mirror of
https://github.com/xtekky/gpt4free.git
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54ef1a511c
- Added "No auth / HAR file" authentication type in providers-and-models.md - Added "Video generation" column to provider tables for future capability - Updated model counts and provider capabilities throughout documentation - Fixed ARTA provider with improved error handling and response validation - Enhanced AllenAI provider with vision model support and proper image handling - Significantly improved Blackbox provider: - Added HAR file authentication support - Added subscription status checking - Added premium/demo model differentiation - Improved session handling and error recovery - Enhanced DDG provider with better error handling for challenges - Improved PollinationsAI and PollinationsImage providers' model handling - Added VideoModel class in g4f/models.py - Added audio/video generation indicators in GUI components - Added new Ai2 models: olmo-1-7b, olmo-2-32b, olmo-4-synthetic - Added new commit message generation tool in etc/tool/commit.py
70 lines
2.1 KiB
Python
70 lines
2.1 KiB
Python
from __future__ import annotations
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from typing import Optional
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from .helper import format_image_prompt
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from ..typing import AsyncResult, Messages
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from .PollinationsAI import PollinationsAI
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class PollinationsImage(PollinationsAI):
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label = "PollinationsImage"
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default_model = "flux"
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default_vision_model = None
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default_image_model = default_model
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audio_models = None
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image_models = [default_image_model] # Default models
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_models_loaded = False # Add a checkbox for synchronization
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@classmethod
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def get_models(cls, **kwargs):
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if not cls._models_loaded:
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# Calling the parent method to load models
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super().get_models()
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# Combine models from the parent class and additional ones
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all_image_models = list(dict.fromkeys(
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cls.image_models +
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PollinationsAI.image_models +
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cls.extra_image_models
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))
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cls.image_models = all_image_models
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cls._models_loaded = True
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return cls.image_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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proxy: str = None,
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prompt: str = None,
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aspect_ratio: str = "1:1",
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width: int = None,
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height: int = None,
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seed: Optional[int] = None,
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cache: bool = False,
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nologo: bool = True,
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private: bool = False,
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enhance: bool = False,
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safe: bool = False,
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n: int = 4,
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**kwargs
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) -> AsyncResult:
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# Calling model updates before creating a generator
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cls.get_models()
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async for chunk in cls._generate_image(
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model=model,
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prompt=format_image_prompt(messages, prompt),
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proxy=proxy,
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aspect_ratio=aspect_ratio,
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width=width,
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height=height,
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seed=seed,
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cache=cache,
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nologo=nologo,
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private=private,
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enhance=enhance,
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safe=safe,
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n=n
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):
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yield chunk
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