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-rw-r--r--g4f/Provider/nexra/NexraAnimagineXL.py66
1 files changed, 66 insertions, 0 deletions
diff --git a/g4f/Provider/nexra/NexraAnimagineXL.py b/g4f/Provider/nexra/NexraAnimagineXL.py
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+from __future__ import annotations
+
+from aiohttp import ClientSession
+import json
+
+from ...typing import AsyncResult, Messages
+from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
+from ...image import ImageResponse
+
+
+class NexraAnimagineXL(AsyncGeneratorProvider, ProviderModelMixin):
+ label = "Nexra Animagine XL"
+ url = "https://nexra.aryahcr.cc/documentation/midjourney/en"
+ api_endpoint = "https://nexra.aryahcr.cc/api/image/complements"
+ working = True
+
+ default_model = 'animagine-xl'
+ models = [default_model]
+
+ @classmethod
+ def get_model(cls, model: str) -> str:
+ return cls.default_model
+
+ @classmethod
+ async def create_async_generator(
+ cls,
+ model: str,
+ messages: Messages,
+ proxy: str = None,
+ response: str = "url", # base64 or url
+ **kwargs
+ ) -> AsyncResult:
+ # Retrieve the correct model to use
+ model = cls.get_model(model)
+
+ # Format the prompt from the messages
+ prompt = messages[0]['content']
+
+ headers = {
+ "Content-Type": "application/json"
+ }
+ payload = {
+ "prompt": prompt,
+ "model": model,
+ "response": response
+ }
+
+ async with ClientSession(headers=headers) as session:
+ async with session.post(cls.api_endpoint, json=payload, proxy=proxy) as response:
+ response.raise_for_status()
+ text_data = await response.text()
+
+ try:
+ # Parse the JSON response
+ json_start = text_data.find('{')
+ json_data = text_data[json_start:]
+ data = json.loads(json_data)
+
+ # Check if the response contains images
+ if 'images' in data and len(data['images']) > 0:
+ image_url = data['images'][0]
+ yield ImageResponse(image_url, prompt)
+ else:
+ yield ImageResponse("No images found in the response.", prompt)
+ except json.JSONDecodeError:
+ yield ImageResponse("Failed to parse JSON. Response might not be in JSON format.", prompt)