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https://github.com/xtekky/gpt4free.git
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* Update model configurations, provider implementations, and documentation - Updated model names and aliases for Qwen QVQ 72B and Qwen 2 72B (@TheFirstNoob) - Revised HuggingSpace class configuration, added default_image_model - Added llama-3.2-70b alias for Llama 3.2 70B model in AutonomousAI - Removed BlackboxCreateAgent class - Added gpt-4o alias for Copilot model - Moved api_key to Mhystical class attribute - Added models property with default_model value for Free2GPT - Simplified Jmuz class implementation - Improved image generation and model handling in DeepInfra - Standardized default models and removed aliases in Gemini - Replaced model aliases with direct model list in GlhfChat (@TheFirstNoob) - Removed trailing slash from image generation URL in PollinationsAI (https://github.com/xtekky/gpt4free/issues/2571) - Updated llama and qwen model configurations - Enhanced provider documentation and model details * Removed from (g4f/models.py) 'Yqcloud' provider from Default due to error 'ResponseStatusError: Response 429: 文字过长，请删减后重试。' * Update docs/providers-and-models.md * refactor(g4f/Provider/DDG.py): Add error handling and rate limiting to DDG provider - Add custom exception classes for rate limits, timeouts, and conversation limits - Implement rate limiting with sleep between requests (0.75s minimum delay) - Add model validation method to check supported models - Add proper error handling for API responses with custom exceptions - Improve session cookie handling for conversation persistence - Clean up User-Agent string and remove redundant code - Add proper error propagation through async generator Breaking changes: - New custom exceptions may require updates to error handling code - Rate limiting affects request timing and throughput - Model validation is now stricter Related: - Adds error handling similar to standard API clients - Improves reliability and robustness of chat interactions * Update g4f/models.py g4f/Provider/PollinationsAI.py * Update g4f/models.py * Restored provider which was not working and was disabled (g4f/Provider/DeepInfraChat.py) * Fixing a bug with Streaming Completions * Update g4f/Provider/PollinationsAI.py * Update g4f/Provider/Blackbox.py g4f/Provider/DDG.py * Added another model for generating images 'ImageGeneration2' to the 'Blackbox' provider * Update docs/providers-and-models.md * Update g4f/models.py g4f/Provider/Blackbox.py * Added a new OIVSCode provider from the Text Models and Vision (Image Upload) model * Update docs/providers-and-models.md * docs: add Conversation Memory class with context handling requested by @TheFirstNoob * Simplified README.md documentation added new docs/configuration.md documentation * Update add README.md docs/configuration.md * Update README.md * Update docs/providers-and-models.md g4f/models.py g4f/Provider/PollinationsAI.py * Added new model deepseek-r1 to Blackbox provider. @TheFirstNoob * Fixed bugs and updated docs/providers-and-models.md etc/unittest/client.py g4f/models.py g4f/Provider/. --------- Co-authored-by: kqlio67 <> Co-authored-by: H Lohaus <hlohaus@users.noreply.github.com>
51 lines
No EOL
1.6 KiB
Python
51 lines
No EOL
1.6 KiB
Python
from __future__ import annotations
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from aiohttp import ClientSession
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from .OpenaiAPI import OpenaiAPI
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from ...typing import AsyncResult, Messages, Cookies
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from ...requests.raise_for_status import raise_for_status
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from ...cookies import get_cookies
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class Cerebras(OpenaiAPI):
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label = "Cerebras Inference"
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url = "https://inference.cerebras.ai/"
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login_url = "https://cloud.cerebras.ai"
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api_base = "https://api.cerebras.ai/v1"
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working = True
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default_model = "llama3.1-70b"
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models = [
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default_model,
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"llama3.1-8b",
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"llama-3.3-70b"
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]
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model_aliases = {"llama-3.1-70b": default_model, "llama-3.1-8b": "llama3.1-8b"}
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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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api_key: str = None,
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cookies: Cookies = None,
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**kwargs
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) -> AsyncResult:
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if api_key is None:
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if cookies is None:
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cookies = get_cookies(".cerebras.ai")
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async with ClientSession(cookies=cookies) as session:
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async with session.get("https://inference.cerebras.ai/api/auth/session") as response:
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await raise_for_status(response)
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data = await response.json()
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if data:
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api_key = data.get("user", {}).get("demoApiKey")
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async for chunk in super().create_async_generator(
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model, messages,
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impersonate="chrome",
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api_key=api_key,
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headers={
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"User-Agent": "ex/JS 1.5.0",
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},
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**kwargs
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):
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yield chunk |