"role": "system", "content": system},
        {"role": "user", "content":
         user + text},
    ],
    stream=True
)

for chunk in completion:
    print(chunk)
    print(chunk.choices[0].delta.get("content"))
    print("****************")

AFTER

from openai import OpenAI

client = OpenAI()

completion = client.chat.completions.create(model=model,
  messages=[
      {"role": "system", "content": system},
      {"role": "user", "content":
      user + text},
  ],
  stream=True
)

for chunk in completion:
    print(chunk)
    print(chunk.choices[0].delta.content)
    print("****************")

Fix multiple exceptions

Repair https://github.com/openai/openai-python/issues/1165, ensure we fix all exceptions in one pass.

BEFORE

try:
   # Some completions handler
   pass
except openai.error.RateLimitError as e:
   print(e)
except openai.error.AuthenticationError as e:
   print(e)
except openai.error.InvalidRequestError as e:
    print(e)

Fixed:

AFTER

try:
   # Some completions handler
   pass
except openai.RateLimitError as e:
   print(e)
except openai.AuthenticationError as e:
   print(e)
except openai.InvalidRequestError as e:
    print(e)