gpt4free/g4f/Provider/Flux.py
kqlio67 bb9132bcb4
Updating provider documentation and small fixes in providers (#2469)
* 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 <>
2024-12-09 16:52:25 +01:00

60 lines
2.8 KiB
Python

from __future__ import annotations
import json
from aiohttp import ClientSession
from ..typing import AsyncResult, Messages
from ..image import ImageResponse, ImagePreview
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
class Flux(AsyncGeneratorProvider, ProviderModelMixin):
label = "HuggingSpace (black-forest-labs-flux-1-dev)"
url = "https://black-forest-labs-flux-1-dev.hf.space"
api_endpoint = "/gradio_api/call/infer"
working = True
default_model = 'flux-dev'
models = [default_model]
image_models = [default_model]
model_aliases = {"flux-dev": "flux-1-dev"}
@classmethod
async def create_async_generator(
cls, model: str, messages: Messages, prompt: str = None, api_key: str = None, proxy: str = None, **kwargs
) -> AsyncResult:
headers = {
"Content-Type": "application/json",
"Accept": "application/json",
}
if api_key is not None:
headers["Authorization"] = f"Bearer {api_key}"
async with ClientSession(headers=headers) as session:
prompt = messages[-1]["content"] if prompt is None else prompt
data = {
"data": [prompt, 0, True, 1024, 1024, 3.5, 28]
}
async with session.post(f"{cls.url}{cls.api_endpoint}", json=data, proxy=proxy) as response:
response.raise_for_status()
event_id = (await response.json()).get("event_id")
async with session.get(f"{cls.url}{cls.api_endpoint}/{event_id}") as event_response:
event_response.raise_for_status()
event = None
async for chunk in event_response.content:
if chunk.startswith(b"event: "):
event = chunk[7:].decode(errors="replace").strip()
if chunk.startswith(b"data: "):
if event == "error":
raise RuntimeError(f"GPU token limit exceeded: {chunk.decode(errors='replace')}")
if event in ("complete", "generating"):
try:
data = json.loads(chunk[6:])
if data is None:
continue
url = data[0]["url"]
except (json.JSONDecodeError, KeyError, TypeError) as e:
raise RuntimeError(f"Failed to parse image URL: {chunk.decode(errors='replace')}", e)
if event == "generating":
yield ImagePreview(url, prompt)
else:
yield ImageResponse(url, prompt)
break