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authorkqlio67 <166700875+kqlio67@users.noreply.github.com>2024-07-08 22:49:38 +0200
committerGitHub <noreply@github.com>2024-07-08 22:49:38 +0200
commita8ab2ad771152e9f53fcb730caac84e5430523ff (patch)
tree41c1c6ea45ad1a66072250ae17238dbf3cc26bdd /g4f/Provider/ReplicateHome.py
parentDelete g4f/Provider/Aichatos.py (diff)
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Diffstat (limited to 'g4f/Provider/ReplicateHome.py')
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diff --git a/g4f/Provider/ReplicateHome.py b/g4f/Provider/ReplicateHome.py
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+from __future__ import annotations
+from typing import Generator, Optional, Dict, Any, Union, List
+import random
+import asyncio
+import base64
+
+from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
+from ..typing import AsyncResult, Messages
+from ..requests import StreamSession, raise_for_status
+from ..errors import ResponseError
+from ..image import ImageResponse
+
+class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin):
+ url = "https://replicate.com"
+ parent = "Replicate"
+ working = True
+ default_model = 'stability-ai/sdxl'
+ models = [
+ # image
+ 'stability-ai/sdxl',
+ 'ai-forever/kandinsky-2.2',
+
+ # text
+ 'meta/llama-2-70b-chat',
+ 'mistralai/mistral-7b-instruct-v0.2'
+ ]
+
+ versions = {
+ # image
+ 'stability-ai/sdxl': [
+ "39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b",
+ "2b017d9b67edd2ee1401238df49d75da53c523f36e363881e057f5dc3ed3c5b2",
+ "7762fd07cf82c948538e41f63f77d685e02b063e37e496e96eefd46c929f9bdc"
+ ],
+ 'ai-forever/kandinsky-2.2': [
+ "ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a"
+ ],
+
+
+ # Text
+ 'meta/llama-2-70b-chat': [
+ "dp-542693885b1777c98ef8c5a98f2005e7"
+ ],
+ 'mistralai/mistral-7b-instruct-v0.2': [
+ "dp-89e00f489d498885048e94f9809fbc76"
+ ]
+ }
+
+ image_models = {"stability-ai/sdxl", "ai-forever/kandinsky-2.2"}
+ text_models = {"meta/llama-2-70b-chat", "mistralai/mistral-7b-instruct-v0.2"}
+
+ @classmethod
+ async def create_async_generator(
+ cls,
+ model: str,
+ messages: Messages,
+ **kwargs: Any
+ ) -> Generator[Union[str, ImageResponse], None, None]:
+ yield await cls.create_async(messages[-1]["content"], model, **kwargs)
+
+ @classmethod
+ async def create_async(
+ cls,
+ prompt: str,
+ model: str,
+ api_key: Optional[str] = None,
+ proxy: Optional[str] = None,
+ timeout: int = 180,
+ version: Optional[str] = None,
+ extra_data: Dict[str, Any] = {},
+ **kwargs: Any
+ ) -> Union[str, ImageResponse]:
+ headers = {
+ 'Accept-Encoding': 'gzip, deflate, br',
+ 'Accept-Language': 'en-US',
+ 'Connection': 'keep-alive',
+ 'Origin': cls.url,
+ 'Referer': f'{cls.url}/',
+ 'Sec-Fetch-Dest': 'empty',
+ 'Sec-Fetch-Mode': 'cors',
+ 'Sec-Fetch-Site': 'same-site',
+ 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36',
+ 'sec-ch-ua': '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"',
+ 'sec-ch-ua-mobile': '?0',
+ 'sec-ch-ua-platform': '"macOS"',
+ }
+
+ if version is None:
+ version = random.choice(cls.versions.get(model, []))
+ if api_key is not None:
+ headers["Authorization"] = f"Bearer {api_key}"
+
+ async with StreamSession(
+ proxies={"all": proxy},
+ headers=headers,
+ timeout=timeout
+ ) as session:
+ data = {
+ "input": {
+ "prompt": prompt,
+ **extra_data
+ },
+ "version": version
+ }
+ if api_key is None:
+ data["model"] = cls.get_model(model)
+ url = "https://homepage.replicate.com/api/prediction"
+ else:
+ url = "https://api.replicate.com/v1/predictions"
+ async with session.post(url, json=data) as response:
+ await raise_for_status(response)
+ result = await response.json()
+ if "id" not in result:
+ raise ResponseError(f"Invalid response: {result}")
+
+ while True:
+ if api_key is None:
+ url = f"https://homepage.replicate.com/api/poll?id={result['id']}"
+ else:
+ url = f"https://api.replicate.com/v1/predictions/{result['id']}"
+ async with session.get(url) as response:
+ await raise_for_status(response)
+ result = await response.json()
+ if "status" not in result:
+ raise ResponseError(f"Invalid response: {result}")
+ if result["status"] == "succeeded":
+ output = result['output']
+ if model in cls.text_models:
+ return ''.join(output) if isinstance(output, list) else output
+ elif model in cls.image_models:
+ images: List[Any] = output
+ images = images[0] if len(images) == 1 else images
+ return ImageResponse(images, prompt)
+ elif result["status"] == "failed":
+ raise ResponseError(f"Prediction failed: {result}")
+ await asyncio.sleep(0.5)