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* refactor(g4f/Provider/Airforce.py): improve model handling and filtering - Add hidden_models set to exclude specific models - Add evil alias for uncensored model handling - Extend filtering for model-specific response tokens - Add response buffering for streamed content - Update model fetching with error handling * refactor(g4f/Provider/Blackbox.py): improve caching and model handling - Add caching system for validated values with file-based storage - Rename 'flux' model to 'ImageGeneration' and update references - Add temperature, top_p and max_tokens parameters to generator - Simplify HTTP headers and remove redundant options - Add model alias mapping for ImageGeneration - Add file system utilities for cache management * feat(g4f/Provider/RobocodersAPI.py): add caching and error handling - Add file-based caching system for access tokens and sessions - Add robust error handling with specific error messages - Add automatic dialog continuation on resource limits - Add HTML parsing with BeautifulSoup for token extraction - Add debug logging for error tracking - Add timeout configuration for API requests * refactor(g4f/Provider/DarkAI.py): update DarkAI default model and aliases - Change default model from llama-3-405b to llama-3-70b - Remove llama-3-405b from supported models list - Remove llama-3.1-405b from model aliases * feat(g4f/Provider/Blackbox2.py): add image generation support - Add image model 'flux' with dedicated API endpoint - Refactor generator to support both text and image outputs - Extract headers into reusable static method - Add type hints for AsyncGenerator return type - Split generation logic into _generate_text and _generate_image methods - Add ImageResponse handling for image generation results BREAKING CHANGE: create_async_generator now returns AsyncGenerator instead of AsyncResult * refactor(g4f/Provider/ChatGptEs.py): update ChatGptEs model configuration - Update models list to include gpt-3.5-turbo - Remove chatgpt-4o-latest from supported models - Remove model_aliases mapping for gpt-4o * feat(g4f/Provider/DeepInfraChat.py): add Accept-Language header support - Add Accept-Language header for internationalization - Maintain existing header configuration - Improve request compatibility with language preferences * refactor(g4f/Provider/needs_auth/Gemini.py): add ProviderModelMixin inheritance - Add ProviderModelMixin to class inheritance - Import ProviderModelMixin from base_provider - Move BaseConversation import to base_provider imports * refactor(g4f/Provider/Liaobots.py): update model details and aliases - Add version suffix to o1 model IDs - Update model aliases for o1-preview and o1-mini - Standardize version format across model definitions * refactor(g4f/Provider/PollinationsAI.py): enhance model support and generation - Split generation logic into dedicated image/text methods - Add additional text models including sur and claude - Add width/height parameters for image generation - Add model existence validation - Add hasattr checks for model lists initialization * chore(gitignore): add provider cache directory - Add g4f/Provider/.cache to gitignore patterns * refactor(g4f/Provider/ReplicateHome.py): update model configuration - Update default model to gemma-2b-it - Add default_image_model configuration - Remove llava-13b from supported models - Simplify request headers * feat(g4f/models.py): expand provider and model support - Add new providers DarkAI and PollinationsAI - Add new models for Mistral, Flux and image generation - Update provider lists for existing models - Add P1 and Evil models with experimental providers BREAKING CHANGE: Remove llava-13b model support * refactor(Airforce): Update type hint for split_message return - Change return type of from to for consistency with import. - Maintain overall functionality and structure of the class. - Ensure compatibility with type hinting standards in Python. * refactor(g4f/Provider/Airforce.py): Update type hint for split_message return - Change return type of 'split_message' from 'list[str]' to 'List[str]' for consistency with import. - Maintain overall functionality and structure of the 'Airforce' class. - Ensure compatibility with type hinting standards in Python. * feat(g4f/Provider/RobocodersAPI.py): Add support for optional BeautifulSoup dependency - Introduce a check for the BeautifulSoup library and handle its absence gracefully. - Raise a if BeautifulSoup is not installed, prompting the user to install it. - Remove direct import of BeautifulSoup to avoid import errors when the library is missing. * fix: Updating provider documentation and small fixes in providers * Disabled the provider (RobocodersAPI) * Fix: Conflicting file g4f/models.py * Update g4f/models.py g4f/Provider/Airforce.py * Update docs/providers-and-models.md g4f/models.py g4f/Provider/Airforce.py g4f/Provider/PollinationsAI.py * Update docs/providers-and-models.md * Update .gitignore * Update g4f/models.py * Update g4f/Provider/PollinationsAI.py --------- Co-authored-by: kqlio67 <>
60 lines
2.8 KiB
Python
60 lines
2.8 KiB
Python
from __future__ import annotations
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import json
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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, ImagePreview
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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class Flux(AsyncGeneratorProvider, ProviderModelMixin):
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label = "HuggingSpace (black-forest-labs-flux-1-dev)"
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url = "https://black-forest-labs-flux-1-dev.hf.space"
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api_endpoint = "/gradio_api/call/infer"
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working = True
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default_model = 'flux-dev'
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models = [default_model]
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image_models = [default_model]
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model_aliases = {"flux-dev": "flux-1-dev"}
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@classmethod
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async def create_async_generator(
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cls, model: str, messages: Messages, prompt: str = None, api_key: str = None, proxy: str = None, **kwargs
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) -> AsyncResult:
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headers = {
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"Content-Type": "application/json",
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"Accept": "application/json",
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}
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if api_key is not None:
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headers["Authorization"] = f"Bearer {api_key}"
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async with ClientSession(headers=headers) as session:
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prompt = messages[-1]["content"] if prompt is None else prompt
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data = {
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"data": [prompt, 0, True, 1024, 1024, 3.5, 28]
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}
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async with session.post(f"{cls.url}{cls.api_endpoint}", json=data, proxy=proxy) as response:
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response.raise_for_status()
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event_id = (await response.json()).get("event_id")
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async with session.get(f"{cls.url}{cls.api_endpoint}/{event_id}") as event_response:
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event_response.raise_for_status()
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event = None
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async for chunk in event_response.content:
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if chunk.startswith(b"event: "):
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event = chunk[7:].decode(errors="replace").strip()
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if chunk.startswith(b"data: "):
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if event == "error":
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raise RuntimeError(f"GPU token limit exceeded: {chunk.decode(errors='replace')}")
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if event in ("complete", "generating"):
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try:
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data = json.loads(chunk[6:])
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if data is None:
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continue
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url = data[0]["url"]
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except (json.JSONDecodeError, KeyError, TypeError) as e:
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raise RuntimeError(f"Failed to parse image URL: {chunk.decode(errors='replace')}", e)
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if event == "generating":
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yield ImagePreview(url, prompt)
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else:
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yield ImageResponse(url, prompt)
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break
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