mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-12-22 18:41:41 +03:00
Major Provider Updates and Model Support Enhancements (#2467)
* 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. --------- Co-authored-by: kqlio67 <>
This commit is contained in:
kqlio67
GitHub
parent
5969983d83
commit
a358b28f47
3
.gitignore
vendored
3
.gitignore
vendored
@ -65,4 +65,5 @@ x.txt
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bench.py
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to-reverse.txt
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g4f/Provider/OpenaiChat2.py
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generated_images/
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generated_images/
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g4f/Provider/.cache
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@ -1,18 +1,19 @@
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from __future__ import annotations
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import json
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import random
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import re
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import requests
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from requests.packages.urllib3.exceptions import InsecureRequestWarning
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from aiohttp import ClientSession
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from typing import List
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from requests.packages.urllib3.exceptions import InsecureRequestWarning
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from ..typing import AsyncResult, Messages
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from ..image import ImageResponse
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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requests.packages.urllib3.disable_warnings(InsecureRequestWarning)
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from .. import debug
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def split_message(message: str, max_length: int = 1000) -> list[str]:
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requests.packages.urllib3.disable_warnings(InsecureRequestWarning)
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def split_message(message: str, max_length: int = 1000) -> List[str]:
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"""Splits the message into parts up to (max_length)."""
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chunks = []
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while len(message) > max_length:
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@ -38,6 +39,8 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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default_model = "gpt-4o-mini"
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default_image_model = "flux"
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hidden_models = {"Flux-1.1-Pro"}
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additional_models_imagine = ["flux-1.1-pro", "dall-e-3"]
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@ -54,39 +57,38 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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"llama-3.1-70b": "llama-3.1-70b-turbo",
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"neural-7b": "neural-chat-7b-v3-1",
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"zephyr-7b": "zephyr-7b-beta",
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"evil": "any-uncensored",
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"sdxl": "stable-diffusion-xl-base",
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"flux-pro": "flux-1.1-pro",
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}
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@classmethod
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def fetch_completions_models(cls):
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response = requests.get('https://api.airforce/models', verify=False)
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response.raise_for_status()
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data = response.json()
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return [model['id'] for model in data['data']]
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@classmethod
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def fetch_imagine_models(cls):
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response = requests.get(
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'https://api.airforce/v1/imagine2/models',
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verify=False
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)
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response.raise_for_status()
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return response.json()
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@classmethod
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def is_image_model(cls, model: str) -> bool:
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return model in cls.image_models
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@classmethod
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def get_models(cls):
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if not cls.models:
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cls.image_models = cls.fetch_imagine_models() + cls.additional_models_imagine
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cls.models = list(dict.fromkeys([cls.default_model] +
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cls.fetch_completions_models() +
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cls.image_models))
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return cls.models
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if not cls.image_models:
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try:
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url = "https://api.airforce/imagine2/models"
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response = requests.get(url, verify=False)
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response.raise_for_status()
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cls.image_models = response.json()
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cls.image_models.extend(cls.additional_models_imagine)
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except Exception as e:
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debug.log(f"Error fetching image models: {e}")
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if not cls.models:
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try:
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url = "https://api.airforce/models"
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response = requests.get(url, verify=False)
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response.raise_for_status()
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data = response.json()
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cls.models = [model['id'] for model in data['data']]
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cls.models.extend(cls.image_models)
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cls.models = [model for model in cls.models if model not in cls.hidden_models]
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except Exception as e:
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debug.log(f"Error fetching text models: {e}")
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cls.models = [cls.default_model]
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return cls.models
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@classmethod
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async def check_api_key(cls, api_key: str) -> bool:
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"""
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@ -111,6 +113,37 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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print(f"Error checking API key: {str(e)}")
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return False
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@classmethod
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def _filter_content(cls, part_response: str) -> str:
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"""
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Filters out unwanted content from the partial response.
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"""
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part_response = re.sub(
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r"One message exceeds the \d+chars per message limit\..+https:\/\/discord\.com\/invite\/\S+",
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'',
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part_response
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)
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part_response = re.sub(
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r"Rate limit \(\d+\/minute\) exceeded\. Join our discord for more: .+https:\/\/discord\.com\/invite\/\S+",
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'',
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part_response
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)
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return part_response
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@classmethod
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def _filter_response(cls, response: str) -> str:
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"""
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Filters the full response to remove system errors and other unwanted text.
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"""
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filtered_response = re.sub(r"\[ERROR\] '\w{8}-\w{4}-\w{4}-\w{4}-\w{12}'", '', response) # any-uncensored
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filtered_response = re.sub(r'<\|im_end\|>', '', filtered_response) # remove <|im_end|> token
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filtered_response = re.sub(r'</s>', '', filtered_response) # neural-chat-7b-v3-1
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filtered_response = re.sub(r'^(Assistant: |AI: |ANSWER: |Output: )', '', filtered_response) # phi-2
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filtered_response = cls._filter_content(filtered_response)
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return filtered_response
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@classmethod
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async def generate_image(
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cls,
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@ -124,6 +157,7 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:133.0) Gecko/20100101 Firefox/133.0",
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"Accept": "image/avif,image/webp,image/png,image/svg+xml,image/*;q=0.8,*/*;q=0.5",
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"Accept-Language": "en-US,en;q=0.5",
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"Accept-Encoding": "gzip, deflate, br, zstd",
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"Content-Type": "application/json",
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"Authorization": f"Bearer {api_key}",
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@ -151,9 +185,13 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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api_key: str,
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proxy: str = None
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) -> AsyncResult:
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"""
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Generates text, buffers the response, filters it, and returns the final result.
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"""
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:133.0) Gecko/20100101 Firefox/133.0",
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"Accept": "application/json, text/event-stream",
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"Accept-Language": "en-US,en;q=0.5",
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"Accept-Encoding": "gzip, deflate, br, zstd",
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"Content-Type": "application/json",
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"Authorization": f"Bearer {api_key}",
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@ -175,6 +213,7 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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response.raise_for_status()
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if stream:
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buffer = [] # Buffer to collect partial responses
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async for line in response.content:
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line = line.decode('utf-8').strip()
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if line.startswith('data: '):
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@ -184,18 +223,20 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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if 'choices' in chunk and chunk['choices']:
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delta = chunk['choices'][0].get('delta', {})
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if 'content' in delta:
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filtered_content = cls._filter_response(delta['content'])
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yield filtered_content
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buffer.append(delta['content'])
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except json.JSONDecodeError:
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continue
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# Combine the buffered response and filter it
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filtered_response = cls._filter_response(''.join(buffer))
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yield filtered_response
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else:
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# Non-streaming response
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result = await response.json()
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if 'choices' in result and result['choices']:
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message = result['choices'][0].get('message', {})
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content = message.get('content', '')
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filtered_content = cls._filter_response(content)
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yield filtered_content
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filtered_response = cls._filter_response(content)
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yield filtered_response
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@classmethod
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async def create_async_generator(
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@ -217,7 +258,7 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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pass
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model = cls.get_model(model)
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if cls.is_image_model(model):
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if model in cls.image_models:
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if prompt is None:
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prompt = messages[-1]['content']
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if seed is None:
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@ -227,27 +268,3 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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else:
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async for result in cls.generate_text(model, messages, max_tokens, temperature, top_p, stream, api_key, proxy):
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yield result
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@classmethod
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def _filter_content(cls, part_response: str) -> str:
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part_response = re.sub(
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r"One message exceeds the \d+chars per message limit\..+https:\/\/discord\.com\/invite\/\S+",
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'',
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part_response
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)
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part_response = re.sub(
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r"Rate limit \(\d+\/minute\) exceeded\. Join our discord for more: .+https:\/\/discord\.com\/invite\/\S+",
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'',
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part_response
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)
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return part_response
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@classmethod
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def _filter_response(cls, response: str) -> str:
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filtered_response = re.sub(r"\[ERROR\] '\w{8}-\w{4}-\w{4}-\w{4}-\w{12}'", '', response) # any-uncensored
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filtered_response = re.sub(r'<\|im_end\|>', '', response) # hermes-2-pro-mistral-7b
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filtered_response = re.sub(r'</s>', '', response) # neural-chat-7b-v3-1
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filtered_response = cls._filter_content(filtered_response)
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return filtered_response
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@ -7,6 +7,10 @@ import json
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import re
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import aiohttp
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import os
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import json
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from pathlib import Path
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from ..typing import AsyncResult, Messages, ImageType
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from ..image import ImageResponse, to_data_uri
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@ -17,22 +21,22 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
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label = "Blackbox AI"
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url = "https://www.blackbox.ai"
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api_endpoint = "https://www.blackbox.ai/api/chat"
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working = True
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supports_stream = True
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supports_system_message = True
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supports_message_history = True
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_last_validated_value = None
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default_model = 'blackboxai'
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default_vision_model = default_model
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default_image_model = 'flux'
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image_models = ['flux', 'repomap']
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image_models = ['ImageGeneration', 'repomap']
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vision_models = [default_model, 'gpt-4o', 'gemini-pro', 'gemini-1.5-flash', 'llama-3.1-8b', 'llama-3.1-70b', 'llama-3.1-405b']
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userSelectedModel = ['gpt-4o', 'gemini-pro', 'claude-sonnet-3.5', 'blackboxai-pro']
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agentMode = {
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'flux': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"}
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'ImageGeneration': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"}
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}
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trendingAgentMode = {
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@ -95,22 +99,63 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
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models = list(dict.fromkeys([default_model, *userSelectedModel, *list(agentMode.keys()), *list(trendingAgentMode.keys())]))
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model_aliases = {
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"gpt-4": "blackboxai",
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"gpt-4": "gpt-4o",
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"gpt-4o-mini": "gpt-4o",
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"gpt-3.5-turbo": "blackboxai",
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"gemini-flash": "gemini-1.5-flash",
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"claude-3.5-sonnet": "claude-sonnet-3.5"
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"claude-3.5-sonnet": "claude-sonnet-3.5",
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"flux": "ImageGeneration",
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}
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@classmethod
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async def fetch_validated(cls):
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if cls._last_validated_value:
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return cls._last_validated_value
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def _get_cache_dir(cls) -> Path:
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# Get the path to the current file
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current_file = Path(__file__)
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# Create the path to the .cache directory
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cache_dir = current_file.parent / '.cache'
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# Create a directory if it does not exist
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cache_dir.mkdir(exist_ok=True)
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return cache_dir
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@classmethod
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def _get_cache_file(cls) -> Path:
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return cls._get_cache_dir() / 'blackbox.json'
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@classmethod
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def _load_cached_value(cls) -> str | None:
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cache_file = cls._get_cache_file()
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if cache_file.exists():
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try:
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with open(cache_file, 'r') as f:
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data = json.load(f)
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return data.get('validated_value')
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except Exception as e:
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print(f"Error reading cache file: {e}")
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return None
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@classmethod
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def _save_cached_value(cls, value: str):
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cache_file = cls._get_cache_file()
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try:
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with open(cache_file, 'w') as f:
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json.dump({'validated_value': value}, f)
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except Exception as e:
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print(f"Error writing to cache file: {e}")
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@classmethod
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async def fetch_validated(cls):
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# Let's try to load the value from the cache first
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cached_value = cls._load_cached_value()
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if cached_value:
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return cached_value
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async with aiohttp.ClientSession() as session:
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try:
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async with session.get(cls.url) as response:
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if response.status != 200:
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print("Failed to load the page.")
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return cls._last_validated_value
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return cached_value
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page_content = await response.text()
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js_files = re.findall(r'static/chunks/\d{4}-[a-fA-F0-9]+\.js', page_content)
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@ -125,12 +170,13 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
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match = key_pattern.search(js_content)
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if match:
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validated_value = match.group(1)
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cls._last_validated_value = validated_value
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# Save the new value to the cache file
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cls._save_cached_value(validated_value)
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return validated_value
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except Exception as e:
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print(f"Error fetching validated value: {e}")
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return cls._last_validated_value
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return cached_value
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@staticmethod
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def generate_id(length=7):
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@ -162,12 +208,16 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
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web_search: bool = False,
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image: ImageType = None,
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image_name: str = None,
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top_p: float = 0.9,
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temperature: float = 0.5,
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max_tokens: int = 1024,
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**kwargs
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) -> AsyncResult:
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message_id = cls.generate_id()
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messages = cls.add_prefix_to_messages(messages, model)
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validated_value = await cls.fetch_validated()
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formatted_message = format_prompt(messages)
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model = cls.get_model(model)
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messages = [{"id": message_id, "content": formatted_message, "role": "user"}]
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|
||||
@ -185,20 +235,10 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
|
||||
headers = {
|
||||
'accept': '*/*',
|
||||
'accept-language': 'en-US,en;q=0.9',
|
||||
'cache-control': 'no-cache',
|
||||
'content-type': 'application/json',
|
||||
'origin': cls.url,
|
||||
'pragma': 'no-cache',
|
||||
'priority': 'u=1, i',
|
||||
'referer': f'{cls.url}/',
|
||||
'sec-ch-ua': '"Not?A_Brand";v="99", "Chromium";v="130"',
|
||||
'sec-ch-ua-mobile': '?0',
|
||||
'sec-ch-ua-platform': '"Linux"',
|
||||
'sec-fetch-dest': 'empty',
|
||||
'sec-fetch-mode': 'cors',
|
||||
'sec-fetch-site': 'same-origin',
|
||||
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36'
|
||||
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36'
|
||||
}
|
||||
|
||||
data = {
|
||||
@ -211,9 +251,9 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
"trendingAgentMode": cls.trendingAgentMode.get(model, {}) if model in cls.trendingAgentMode else {},
|
||||
"isMicMode": False,
|
||||
"userSystemPrompt": None,
|
||||
"maxTokens": 1024,
|
||||
"playgroundTopP": 0.9,
|
||||
"playgroundTemperature": 0.5,
|
||||
"maxTokens": max_tokens,
|
||||
"playgroundTopP": top_p,
|
||||
"playgroundTemperature": temperature,
|
||||
"isChromeExt": False,
|
||||
"githubToken": None,
|
||||
"clickedAnswer2": False,
|
||||
@ -225,7 +265,7 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
"webSearchMode": web_search,
|
||||
"validated": validated_value,
|
||||
"imageGenerationMode": False,
|
||||
"webSearchModePrompt": False
|
||||
"webSearchModePrompt": web_search
|
||||
}
|
||||
|
||||
async with ClientSession(headers=headers) as session:
|
||||
|
||||
@ -3,20 +3,30 @@ from __future__ import annotations
|
||||
import random
|
||||
import asyncio
|
||||
from aiohttp import ClientSession
|
||||
from typing import Union, AsyncGenerator
|
||||
|
||||
from ..typing import AsyncResult, Messages
|
||||
from ..image import ImageResponse
|
||||
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
|
||||
|
||||
from .. import debug
|
||||
|
||||
class Blackbox2(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
url = "https://www.blackbox.ai"
|
||||
api_endpoint = "https://www.blackbox.ai/api/improve-prompt"
|
||||
api_endpoints = {
|
||||
"llama-3.1-70b": "https://www.blackbox.ai/api/improve-prompt",
|
||||
"flux": "https://www.blackbox.ai/api/image-generator"
|
||||
}
|
||||
|
||||
working = True
|
||||
supports_system_message = True
|
||||
supports_message_history = True
|
||||
supports_stream = False
|
||||
|
||||
default_model = 'llama-3.1-70b'
|
||||
models = [default_model]
|
||||
chat_models = ['llama-3.1-70b']
|
||||
image_models = ['flux']
|
||||
models = [*chat_models, *image_models]
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
@ -27,23 +37,27 @@ class Blackbox2(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
max_retries: int = 3,
|
||||
delay: int = 1,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
headers = {
|
||||
'accept': '*/*',
|
||||
'accept-language': 'en-US,en;q=0.9',
|
||||
'content-type': 'text/plain;charset=UTF-8',
|
||||
'dnt': '1',
|
||||
'origin': 'https://www.blackbox.ai',
|
||||
'priority': 'u=1, i',
|
||||
'referer': 'https://www.blackbox.ai',
|
||||
'sec-ch-ua': '"Chromium";v="131", "Not_A Brand";v="24"',
|
||||
'sec-ch-ua-mobile': '?0',
|
||||
'sec-ch-ua-platform': '"Linux"',
|
||||
'sec-fetch-dest': 'empty',
|
||||
'sec-fetch-mode': 'cors',
|
||||
'sec-fetch-site': 'same-origin',
|
||||
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36'
|
||||
}
|
||||
) -> AsyncGenerator:
|
||||
if model in cls.chat_models:
|
||||
async for result in cls._generate_text(model, messages, proxy, max_retries, delay):
|
||||
yield result
|
||||
elif model in cls.image_models:
|
||||
async for result in cls._generate_image(model, messages, proxy):
|
||||
yield result
|
||||
else:
|
||||
raise ValueError(f"Unsupported model: {model}")
|
||||
|
||||
@classmethod
|
||||
async def _generate_text(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
proxy: str = None,
|
||||
max_retries: int = 3,
|
||||
delay: int = 1
|
||||
) -> AsyncGenerator:
|
||||
headers = cls._get_headers()
|
||||
api_endpoint = cls.api_endpoints[model]
|
||||
|
||||
data = {
|
||||
"messages": messages,
|
||||
@ -53,7 +67,7 @@ class Blackbox2(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
async with ClientSession(headers=headers) as session:
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
|
||||
async with session.post(api_endpoint, json=data, proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
response_data = await response.json()
|
||||
if 'prompt' in response_data:
|
||||
@ -68,3 +82,39 @@ class Blackbox2(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
wait_time = delay * (2 ** attempt) + random.uniform(0, 1)
|
||||
debug.log(f"Attempt {attempt + 1} failed. Retrying in {wait_time:.2f} seconds...")
|
||||
await asyncio.sleep(wait_time)
|
||||
|
||||
@classmethod
|
||||
async def _generate_image(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
proxy: str = None
|
||||
) -> AsyncGenerator:
|
||||
headers = cls._get_headers()
|
||||
api_endpoint = cls.api_endpoints[model]
|
||||
|
||||
async with ClientSession(headers=headers) as session:
|
||||
prompt = messages[-1]["content"]
|
||||
data = {
|
||||
"query": prompt
|
||||
}
|
||||
|
||||
async with session.post(api_endpoint, headers=headers, json=data, proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
response_data = await response.json()
|
||||
|
||||
if 'markdown' in response_data:
|
||||
image_url = response_data['markdown'].split('(')[1].split(')')[0]
|
||||
yield ImageResponse(images=image_url, alt=prompt)
|
||||
|
||||
@staticmethod
|
||||
def _get_headers() -> dict:
|
||||
return {
|
||||
'accept': '*/*',
|
||||
'accept-language': 'en-US,en;q=0.9',
|
||||
'content-type': 'text/plain;charset=UTF-8',
|
||||
'origin': 'https://www.blackbox.ai',
|
||||
'priority': 'u=1, i',
|
||||
'referer': 'https://www.blackbox.ai',
|
||||
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36'
|
||||
}
|
||||
|
||||
@ -12,17 +12,14 @@ from .helper import format_prompt
|
||||
class ChatGptEs(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
url = "https://chatgpt.es"
|
||||
api_endpoint = "https://chatgpt.es/wp-admin/admin-ajax.php"
|
||||
|
||||
working = True
|
||||
supports_stream = True
|
||||
supports_system_message = True
|
||||
supports_message_history = True
|
||||
|
||||
default_model = 'gpt-4o'
|
||||
models = ['gpt-4o', 'gpt-4o-mini', 'chatgpt-4o-latest']
|
||||
|
||||
model_aliases = {
|
||||
"gpt-4o": "chatgpt-4o-latest",
|
||||
}
|
||||
models = ['gpt-3.5-turbo', 'gpt-4o', 'gpt-4o-mini']
|
||||
|
||||
@classmethod
|
||||
def get_model(cls, model: str) -> str:
|
||||
|
||||
@ -16,17 +16,15 @@ class DarkAI(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
supports_system_message = True
|
||||
supports_message_history = True
|
||||
|
||||
default_model = 'llama-3-405b'
|
||||
default_model = 'llama-3-70b'
|
||||
models = [
|
||||
'gpt-4o', # Uncensored
|
||||
'gpt-3.5-turbo', # Uncensored
|
||||
'llama-3-70b', # Uncensored
|
||||
default_model,
|
||||
]
|
||||
|
||||
model_aliases = {
|
||||
"llama-3.1-70b": "llama-3-70b",
|
||||
"llama-3.1-405b": "llama-3-405b",
|
||||
}
|
||||
|
||||
@classmethod
|
||||
|
||||
@ -43,6 +43,7 @@ class DeepInfraChat(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
headers = {
|
||||
'Accept-Language': 'en-US,en;q=0.9',
|
||||
'Content-Type': 'application/json',
|
||||
'Origin': 'https://deepinfra.com',
|
||||
'Referer': 'https://deepinfra.com/',
|
||||
|
||||
@ -36,8 +36,8 @@ models = {
|
||||
"tokenLimit": 126000,
|
||||
"context": "128K",
|
||||
},
|
||||
"o1-preview": {
|
||||
"id": "o1-preview",
|
||||
"o1-preview-2024-09-12": {
|
||||
"id": "o1-preview-2024-09-12",
|
||||
"name": "o1-preview",
|
||||
"model": "o1",
|
||||
"provider": "OpenAI",
|
||||
@ -45,8 +45,8 @@ models = {
|
||||
"tokenLimit": 100000,
|
||||
"context": "128K",
|
||||
},
|
||||
"o1-mini": {
|
||||
"id": "o1-mini",
|
||||
"o1-mini-2024-09-12": {
|
||||
"id": "o1-mini-2024-09-12",
|
||||
"name": "o1-mini",
|
||||
"model": "o1",
|
||||
"provider": "OpenAI",
|
||||
@ -152,6 +152,9 @@ class Liaobots(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
"gpt-4o-mini": "gpt-4o-mini-2024-07-18",
|
||||
"gpt-4": "gpt-4o-2024-08-06",
|
||||
|
||||
"o1-preview": "o1-preview-2024-09-12",
|
||||
"o1-mini": "o1-mini-2024-09-12",
|
||||
|
||||
"claude-3-opus": "claude-3-opus-20240229",
|
||||
"claude-3.5-sonnet": "claude-3-5-sonnet-20240620",
|
||||
"claude-3.5-sonnet": "claude-3-5-sonnet-20241022",
|
||||
|
||||
107
g4f/Provider/PollinationsAI.py
Normal file
107
g4f/Provider/PollinationsAI.py
Normal file
@ -0,0 +1,107 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from urllib.parse import quote
|
||||
import random
|
||||
import requests
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import AsyncResult, Messages
|
||||
from ..image import ImageResponse
|
||||
from ..requests.raise_for_status import raise_for_status
|
||||
from ..requests.aiohttp import get_connector
|
||||
from .needs_auth.OpenaiAPI import OpenaiAPI
|
||||
from .helper import format_prompt
|
||||
|
||||
class PollinationsAI(OpenaiAPI):
|
||||
label = "Pollinations.AI"
|
||||
url = "https://pollinations.ai"
|
||||
|
||||
working = True
|
||||
needs_auth = False
|
||||
supports_stream = True
|
||||
|
||||
default_model = "openai"
|
||||
|
||||
additional_models_image = ["unity", "midijourney", "rtist"]
|
||||
additional_models_text = ["sur", "sur-mistral", "claude"]
|
||||
|
||||
model_aliases = {
|
||||
"gpt-4o": "openai",
|
||||
"mistral-nemo": "mistral",
|
||||
"llama-3.1-70b": "llama", #
|
||||
"gpt-3.5-turbo": "searchgpt",
|
||||
"gpt-4": "searchgpt",
|
||||
"gpt-3.5-turbo": "claude",
|
||||
"gpt-4": "claude",
|
||||
"qwen-2.5-coder-32b": "qwen-coder",
|
||||
"claude-3.5-sonnet": "sur",
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def get_models(cls):
|
||||
if not hasattr(cls, 'image_models'):
|
||||
cls.image_models = []
|
||||
if not cls.image_models:
|
||||
url = "https://image.pollinations.ai/models"
|
||||
response = requests.get(url)
|
||||
raise_for_status(response)
|
||||
cls.image_models = response.json()
|
||||
cls.image_models.extend(cls.additional_models_image)
|
||||
if not hasattr(cls, 'models'):
|
||||
cls.models = []
|
||||
if not cls.models:
|
||||
url = "https://text.pollinations.ai/models"
|
||||
response = requests.get(url)
|
||||
raise_for_status(response)
|
||||
cls.models = [model.get("name") for model in response.json()]
|
||||
cls.models.extend(cls.image_models)
|
||||
cls.models.extend(cls.additional_models_text)
|
||||
return cls.models
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
prompt: str = None,
|
||||
api_base: str = "https://text.pollinations.ai/openai",
|
||||
api_key: str = None,
|
||||
proxy: str = None,
|
||||
seed: str = None,
|
||||
width: int = 1024,
|
||||
height: int = 1024,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
if model in cls.image_models:
|
||||
async for response in cls._generate_image(model, messages, prompt, seed, width, height):
|
||||
yield response
|
||||
elif model in cls.models:
|
||||
async for response in cls._generate_text(model, messages, api_base, api_key, proxy, **kwargs):
|
||||
yield response
|
||||
else:
|
||||
raise ValueError(f"Unknown model: {model}")
|
||||
|
||||
@classmethod
|
||||
async def _generate_image(cls, model: str, messages: Messages, prompt: str = None, seed: str = None, width: int = 1024, height: int = 1024):
|
||||
if prompt is None:
|
||||
prompt = messages[-1]["content"]
|
||||
if seed is None:
|
||||
seed = random.randint(0, 100000)
|
||||
image = f"https://image.pollinations.ai/prompt/{quote(prompt)}?width={width}&height={height}&seed={int(seed)}&nofeed=true&nologo=true&model={quote(model)}"
|
||||
yield ImageResponse(image, prompt)
|
||||
|
||||
@classmethod
|
||||
async def _generate_text(cls, model: str, messages: Messages, api_base: str, api_key: str = None, proxy: str = None, **kwargs):
|
||||
if api_key is None:
|
||||
async with ClientSession(connector=get_connector(proxy=proxy)) as session:
|
||||
prompt = format_prompt(messages)
|
||||
async with session.get(f"https://text.pollinations.ai/{quote(prompt)}?model={quote(model)}") as response:
|
||||
await raise_for_status(response)
|
||||
async for line in response.content.iter_any():
|
||||
yield line.decode(errors="ignore")
|
||||
else:
|
||||
async for chunk in super().create_async_generator(
|
||||
model, messages, api_base=api_base, proxy=proxy, **kwargs
|
||||
):
|
||||
yield chunk
|
||||
@ -19,7 +19,8 @@ class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
supports_system_message = True
|
||||
supports_message_history = True
|
||||
|
||||
default_model = 'yorickvp/llava-13b'
|
||||
default_model = 'google-deepmind/gemma-2b-it'
|
||||
default_image_model = 'stability-ai/stable-diffusion-3'
|
||||
|
||||
image_models = [
|
||||
'stability-ai/stable-diffusion-3',
|
||||
@ -29,7 +30,6 @@ class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
|
||||
text_models = [
|
||||
'google-deepmind/gemma-2b-it',
|
||||
'yorickvp/llava-13b',
|
||||
]
|
||||
|
||||
models = text_models + image_models
|
||||
@ -42,7 +42,6 @@ class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
|
||||
# text_models
|
||||
"gemma-2b": "google-deepmind/gemma-2b-it",
|
||||
"llava-13b": "yorickvp/llava-13b",
|
||||
}
|
||||
|
||||
model_versions = {
|
||||
@ -53,7 +52,6 @@ class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
|
||||
# text_models
|
||||
"google-deepmind/gemma-2b-it": "dff94eaf770e1fc211e425a50b51baa8e4cac6c39ef074681f9e39d778773626",
|
||||
"yorickvp/llava-13b": "80537f9eead1a5bfa72d5ac6ea6414379be41d4d4f6679fd776e9535d1eb58bb",
|
||||
}
|
||||
|
||||
@classmethod
|
||||
@ -70,18 +68,9 @@ class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
headers = {
|
||||
"accept": "*/*",
|
||||
"accept-language": "en-US,en;q=0.9",
|
||||
"cache-control": "no-cache",
|
||||
"content-type": "application/json",
|
||||
"origin": "https://replicate.com",
|
||||
"pragma": "no-cache",
|
||||
"priority": "u=1, i",
|
||||
"referer": "https://replicate.com/",
|
||||
"sec-ch-ua": '"Not;A=Brand";v="24", "Chromium";v="128"',
|
||||
"sec-ch-ua-mobile": "?0",
|
||||
"sec-ch-ua-platform": '"Linux"',
|
||||
"sec-fetch-dest": "empty",
|
||||
"sec-fetch-mode": "cors",
|
||||
"sec-fetch-site": "same-site",
|
||||
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36"
|
||||
}
|
||||
|
||||
|
||||
@ -2,10 +2,24 @@ from __future__ import annotations
|
||||
|
||||
import json
|
||||
import aiohttp
|
||||
from pathlib import Path
|
||||
|
||||
try:
|
||||
from bs4 import BeautifulSoup
|
||||
HAS_BEAUTIFULSOUP = True
|
||||
except ImportError:
|
||||
HAS_BEAUTIFULSOUP = False
|
||||
BeautifulSoup = None
|
||||
|
||||
from aiohttp import ClientTimeout
|
||||
from ..errors import MissingRequirementsError
|
||||
from ..typing import AsyncResult, Messages
|
||||
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
|
||||
from .helper import format_prompt
|
||||
|
||||
from .. import debug
|
||||
|
||||
|
||||
class RobocodersAPI(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
label = "API Robocoders AI"
|
||||
url = "https://api.robocoders.ai/docs"
|
||||
@ -16,6 +30,9 @@ class RobocodersAPI(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
agent = [default_model, "RepoAgent", "FrontEndAgent"]
|
||||
models = [*agent]
|
||||
|
||||
CACHE_DIR = Path(__file__).parent / ".cache"
|
||||
CACHE_FILE = CACHE_DIR / "robocoders.json"
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
@ -24,14 +41,14 @@ class RobocodersAPI(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
proxy: str = None,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
access_token = await cls._get_access_token(session)
|
||||
if not access_token:
|
||||
raise Exception("Failed to get access token")
|
||||
|
||||
session_id = await cls._create_session(session, access_token)
|
||||
if not session_id:
|
||||
raise Exception("Failed to create session")
|
||||
|
||||
timeout = ClientTimeout(total=600)
|
||||
|
||||
async with aiohttp.ClientSession(timeout=timeout) as session:
|
||||
# Load or create access token and session ID
|
||||
access_token, session_id = await cls._get_or_create_access_and_session(session)
|
||||
if not access_token or not session_id:
|
||||
raise Exception("Failed to initialize API interaction")
|
||||
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
@ -45,38 +62,116 @@ class RobocodersAPI(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
"prompt": prompt,
|
||||
"agent": model
|
||||
}
|
||||
|
||||
|
||||
async with session.post(cls.api_endpoint, headers=headers, json=data, proxy=proxy) as response:
|
||||
if response.status != 200:
|
||||
raise Exception(f"Error: {response.status}")
|
||||
if response.status == 401: # Unauthorized, refresh token
|
||||
cls._clear_cached_data()
|
||||
raise Exception("Unauthorized: Invalid token, please retry.")
|
||||
elif response.status == 422:
|
||||
raise Exception("Validation Error: Invalid input.")
|
||||
elif response.status >= 500:
|
||||
raise Exception(f"Server Error: {response.status}")
|
||||
elif response.status != 200:
|
||||
raise Exception(f"Unexpected Error: {response.status}")
|
||||
|
||||
async for line in response.content:
|
||||
if line:
|
||||
try:
|
||||
response_data = json.loads(line)
|
||||
message = response_data.get('message', '')
|
||||
# Decode bytes into a string
|
||||
line_str = line.decode('utf-8')
|
||||
response_data = json.loads(line_str)
|
||||
|
||||
# Get the message from the 'args.content' or 'message' field
|
||||
message = (response_data.get('args', {}).get('content') or
|
||||
response_data.get('message', ''))
|
||||
|
||||
if message:
|
||||
yield message
|
||||
|
||||
# Check for reaching the resource limit
|
||||
if (response_data.get('action') == 'message' and
|
||||
response_data.get('args', {}).get('wait_for_response')):
|
||||
# Automatically continue the dialog
|
||||
continue_data = {
|
||||
"sid": session_id,
|
||||
"prompt": "continue",
|
||||
"agent": model
|
||||
}
|
||||
async with session.post(
|
||||
cls.api_endpoint,
|
||||
headers=headers,
|
||||
json=continue_data,
|
||||
proxy=proxy
|
||||
) as continue_response:
|
||||
if continue_response.status == 200:
|
||||
async for continue_line in continue_response.content:
|
||||
if continue_line:
|
||||
try:
|
||||
continue_line_str = continue_line.decode('utf-8')
|
||||
continue_data = json.loads(continue_line_str)
|
||||
continue_message = (
|
||||
continue_data.get('args', {}).get('content') or
|
||||
continue_data.get('message', '')
|
||||
)
|
||||
if continue_message:
|
||||
yield continue_message
|
||||
except json.JSONDecodeError:
|
||||
debug.log(f"Failed to decode continue JSON: {continue_line}")
|
||||
except Exception as e:
|
||||
debug.log(f"Error processing continue response: {e}")
|
||||
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
debug.log(f"Failed to decode JSON: {line}")
|
||||
except Exception as e:
|
||||
debug.log(f"Error processing response: {e}")
|
||||
|
||||
@staticmethod
|
||||
async def _get_access_token(session: aiohttp.ClientSession) -> str:
|
||||
async def _get_or_create_access_and_session(session: aiohttp.ClientSession):
|
||||
RobocodersAPI.CACHE_DIR.mkdir(exist_ok=True) # Ensure cache directory exists
|
||||
|
||||
# Load data from cache
|
||||
if RobocodersAPI.CACHE_FILE.exists():
|
||||
with open(RobocodersAPI.CACHE_FILE, "r") as f:
|
||||
data = json.load(f)
|
||||
access_token = data.get("access_token")
|
||||
session_id = data.get("sid")
|
||||
|
||||
# Validate loaded data
|
||||
if access_token and session_id:
|
||||
return access_token, session_id
|
||||
|
||||
# If data not valid, create new access token and session ID
|
||||
access_token = await RobocodersAPI._fetch_and_cache_access_token(session)
|
||||
session_id = await RobocodersAPI._create_and_cache_session(session, access_token)
|
||||
return access_token, session_id
|
||||
|
||||
@staticmethod
|
||||
async def _fetch_and_cache_access_token(session: aiohttp.ClientSession) -> str:
|
||||
if not HAS_BEAUTIFULSOUP:
|
||||
raise MissingRequirementsError('Install "beautifulsoup4" package | pip install -U beautifulsoup4')
|
||||
return token
|
||||
|
||||
url_auth = 'https://api.robocoders.ai/auth'
|
||||
headers_auth = {
|
||||
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
|
||||
'accept-language': 'en-US,en;q=0.9',
|
||||
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36',
|
||||
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36',
|
||||
}
|
||||
|
||||
async with session.get(url_auth, headers=headers_auth) as response:
|
||||
if response.status == 200:
|
||||
text = await response.text()
|
||||
return text.split('id="token">')[1].split('</pre>')[0].strip()
|
||||
html = await response.text()
|
||||
soup = BeautifulSoup(html, 'html.parser')
|
||||
token_element = soup.find('pre', id='token')
|
||||
if token_element:
|
||||
token = token_element.text.strip()
|
||||
|
||||
# Cache the token
|
||||
RobocodersAPI._save_cached_data({"access_token": token})
|
||||
return token
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
async def _create_session(session: aiohttp.ClientSession, access_token: str) -> str:
|
||||
async def _create_and_cache_session(session: aiohttp.ClientSession, access_token: str) -> str:
|
||||
url_create_session = 'https://api.robocoders.ai/create-session'
|
||||
headers_create_session = {
|
||||
'Authorization': f'Bearer {access_token}'
|
||||
@ -85,6 +180,58 @@ class RobocodersAPI(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
async with session.get(url_create_session, headers=headers_create_session) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
return data.get('sid')
|
||||
session_id = data.get('sid')
|
||||
|
||||
# Cache session ID
|
||||
RobocodersAPI._update_cached_data({"sid": session_id})
|
||||
return session_id
|
||||
elif response.status == 401:
|
||||
RobocodersAPI._clear_cached_data()
|
||||
raise Exception("Unauthorized: Invalid token during session creation.")
|
||||
elif response.status == 422:
|
||||
raise Exception("Validation Error: Check input parameters.")
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def _save_cached_data(new_data: dict):
|
||||
"""Save new data to cache file"""
|
||||
RobocodersAPI.CACHE_DIR.mkdir(exist_ok=True)
|
||||
RobocodersAPI.CACHE_FILE.touch(exist_ok=True)
|
||||
with open(RobocodersAPI.CACHE_FILE, "w") as f:
|
||||
json.dump(new_data, f)
|
||||
|
||||
@staticmethod
|
||||
def _update_cached_data(updated_data: dict):
|
||||
"""Update existing cache data with new values"""
|
||||
data = {}
|
||||
if RobocodersAPI.CACHE_FILE.exists():
|
||||
with open(RobocodersAPI.CACHE_FILE, "r") as f:
|
||||
try:
|
||||
data = json.load(f)
|
||||
except json.JSONDecodeError:
|
||||
# If cache file is corrupted, start with empty dict
|
||||
data = {}
|
||||
|
||||
data.update(updated_data)
|
||||
with open(RobocodersAPI.CACHE_FILE, "w") as f:
|
||||
json.dump(data, f)
|
||||
|
||||
@staticmethod
|
||||
def _clear_cached_data():
|
||||
"""Remove cache file"""
|
||||
try:
|
||||
if RobocodersAPI.CACHE_FILE.exists():
|
||||
RobocodersAPI.CACHE_FILE.unlink()
|
||||
except Exception as e:
|
||||
debug.log(f"Error clearing cache: {e}")
|
||||
|
||||
@staticmethod
|
||||
def _get_cached_data() -> dict:
|
||||
"""Get all cached data"""
|
||||
if RobocodersAPI.CACHE_FILE.exists():
|
||||
try:
|
||||
with open(RobocodersAPI.CACHE_FILE, "r") as f:
|
||||
return json.load(f)
|
||||
except json.JSONDecodeError:
|
||||
return {}
|
||||
return {}
|
||||
|
||||
@ -30,6 +30,7 @@ from .MagickPen import MagickPen
|
||||
from .PerplexityLabs import PerplexityLabs
|
||||
from .Pi import Pi
|
||||
from .Pizzagpt import Pizzagpt
|
||||
from .PollinationsAI import PollinationsAI
|
||||
from .Prodia import Prodia
|
||||
from .Reka import Reka
|
||||
from .ReplicateHome import ReplicateHome
|
||||
|
||||
@ -16,7 +16,7 @@ except ImportError:
|
||||
|
||||
from ... import debug
|
||||
from ...typing import Messages, Cookies, ImageType, AsyncResult, AsyncIterator
|
||||
from ..base_provider import AsyncGeneratorProvider, BaseConversation, SynthesizeData
|
||||
from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin, BaseConversation, SynthesizeData
|
||||
from ..helper import format_prompt, get_cookies
|
||||
from ...requests.raise_for_status import raise_for_status
|
||||
from ...requests.aiohttp import get_connector
|
||||
@ -50,7 +50,7 @@ UPLOAD_IMAGE_HEADERS = {
|
||||
"x-tenant-id": "bard-storage",
|
||||
}
|
||||
|
||||
class Gemini(AsyncGeneratorProvider):
|
||||
class Gemini(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
url = "https://gemini.google.com"
|
||||
needs_auth = True
|
||||
working = True
|
||||
@ -329,4 +329,4 @@ async def iter_base64_decode(response_iter: AsyncIterator[bytes]) -> AsyncIterat
|
||||
chunk = buffer + chunk
|
||||
rest = len(chunk) % 4
|
||||
buffer = chunk[-rest:]
|
||||
yield base64.b64decode(chunk[:-rest])
|
||||
yield base64.b64decode(chunk[:-rest])
|
||||
|
||||
@ -1,70 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from urllib.parse import quote
|
||||
import random
|
||||
import requests
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ...typing import AsyncResult, Messages
|
||||
from ...image import ImageResponse
|
||||
from ...requests.raise_for_status import raise_for_status
|
||||
from ...requests.aiohttp import get_connector
|
||||
from .OpenaiAPI import OpenaiAPI
|
||||
from ..helper import format_prompt
|
||||
|
||||
class PollinationsAI(OpenaiAPI):
|
||||
label = "Pollinations.AI"
|
||||
url = "https://pollinations.ai"
|
||||
working = True
|
||||
needs_auth = False
|
||||
supports_stream = True
|
||||
default_model = "openai"
|
||||
|
||||
@classmethod
|
||||
def get_models(cls):
|
||||
if not cls.image_models:
|
||||
url = "https://image.pollinations.ai/models"
|
||||
response = requests.get(url)
|
||||
raise_for_status(response)
|
||||
cls.image_models = response.json()
|
||||
if not cls.models:
|
||||
url = "https://text.pollinations.ai/models"
|
||||
response = requests.get(url)
|
||||
raise_for_status(response)
|
||||
cls.models = [model.get("name") for model in response.json()]
|
||||
cls.models.extend(cls.image_models)
|
||||
return cls.models
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
prompt: str = None,
|
||||
api_base: str = "https://text.pollinations.ai/openai",
|
||||
api_key: str = None,
|
||||
proxy: str = None,
|
||||
seed: str = None,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
if model in cls.image_models:
|
||||
if prompt is None:
|
||||
prompt = messages[-1]["content"]
|
||||
if seed is None:
|
||||
seed = random.randint(0, 100000)
|
||||
image = f"https://image.pollinations.ai/prompt/{quote(prompt)}?width=1024&height=1024&seed={int(seed)}&nofeed=true&nologo=true&model={quote(model)}"
|
||||
yield ImageResponse(image, prompt)
|
||||
return
|
||||
if api_key is None:
|
||||
async with ClientSession(connector=get_connector(proxy=proxy)) as session:
|
||||
prompt = format_prompt(messages)
|
||||
async with session.get(f"https://text.pollinations.ai/{quote(prompt)}?model={quote(model)}") as response:
|
||||
await raise_for_status(response)
|
||||
async for line in response.content.iter_any():
|
||||
yield line.decode(errors="ignore")
|
||||
else:
|
||||
async for chunk in super().create_async_generator(
|
||||
model, messages, api_base=api_base, proxy=proxy, **kwargs
|
||||
):
|
||||
yield chunk
|
||||
@ -20,7 +20,6 @@ from .OpenaiAPI import OpenaiAPI
|
||||
from .OpenaiChat import OpenaiChat
|
||||
from .PerplexityApi import PerplexityApi
|
||||
from .Poe import Poe
|
||||
from .PollinationsAI import PollinationsAI
|
||||
from .Raycast import Raycast
|
||||
from .Replicate import Replicate
|
||||
from .Theb import Theb
|
||||
|
||||
113
g4f/models.py
113
g4f/models.py
@ -14,6 +14,7 @@ from .Provider import (
|
||||
Cloudflare,
|
||||
Copilot,
|
||||
CopilotAccount,
|
||||
DarkAI,
|
||||
DDG,
|
||||
DeepInfraChat,
|
||||
Free2GPT,
|
||||
@ -33,6 +34,7 @@ from .Provider import (
|
||||
PerplexityLabs,
|
||||
Pi,
|
||||
Pizzagpt,
|
||||
PollinationsAI,
|
||||
Reka,
|
||||
ReplicateHome,
|
||||
RubiksAI,
|
||||
@ -93,20 +95,20 @@ default = Model(
|
||||
gpt_35_turbo = Model(
|
||||
name = 'gpt-3.5-turbo',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = Blackbox
|
||||
best_provider = IterListProvider([Blackbox, ChatGptEs, PollinationsAI, DarkAI])
|
||||
)
|
||||
|
||||
# gpt-4
|
||||
gpt_4o = Model(
|
||||
name = 'gpt-4o',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([Blackbox, ChatGptEs, ChatGpt, AmigoChat, Airforce, Liaobots, OpenaiChat])
|
||||
best_provider = IterListProvider([Blackbox, ChatGptEs, PollinationsAI, DarkAI, ChatGpt, AmigoChat, Airforce, Liaobots, OpenaiChat])
|
||||
)
|
||||
|
||||
gpt_4o_mini = Model(
|
||||
name = 'gpt-4o-mini',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([DDG, ChatGptEs, Pizzagpt, ChatGpt, AmigoChat, Airforce, RubiksAI, MagickPen, Liaobots, OpenaiChat])
|
||||
best_provider = IterListProvider([DDG, Blackbox, ChatGptEs, Pizzagpt, ChatGpt, AmigoChat, Airforce, RubiksAI, MagickPen, Liaobots, OpenaiChat])
|
||||
)
|
||||
|
||||
gpt_4_turbo = Model(
|
||||
@ -118,7 +120,7 @@ gpt_4_turbo = Model(
|
||||
gpt_4 = Model(
|
||||
name = 'gpt-4',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([DDG, Copilot, OpenaiChat, Liaobots, Airforce])
|
||||
best_provider = IterListProvider([DDG, Blackbox, PollinationsAI, Copilot, OpenaiChat, Liaobots, Airforce])
|
||||
)
|
||||
|
||||
# o1
|
||||
@ -171,7 +173,7 @@ llama_3_1_8b = Model(
|
||||
llama_3_1_70b = Model(
|
||||
name = "llama-3.1-70b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([DDG, DeepInfraChat, Blackbox, Blackbox2, TeachAnything, Airforce, RubiksAI, HuggingChat, HuggingFace, PerplexityLabs])
|
||||
best_provider = IterListProvider([DDG, DeepInfraChat, Blackbox, Blackbox2, TeachAnything, PollinationsAI, DarkAI, Airforce, RubiksAI, HuggingChat, HuggingFace, PerplexityLabs])
|
||||
)
|
||||
|
||||
llama_3_1_405b = Model(
|
||||
@ -228,7 +230,13 @@ mistral_tiny = Model(
|
||||
mistral_nemo = Model(
|
||||
name = "mistral-nemo",
|
||||
base_provider = "Mistral",
|
||||
best_provider = IterListProvider([HuggingChat, AmigoChat, HuggingFace])
|
||||
best_provider = IterListProvider([PollinationsAI, HuggingChat, AmigoChat, HuggingFace])
|
||||
)
|
||||
|
||||
mistral_large = Model(
|
||||
name = "mistral-large",
|
||||
base_provider = "Mistral",
|
||||
best_provider = PollinationsAI
|
||||
)
|
||||
|
||||
### NousResearch ###
|
||||
@ -320,7 +328,7 @@ claude_3_haiku = Model(
|
||||
claude_3_5_sonnet = Model(
|
||||
name = 'claude-3.5-sonnet',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([Blackbox, AmigoChat, Liaobots])
|
||||
best_provider = IterListProvider([Blackbox, PollinationsAI, AmigoChat, Liaobots])
|
||||
)
|
||||
|
||||
claude_3_5_haiku = Model(
|
||||
@ -353,7 +361,7 @@ blackboxai_pro = Model(
|
||||
command_r_plus = Model(
|
||||
name = 'command-r-plus',
|
||||
base_provider = 'CohereForAI',
|
||||
best_provider = IterListProvider([HuggingChat, AmigoChat])
|
||||
best_provider = IterListProvider([PollinationsAI, HuggingChat, AmigoChat])
|
||||
)
|
||||
|
||||
### Qwen ###
|
||||
@ -381,7 +389,7 @@ qwen_2_5_72b = Model(
|
||||
qwen_2_5_coder_32b = Model(
|
||||
name = 'qwen-2.5-coder-32b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = IterListProvider([DeepInfraChat, HuggingChat, HuggingFace])
|
||||
best_provider = IterListProvider([DeepInfraChat, PollinationsAI, HuggingChat, HuggingFace])
|
||||
)
|
||||
|
||||
qwq_32b = Model(
|
||||
@ -431,13 +439,6 @@ wizardlm_2_8x22b = Model(
|
||||
best_provider = DeepInfraChat
|
||||
)
|
||||
|
||||
### Yorickvp ###
|
||||
llava_13b = Model(
|
||||
name = 'llava-13b',
|
||||
base_provider = 'Yorickvp',
|
||||
best_provider = ReplicateHome
|
||||
)
|
||||
|
||||
### OpenChat ###
|
||||
openchat_3_5 = Model(
|
||||
name = 'openchat-3.5',
|
||||
@ -551,11 +552,18 @@ jamba_mini = Model(
|
||||
best_provider = AmigoChat
|
||||
)
|
||||
|
||||
### llmplayground.net ###
|
||||
any_uncensored = Model(
|
||||
name = 'any-uncensored',
|
||||
base_provider = 'llmplayground.net',
|
||||
best_provider = Airforce
|
||||
### PollinationsAI ###
|
||||
p1 = Model(
|
||||
name = 'p1',
|
||||
base_provider = 'PollinationsAI',
|
||||
best_provider = PollinationsAI
|
||||
)
|
||||
|
||||
### Uncensored AI ###
|
||||
evil = Model(
|
||||
name = 'evil',
|
||||
base_provider = 'Evil Mode - Experimental',
|
||||
best_provider = IterListProvider([PollinationsAI, Airforce])
|
||||
)
|
||||
|
||||
#############
|
||||
@ -588,13 +596,13 @@ playground_v2_5 = ImageModel(
|
||||
flux = ImageModel(
|
||||
name = 'flux',
|
||||
base_provider = 'Flux AI',
|
||||
best_provider = IterListProvider([Blackbox, Airforce])
|
||||
best_provider = IterListProvider([Blackbox, Blackbox2, PollinationsAI, Airforce])
|
||||
)
|
||||
|
||||
flux_pro = ImageModel(
|
||||
name = 'flux-pro',
|
||||
base_provider = 'Flux AI',
|
||||
best_provider = Airforce
|
||||
best_provider = IterListProvider([PollinationsAI, Airforce])
|
||||
)
|
||||
|
||||
flux_dev = ImageModel(
|
||||
@ -606,19 +614,25 @@ flux_dev = ImageModel(
|
||||
flux_realism = ImageModel(
|
||||
name = 'flux-realism',
|
||||
base_provider = 'Flux AI',
|
||||
best_provider = IterListProvider([Airforce, AmigoChat])
|
||||
best_provider = IterListProvider([PollinationsAI, Airforce, AmigoChat])
|
||||
)
|
||||
|
||||
flux_cablyai = Model(
|
||||
name = 'flux-cablyai',
|
||||
base_provider = 'Flux AI',
|
||||
best_provider = PollinationsAI
|
||||
)
|
||||
|
||||
flux_anime = ImageModel(
|
||||
name = 'flux-anime',
|
||||
base_provider = 'Flux AI',
|
||||
best_provider = Airforce
|
||||
best_provider = IterListProvider([PollinationsAI, Airforce])
|
||||
)
|
||||
|
||||
flux_3d = ImageModel(
|
||||
name = 'flux-3d',
|
||||
base_provider = 'Flux AI',
|
||||
best_provider = Airforce
|
||||
best_provider = IterListProvider([PollinationsAI, Airforce])
|
||||
)
|
||||
|
||||
flux_disney = ImageModel(
|
||||
@ -653,11 +667,36 @@ recraft_v3 = ImageModel(
|
||||
best_provider = AmigoChat
|
||||
)
|
||||
|
||||
### Midjourney ###
|
||||
midijourney = Model(
|
||||
name = 'midijourney',
|
||||
base_provider = 'Midjourney',
|
||||
best_provider = PollinationsAI
|
||||
)
|
||||
|
||||
### Other ###
|
||||
any_dark = ImageModel(
|
||||
name = 'any-dark',
|
||||
base_provider = 'Other',
|
||||
best_provider = Airforce
|
||||
best_provider = IterListProvider([PollinationsAI, Airforce])
|
||||
)
|
||||
|
||||
turbo = Model(
|
||||
name = 'turbo',
|
||||
base_provider = 'Other',
|
||||
best_provider = PollinationsAI
|
||||
)
|
||||
|
||||
unity = Model(
|
||||
name = 'unity',
|
||||
base_provider = 'Other',
|
||||
best_provider = PollinationsAI
|
||||
)
|
||||
|
||||
rtist = Model(
|
||||
name = 'rtist',
|
||||
base_provider = 'Other',
|
||||
best_provider = PollinationsAI
|
||||
)
|
||||
|
||||
class ModelUtils:
|
||||
@ -716,6 +755,7 @@ class ModelUtils:
|
||||
'mixtral-8x7b': mixtral_8x7b,
|
||||
'mistral-tiny': mistral_tiny,
|
||||
'mistral-nemo': mistral_nemo,
|
||||
'mistral-large': mistral_large,
|
||||
|
||||
### NousResearch ###
|
||||
'mixtral-8x7b-dpo': mixtral_8x7b_dpo,
|
||||
@ -778,9 +818,6 @@ class ModelUtils:
|
||||
### Inflection ###
|
||||
'pi': pi,
|
||||
|
||||
### Yorickvp ###
|
||||
'llava-13b': llava_13b,
|
||||
|
||||
### WizardLM ###
|
||||
'wizardlm-2-8x22b': wizardlm_2_8x22b,
|
||||
|
||||
@ -830,9 +867,12 @@ class ModelUtils:
|
||||
### Gryphe ###
|
||||
'mythomax-13b': mythomax_13b,
|
||||
|
||||
### llmplayground.net ###
|
||||
'any-uncensored': any_uncensored,
|
||||
|
||||
### PollinationsAI ###
|
||||
'p1': p1,
|
||||
|
||||
### Uncensored AI ###
|
||||
'evil': evil,
|
||||
|
||||
#############
|
||||
### Image ###
|
||||
#############
|
||||
@ -849,6 +889,7 @@ class ModelUtils:
|
||||
'flux-pro': flux_pro,
|
||||
'flux-dev': flux_dev,
|
||||
'flux-realism': flux_realism,
|
||||
'flux-cablyai': flux_cablyai,
|
||||
'flux-anime': flux_anime,
|
||||
'flux-3d': flux_3d,
|
||||
'flux-disney': flux_disney,
|
||||
@ -861,8 +902,14 @@ class ModelUtils:
|
||||
### Recraft ###
|
||||
'recraft-v3': recraft_v3,
|
||||
|
||||
### Midjourney ###
|
||||
'midijourney': midijourney,
|
||||
|
||||
### Other ###
|
||||
'any-dark': any_dark,
|
||||
'turbo': turbo,
|
||||
'unity': unity,
|
||||
'rtist': rtist,
|
||||
}
|
||||
|
||||
# Create a list of all working models
|
||||
|
||||
Loading…
Reference in New Issue
Block a user