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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>
76 lines
No EOL
2.9 KiB
Python
76 lines
No EOL
2.9 KiB
Python
from __future__ import annotations
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import random
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from ...typing import AsyncResult, Messages
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from ...providers.response import ImageResponse
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from ...errors import ModelNotSupportedError, MissingAuthError
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from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from .HuggingChat import HuggingChat
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from .HuggingFaceAPI import HuggingFaceAPI
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from .HuggingFaceInference import HuggingFaceInference
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from .HuggingFaceMedia import HuggingFaceMedia
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from .models import model_aliases, vision_models, default_vision_model
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from ... import debug
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class HuggingFace(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://huggingface.co"
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login_url = "https://huggingface.co/settings/tokens"
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working = True
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supports_message_history = True
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@classmethod
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def get_models(cls, **kwargs) -> list[str]:
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if not cls.models:
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cls.models = HuggingFaceInference.get_models()
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cls.image_models = HuggingFaceInference.image_models
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return cls.models
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model_aliases = model_aliases
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vision_models = vision_models
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default_vision_model = default_vision_model
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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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**kwargs
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) -> AsyncResult:
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if model in cls.model_aliases:
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model = cls.model_aliases[model]
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if "tools" not in kwargs and "media" not in kwargs and random.random() >= 0.5:
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try:
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is_started = False
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async for chunk in HuggingFaceInference.create_async_generator(model, messages, **kwargs):
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if isinstance(chunk, (str, ImageResponse)):
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is_started = True
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yield chunk
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if is_started:
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return
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except Exception as e:
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if is_started:
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raise e
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debug.error(f"{cls.__name__} {type(e).__name__}; {e}")
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if not cls.image_models:
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cls.get_models()
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try:
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async for chunk in HuggingFaceMedia.create_async_generator(model, messages, **kwargs):
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yield chunk
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return
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except ModelNotSupportedError:
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pass
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if model in cls.image_models:
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if "api_key" not in kwargs:
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async for chunk in HuggingChat.create_async_generator(model, messages, **kwargs):
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yield chunk
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else:
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async for chunk in HuggingFaceInference.create_async_generator(model, messages, **kwargs):
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yield chunk
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return
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try:
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async for chunk in HuggingFaceAPI.create_async_generator(model, messages, **kwargs):
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yield chunk
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except (ModelNotSupportedError, MissingAuthError):
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async for chunk in HuggingFaceInference.create_async_generator(model, messages, **kwargs):
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yield chunk |