mirror of
https://github.com/xtekky/gpt4free.git
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84812b9632
Improve read access_token in OpenaiChat Add IterProvider Add system message support in FlowGpt Filter none values in new Client
218 lines
7.6 KiB
Python
218 lines
7.6 KiB
Python
from __future__ import annotations
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import re
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import os
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import time
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import random
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import string
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from .stubs import ChatCompletion, ChatCompletionChunk, Image, ImagesResponse
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from .typing import Union, Iterator, Messages, ImageType
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from .providers.types import BaseProvider, ProviderType
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from .image import ImageResponse as ImageProviderResponse
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from .Provider.BingCreateImages import BingCreateImages
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from .Provider.needs_auth import Gemini, OpenaiChat
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from .errors import NoImageResponseError
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from . import get_model_and_provider, get_last_provider
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ImageProvider = Union[BaseProvider, object]
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Proxies = Union[dict, str]
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IterResponse = Iterator[Union[ChatCompletion, ChatCompletionChunk]]
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def read_json(text: str) -> dict:
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"""
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Parses JSON code block from a string.
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Args:
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text (str): A string containing a JSON code block.
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Returns:
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dict: A dictionary parsed from the JSON code block.
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"""
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match = re.search(r"```(json|)\n(?P<code>[\S\s]+?)\n```", text)
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if match:
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return match.group("code")
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return text
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def iter_response(
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response: iter[str],
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stream: bool,
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response_format: dict = None,
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max_tokens: int = None,
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stop: list = None
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) -> IterResponse:
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content = ""
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finish_reason = None
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completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28))
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for idx, chunk in enumerate(response):
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content += str(chunk)
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if max_tokens is not None and idx + 1 >= max_tokens:
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finish_reason = "length"
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first = -1
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word = None
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if stop is not None:
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for word in list(stop):
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first = content.find(word)
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if first != -1:
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content = content[:first]
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break
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if stream and first != -1:
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first = chunk.find(word)
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if first != -1:
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chunk = chunk[:first]
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else:
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first = 0
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if first != -1:
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finish_reason = "stop"
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if stream:
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yield ChatCompletionChunk(chunk, None, completion_id, int(time.time()))
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if finish_reason is not None:
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break
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finish_reason = "stop" if finish_reason is None else finish_reason
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if stream:
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yield ChatCompletionChunk(None, finish_reason, completion_id, int(time.time()))
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else:
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if response_format is not None and "type" in response_format:
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if response_format["type"] == "json_object":
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content = read_json(content)
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yield ChatCompletion(content, finish_reason, completion_id, int(time.time()))
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def iter_append_model_and_provider(response: IterResponse) -> IterResponse:
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last_provider = None
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for chunk in response:
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last_provider = get_last_provider(True) if last_provider is None else last_provider
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chunk.model = last_provider.get("model")
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chunk.provider = last_provider.get("name")
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yield chunk
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class Client():
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def __init__(
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self,
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api_key: str = None,
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proxies: Proxies = None,
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provider: ProviderType = None,
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image_provider: ImageProvider = None,
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**kwargs
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) -> None:
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self.api_key: str = api_key
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self.proxies: Proxies = proxies
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self.chat: Chat = Chat(self, provider)
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self.images: Images = Images(self, image_provider)
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def get_proxy(self) -> Union[str, None]:
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if isinstance(self.proxies, str):
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return self.proxies
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elif self.proxies is None:
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return os.environ.get("G4F_PROXY")
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elif "all" in self.proxies:
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return self.proxies["all"]
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elif "https" in self.proxies:
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return self.proxies["https"]
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def filter_none(**kwargs):
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for key in list(kwargs.keys()):
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if kwargs[key] is None:
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del kwargs[key]
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return kwargs
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class Completions():
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def __init__(self, client: Client, provider: ProviderType = None):
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self.client: Client = client
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self.provider: ProviderType = provider
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def create(
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self,
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messages: Messages,
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model: str,
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provider: ProviderType = None,
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stream: bool = False,
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response_format: dict = None,
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max_tokens: int = None,
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stop: Union[list[str], str] = None,
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api_key: str = None,
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**kwargs
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) -> Union[ChatCompletion, Iterator[ChatCompletionChunk]]:
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model, provider = get_model_and_provider(
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model,
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self.provider if provider is None else provider,
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stream,
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**kwargs
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)
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stop = [stop] if isinstance(stop, str) else stop
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response = provider.create_completion(
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model, messages, stream,
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**filter_none(
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proxy=self.client.get_proxy(),
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max_tokens=max_tokens,
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stop=stop,
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api_key=self.client.api_key if api_key is None else api_key
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),
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**kwargs
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)
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response = iter_response(response, stream, response_format, max_tokens, stop)
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response = iter_append_model_and_provider(response)
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return response if stream else next(response)
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class Chat():
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completions: Completions
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def __init__(self, client: Client, provider: ProviderType = None):
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self.completions = Completions(client, provider)
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class ImageModels():
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gemini = Gemini
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openai = OpenaiChat
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def __init__(self, client: Client) -> None:
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self.client = client
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self.default = BingCreateImages(proxy=self.client.get_proxy())
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def get(self, name: str, default: ImageProvider = None) -> ImageProvider:
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return getattr(self, name) if hasattr(self, name) else default or self.default
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class Images():
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def __init__(self, client: Client, provider: ImageProvider = None):
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self.client: Client = client
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self.provider: ImageProvider = provider
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self.models: ImageModels = ImageModels(client)
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def generate(self, prompt, model: str = None, **kwargs):
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provider = self.models.get(model, self.provider)
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if isinstance(provider, BaseProvider) or isinstance(provider, type) and issubclass(provider, BaseProvider):
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prompt = f"create a image: {prompt}"
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response = provider.create_completion(
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"",
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[{"role": "user", "content": prompt}],
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True,
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proxy=self.client.get_proxy(),
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**kwargs
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)
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else:
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response = provider.create(prompt)
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for chunk in response:
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if isinstance(chunk, ImageProviderResponse):
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images = [chunk.images] if isinstance(chunk.images, str) else chunk.images
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return ImagesResponse([Image(image) for image in images])
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raise NoImageResponseError()
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def create_variation(self, image: ImageType, model: str = None, **kwargs):
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provider = self.models.get(model, self.provider)
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result = None
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if isinstance(provider, type) and issubclass(provider, BaseProvider):
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response = provider.create_completion(
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"",
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[{"role": "user", "content": "create a image like this"}],
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True,
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image=image,
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proxy=self.client.get_proxy(),
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**kwargs
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)
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for chunk in response:
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if isinstance(chunk, ImageProviderResponse):
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result = ([chunk.images] if isinstance(chunk.images, str) else chunk.images)
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result = ImagesResponse([Image(image)for image in result])
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if result is None:
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raise NoImageResponseError()
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return result |