mirror of
https://github.com/xtekky/gpt4free.git
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75 lines
2.4 KiB
Python
75 lines
2.4 KiB
Python
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from __future__ import annotations
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from aiohttp import ClientSession
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import json
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from ...typing import AsyncResult, Messages
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from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from ...image import ImageResponse
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class NexraDallE2(AsyncGeneratorProvider, ProviderModelMixin):
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label = "Nexra DALL-E 2"
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url = "https://nexra.aryahcr.cc/documentation/dall-e/en"
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api_endpoint = "https://nexra.aryahcr.cc/api/image/complements"
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working = True
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default_model = 'dalle2'
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models = [default_model]
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model_aliases = {
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"dalle-2": "dalle2",
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}
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@classmethod
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def get_model(cls, model: str) -> str:
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if model in cls.models:
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return model
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elif model in cls.model_aliases:
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return cls.model_aliases[model]
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else:
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return cls.default_model
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: Messages,
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proxy: str = None,
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response: str = "url", # base64 or url
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**kwargs
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) -> AsyncResult:
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# Retrieve the correct model to use
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model = cls.get_model(model)
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# Format the prompt from the messages
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prompt = messages[0]['content']
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headers = {
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"Content-Type": "application/json"
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}
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payload = {
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"prompt": prompt,
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"model": model,
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"response": response
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}
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async with ClientSession(headers=headers) as session:
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async with session.post(cls.api_endpoint, json=payload, proxy=proxy) as response:
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response.raise_for_status()
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text_data = await response.text()
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try:
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# Parse the JSON response
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json_start = text_data.find('{')
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json_data = text_data[json_start:]
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data = json.loads(json_data)
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# Check if the response contains images
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if 'images' in data and len(data['images']) > 0:
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image_url = data['images'][0]
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yield ImageResponse(image_url, prompt)
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else:
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yield ImageResponse("No images found in the response.", prompt)
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except json.JSONDecodeError:
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yield ImageResponse("Failed to parse JSON. Response might not be in JSON format.", prompt)
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