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https://github.com/xtekky/gpt4free.git
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0a070bdf10
* feat: introduce AnyProvider & LM Arena, overhaul model/provider logic
- **Provider additions & removals**
- Added `Provider/LMArenaProvider.py` with full async stream implementation and vision model support
- Registered `LMArenaProvider` in `Provider/__init__.py`; removed old `hf_space/LMArenaProvider.py`
- Created `providers/any_provider.py`; registers `AnyProvider` dynamically in `Provider`
- **Provider framework enhancements**
- `providers/base_provider.py`
- Added `video_models` and `audio_models` attributes
- `providers/retry_provider.py`
- Introduced `is_content()` helper; now treats `AudioResponse` as stream content
- **Cloudflare provider refactor**
- `Provider/Cloudflare.py`
- Re‑implemented `get_models()` with `read_models()` helper, `fallback_models`, robust nodriver/curl handling and model‑name cleaning
- **Other provider tweaks**
- `Provider/Copilot.py` – removed `"reasoning"` alias and initial `setOptions` WS message
- `Provider/PollinationsAI.py` & `PollinationsImage.py`
- Converted `audio_models` from list to dict, adjusted usage checks and labels
- `Provider/hf/__init__.py` – applies `model_aliases` remap before dispatch
- `Provider/hf_space/DeepseekAI_JanusPro7b.py` – now merges media before upload
- `needs_auth/Gemini.py` – dropped obsolete Gemini model entries
- `needs_auth/GigaChat.py` – added lowercase `"gigachat"` alias
- **API & client updates**
- Replaced `ProviderUtils` with new `Provider` map usage throughout API and GUI server
- Integrated `AnyProvider` as default fallback in `g4f/client` sync & async flows
- API endpoints now return counts of providers per model and filter by `x_ignored` header
- **GUI improvements**
- Updated JS labels with emoji icons, provider ignore logic, model count display
- **Model registry**
- Renamed base model `"GigaChat:latest"` ➜ `"gigachat"` in `models.py`
- **Miscellaneous**
- Added audio/video flags to GUI provider list
- Tightened error propagation in `retry_provider.raise_exceptions`
* Fix unittests
* fix: handle None conversation when accessing provider-specific data
- Modified `AnyProvider` class in `g4f/providers/any_provider.py`
- Updated logic to check if `conversation` is not None before accessing `provider.__name__` attribute
- Wrapped `getattr(conversation, provider.__name__, None)` block in an additional `if conversation is not None` condition
- Changed `setattr(conversation, provider.__name__, chunk)` to use `chunk.get_dict()` instead of the object directly
- Ensured consistent use of `JsonConversation` when modifying or assigning `conversation` data
* ```
feat: add provider string conversion & update IterListProvider call
- In g4f/client/__init__.py, within both Completions and AsyncCompletions, added a check to convert the provider from a string using convert_to_provider(provider) when applicable.
- In g4f/providers/any_provider.py, removed the second argument (False) from the IterListProvider constructor call in the async for loop.
```
---------
Co-authored-by: hlohaus <983577+hlohaus@users.noreply.github.com>
71 lines
2.1 KiB
Python
71 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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parent = PollinationsAI.__name__
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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 = {}
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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 = 1,
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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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