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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 <>
104 lines
4.0 KiB
Python
104 lines
4.0 KiB
Python
from __future__ import annotations
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import random
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import json
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from ..typing import AsyncResult, Messages
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from ..requests import StreamSession, raise_for_status
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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API_URL = "https://www.perplexity.ai/socket.io/"
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WS_URL = "wss://www.perplexity.ai/socket.io/"
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class PerplexityLabs(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://labs.perplexity.ai"
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working = True
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default_model = "llama-3.1-70b-instruct"
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models = [
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"llama-3.1-sonar-large-128k-online",
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"llama-3.1-sonar-small-128k-online",
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"llama-3.1-sonar-large-128k-chat",
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"llama-3.1-sonar-small-128k-chat",
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"llama-3.1-8b-instruct",
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"llama-3.1-70b-instruct",
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"/models/LiquidCloud",
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]
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model_aliases = {
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"sonar-online": "llama-3.1-sonar-large-128k-online",
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"sonar-online": "sonar-small-128k-online",
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"sonar-chat": "llama-3.1-sonar-large-128k-chat",
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"sonar-chat": "llama-3.1-sonar-small-128k-chat",
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"llama-3.3-70b": "llama-3.3-70b-instruct",
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"llama-3.1-8b": "llama-3.1-8b-instruct",
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"llama-3.1-70b": "llama-3.1-70b-instruct",
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"lfm-40b": "/models/LiquidCloud",
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}
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: Messages,
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proxy: str = None,
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**kwargs
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) -> AsyncResult:
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:121.0) Gecko/20100101 Firefox/121.0",
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"Accept": "*/*",
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"Accept-Language": "de,en-US;q=0.7,en;q=0.3",
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"Accept-Encoding": "gzip, deflate, br",
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"Origin": cls.url,
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"Connection": "keep-alive",
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"Referer": f"{cls.url}/",
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"Sec-Fetch-Dest": "empty",
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"Sec-Fetch-Mode": "cors",
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"Sec-Fetch-Site": "same-site",
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"TE": "trailers",
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}
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async with StreamSession(headers=headers, proxies={"all": proxy}) as session:
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t = format(random.getrandbits(32), "08x")
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async with session.get(
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f"{API_URL}?EIO=4&transport=polling&t={t}"
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) as response:
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await raise_for_status(response)
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text = await response.text()
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assert text.startswith("0")
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sid = json.loads(text[1:])["sid"]
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post_data = '40{"jwt":"anonymous-ask-user"}'
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async with session.post(
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f"{API_URL}?EIO=4&transport=polling&t={t}&sid={sid}",
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data=post_data
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) as response:
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await raise_for_status(response)
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assert await response.text() == "OK"
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async with session.ws_connect(f"{WS_URL}?EIO=4&transport=websocket&sid={sid}", autoping=False) as ws:
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await ws.send_str("2probe")
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assert(await ws.receive_str() == "3probe")
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await ws.send_str("5")
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assert(await ws.receive_str())
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assert(await ws.receive_str() == "6")
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message_data = {
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"version": "2.13",
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"source": "default",
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"model": model,
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"messages": messages
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}
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await ws.send_str("42" + json.dumps(["perplexity_labs", message_data]))
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last_message = 0
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while True:
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message = await ws.receive_str()
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if message == "2":
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if last_message == 0:
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raise RuntimeError("Unknown error")
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await ws.send_str("3")
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continue
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try:
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data = json.loads(message[2:])[1]
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yield data["output"][last_message:]
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last_message = len(data["output"])
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if data["final"]:
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break
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except:
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raise RuntimeError(f"Message: {message}")
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