mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-12-23 19:11:48 +03:00
109 lines
4.3 KiB
Python
109 lines
4.3 KiB
Python
from __future__ import annotations
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from urllib.parse import quote
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import random
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import requests
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from aiohttp import ClientSession
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from ..typing import AsyncResult, Messages
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from ..image import ImageResponse
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from ..requests.raise_for_status import raise_for_status
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from ..requests.aiohttp import get_connector
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from .needs_auth.OpenaiAPI import OpenaiAPI
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from .helper import format_prompt
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class PollinationsAI(OpenaiAPI):
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label = "Pollinations AI"
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url = "https://pollinations.ai"
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working = True
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needs_auth = False
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supports_stream = True
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api_base = "https://text.pollinations.ai/openai"
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default_model = "openai"
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additional_models_image = ["midjourney", "dall-e-3"]
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additional_models_text = ["sur", "sur-mistral", "claude"]
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model_aliases = {
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"gpt-4o": "openai",
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"mistral-nemo": "mistral",
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"llama-3.1-70b": "llama", #
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"gpt-4": "searchgpt",
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"gpt-4": "claude",
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"qwen-2.5-coder-32b": "qwen-coder",
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"claude-3.5-sonnet": "sur",
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}
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36"
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}
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@classmethod
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def get_models(cls, **kwargs):
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if not hasattr(cls, 'image_models'):
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cls.image_models = []
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if not cls.image_models:
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url = "https://image.pollinations.ai/models"
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response = requests.get(url, headers=cls.headers)
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raise_for_status(response)
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cls.image_models = response.json()
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cls.image_models.extend(cls.additional_models_image)
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if not hasattr(cls, 'models'):
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cls.models = []
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if not cls.models:
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url = "https://text.pollinations.ai/models"
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response = requests.get(url, headers=cls.headers)
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raise_for_status(response)
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cls.models = [model.get("name") for model in response.json()]
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cls.models.extend(cls.image_models)
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cls.models.extend(cls.additional_models_text)
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return cls.models
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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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prompt: str = None,
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api_key: str = None,
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proxy: str = None,
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seed: str = None,
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width: int = 1024,
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height: int = 1024,
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**kwargs
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) -> AsyncResult:
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model = cls.get_model(model)
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if model in cls.image_models:
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async for response in cls._generate_image(model, messages, prompt, proxy, seed, width, height):
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yield response
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elif model in cls.models:
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async for response in cls._generate_text(model, messages, api_key, proxy, **kwargs):
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yield response
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else:
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raise ValueError(f"Unknown model: {model}")
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@classmethod
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async def _generate_image(cls, model: str, messages: Messages, prompt: str = None, proxy: str = None, seed: str = None, width: int = 1024, height: int = 1024):
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if prompt is None:
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prompt = messages[-1]["content"]
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if seed is None:
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seed = random.randint(0, 100000)
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image = f"https://image.pollinations.ai/prompt/{quote(prompt)}?width={width}&height={height}&seed={int(seed)}&nofeed=true&nologo=true&model={quote(model)}"
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async with ClientSession(connector=get_connector(proxy=proxy), headers=cls.headers) as session:
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async with session.get(image) as response:
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await raise_for_status(response)
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yield ImageResponse(image, prompt)
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@classmethod
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async def _generate_text(cls, model: str, messages: Messages, api_key: str = None, proxy: str = None, **kwargs):
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if api_key is None:
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async with ClientSession(connector=get_connector(proxy=proxy), headers=cls.headers) as session:
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prompt = format_prompt(messages)
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async with session.get(f"https://text.pollinations.ai/{quote(prompt)}?model={quote(model)}") as response:
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await raise_for_status(response)
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async for line in response.content.iter_any():
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yield line.decode(errors="ignore")
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else:
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async for chunk in super().create_async_generator(
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model, messages, proxy=proxy, **kwargs
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):
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yield chunk |