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Update (g4f/Provider/Airforce.py)
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@ -16,12 +16,12 @@ This document provides an overview of various AI providers and models, including
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| Provider | Text Models | Image Models | Vision Models | Stream | Status | Auth |
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|----------|-------------|--------------|---------------|--------|--------|------|
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|[ai4chat.co](https://www.ai4chat.co)|`g4f.Provider.Ai4Chat`|`gpt-4`|❌|❌|✔||❌|
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|[chat.ai365vip.com](https://chat.ai365vip.com)|`g4f.Provider.AI365VIP`|`gpt-3.5-turbo, gpt-4o`|❌|❌|?||❌|
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|[chat.ai365vip.com](https://chat.ai365vip.com)|`g4f.Provider.AI365VIP`|✔|❌|❌|?||❌|
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|[aichatfree.info](https://aichatfree.info)|`g4f.Provider.AIChatFree`|`gemini-pro`|❌|❌|✔||❌|
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|[aichatonline.org](https://aichatonline.org)|`g4f.Provider.AiChatOnline`|`gpt-4o-mini`|❌|❌|?||❌|
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|[ai-chats.org](https://ai-chats.org)|`g4f.Provider.AiChats`|`gpt-4`|`dalle`|❌|?||❌|
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|[api.airforce](https://api.airforce)|`g4f.Provider.AiMathGPT`|`llama-3.1-70b`|❌|❌|✔||❌|
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|[api.airforce](https://api.airforce)|`g4f.Provider.Airforce`|`gpt-4, gpt-4-turbo, gpt-4o-mini, gpt-3.5-turbo, gpt-4o, claude-3-haiku, claude-3-sonnet, claude-3-5-sonnet, claude-3-opus, llama-3-70b, llama-3-8b, llama-2-13b, llama-3.1-405b, llama-3.1-70b, llama-3.1-8b, llamaguard-2-8b, llamaguard-7b, llama-3.2-90b, mixtral-8x7b mixtral-8x22b, mistral-7b, qwen-1.5-7b, qwen-1.5-14b, qwen-1.5-72b, qwen-1.5-110b, qwen-2-72b, gemma-2b, gemma-2-9b, gemma-2-27b, gemini-flash, gemini-pro, deepseek, mixtral-8x7b-dpo, yi-34b, wizardlm-2-8x22b, solar-10.7b, mythomax-l2-13b, cosmosrp`|`flux, flux-realism', flux-anime, flux-3d, flux-disney, flux-pixel, flux-4o, any-dark, dalle-3`|❌|✔||❌|
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|[api.airforce](https://api.airforce)|`g4f.Provider.Airforce`|`claude-3-haiku, claude-3-sonnet, claude-3-opus, gpt-4, gpt-4-turbo, gpt-4o-mini, gpt-3.5-turbo, llama-3-70b, llama-3-8b, llama-2-13b, llama-3.1-405b, llama-3.1-70b, llama-3.1-8b, llamaguard-2-8b, llamaguard-7b, llama-3.2-90b, llamaguard-3-8b, llama-3.2-11b, llamaguard-3-11b, llama-3.2-3b, llama-3.2-1b, llama-2-7b, mixtral-8x7b, mixtral-8x22b, mythomax-13b, openchat-3.5, qwen-2-72b, qwen-2-5-7b, qwen-2-5-72b, gemma-2b, gemma-2-9b, gemma-2b-27b, gemini-flash, gemini-pro, dbrx-instruct, deepseek-coder, hermes-2-dpo, hermes-2, openhermes-2.5, wizardlm-2-8x22b, phi-2, solar-10-7b, cosmosrp, lfm-40b, german-7b, zephyr-7b`|`flux, flux-realism', flux-anime, flux-3d, flux-disney, flux-pixel, flux-4o, any-dark, dalle-3`|❌|✔||❌|
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|[aiuncensored.info](https://www.aiuncensored.info)|`g4f.Provider.AIUncensored`|✔|✔|❌|✔||❌|
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|[allyfy.chat](https://allyfy.chat/)|`g4f.Provider.Allyfy`|`gpt-3.5-turbo`|❌|❌|✔||❌|
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|[amigochat.io/chat](https://amigochat.io/chat/)|`g4f.Provider.AmigoChat`|`gpt-4o, gpt-4o-mini, o1, o1-mini, claude-3.5-sonnet, llama-3.2-90b, llama-3.1-405b, gemini-pro`|`flux-pro, flux-realism, dalle-3`|❌|✔||❌|
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@ -131,6 +131,8 @@ This document provides an overview of various AI providers and models, including
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|mistral-nemo|Mistral AI|2+ Providers|[huggingface.co](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)|
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|mistral-large|Mistral AI|2+ Providers|[mistral.ai](https://mistral.ai/news/mistral-large-2407/)|
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|mixtral-8x7b-dpo|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO)|
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|hermes-2-dpo|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO)|
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|hermes-2|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B)|
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|yi-34b|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Yi-34B)|
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|hermes-3|NousResearch|2+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B)|
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|gemini|Google DeepMind|1+ Providers|[deepmind.google](http://deepmind.google/technologies/gemini/)|
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@ -170,7 +172,7 @@ This document provides an overview of various AI providers and models, including
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|solar-10-7b|Upstage|1+ Providers|[huggingface.co](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)|
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|solar-pro|Upstage|1+ Providers|[huggingface.co](https://huggingface.co/upstage/solar-pro-preview-instruct)|
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|pi|Inflection|1+ Providers|[inflection.ai](https://inflection.ai/blog/inflection-2-5)|
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|deepseek|DeepSeek|1+ Providers|[deepseek.com](https://www.deepseek.com/)|
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|deepseek-coder|DeepSeek|1+ Providers|[huggingface.co](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Instruct)|
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|wizardlm-2-7b|WizardLM|1+ Providers|[huggingface.co](https://huggingface.co/dreamgen/WizardLM-2-7B)|
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|wizardlm-2-8x22b|WizardLM|2+ Providers|[huggingface.co](https://huggingface.co/alpindale/WizardLM-2-8x22B)|
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|sh-n-7b|Together|1+ Providers|[huggingface.co](https://huggingface.co/togethercomputer/StripedHyena-Nous-7B)|
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@ -190,6 +192,10 @@ This document provides an overview of various AI providers and models, including
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|german-7b|TheBloke|1+ Providers|[huggingface.co](https://huggingface.co/TheBloke/DiscoLM_German_7b_v1-GGUF)|
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|tinyllama-1.1b|TinyLlama|1+ Providers|[huggingface.co](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0)|
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|cybertron-7b|TheBloke|1+ Providers|[huggingface.co](https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16)|
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|openhermes-2.5|Teknium|1+ Providers|[huggingface.co](https://huggingface.co/datasets/teknium/OpenHermes-2.5)|
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|lfm-40b|Liquid|1+ Providers|[liquid.ai](https://www.liquid.ai/liquid-foundation-models)|
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|zephyr-7b|HuggingFaceH4|1+ Providers|[huggingface.co](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta)|
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### Image Models
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| Model | Base Provider | Providers | Website |
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@ -1,105 +1,30 @@
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from __future__ import annotations
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import random
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import json
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import re
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from typing import Any, Dict
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import inspect
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from aiohttp import ClientSession
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from ..typing import AsyncResult, Messages
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from ..image import ImageResponse
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def split_long_message(message: str, max_length: int = 4000) -> list[str]:
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return [message[i:i+max_length] for i in range(0, len(message), max_length)]
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from .helper import format_prompt
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from .airforce.AirforceChat import AirforceChat
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from .airforce.AirforceImage import AirforceImage
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class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://api.airforce"
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image_api_endpoint = "https://api.airforce/imagine2"
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text_api_endpoint = "https://api.airforce/chat/completions"
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api_endpoint_completions = AirforceChat.api_endpoint_completions
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api_endpoint_imagine2 = AirforceImage.api_endpoint_imagine2
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working = True
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supports_stream = AirforceChat.supports_stream
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supports_system_message = AirforceChat.supports_system_message
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supports_message_history = AirforceChat.supports_message_history
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default_model = 'llama-3-70b-chat'
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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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text_models = [
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'claude-3-haiku-20240307',
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'claude-3-sonnet-20240229',
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'claude-3-5-sonnet-20240620',
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'claude-3-opus-20240229',
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'chatgpt-4o-latest',
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'gpt-4',
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'gpt-4-turbo',
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'gpt-4o-mini-2024-07-18',
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'gpt-4o-mini',
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'gpt-3.5-turbo',
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'gpt-3.5-turbo-0125',
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'gpt-3.5-turbo-1106',
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default_model,
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'llama-3-70b-chat-turbo',
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'llama-3-8b-chat',
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'llama-3-8b-chat-turbo',
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'llama-3-70b-chat-lite',
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'llama-3-8b-chat-lite',
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'llama-2-13b-chat',
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'llama-3.1-405b-turbo',
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'llama-3.1-70b-turbo',
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'llama-3.1-8b-turbo',
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'LlamaGuard-2-8b',
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'Llama-Guard-7b',
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'Llama-3.2-90B-Vision-Instruct-Turbo',
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'Mixtral-8x7B-Instruct-v0.1',
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'Mixtral-8x22B-Instruct-v0.1',
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'Mistral-7B-Instruct-v0.1',
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'Mistral-7B-Instruct-v0.2',
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'Mistral-7B-Instruct-v0.3',
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'Qwen1.5-7B-Chat',
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'Qwen1.5-14B-Chat',
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'Qwen1.5-72B-Chat',
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'Qwen1.5-110B-Chat',
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'Qwen2-72B-Instruct',
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'gemma-2b-it',
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'gemma-2-9b-it',
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'gemma-2-27b-it',
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'gemini-1.5-flash',
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'gemini-1.5-pro',
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'deepseek-llm-67b-chat',
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'Nous-Hermes-2-Mixtral-8x7B-DPO',
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'Nous-Hermes-2-Yi-34B',
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'WizardLM-2-8x22B',
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'SOLAR-10.7B-Instruct-v1.0',
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'MythoMax-L2-13b',
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'cosmosrp',
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]
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image_models = [
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'flux',
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'flux-realism',
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'flux-anime',
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'flux-3d',
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'flux-disney',
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'flux-pixel',
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'flux-4o',
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'any-dark',
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]
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models = [
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*text_models,
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*image_models,
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]
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default_model = AirforceChat.default_model
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models = [*AirforceChat.text_models, *AirforceImage.image_models]
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model_aliases = {
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"claude-3-haiku": "claude-3-haiku-20240307",
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"claude-3-sonnet": "claude-3-sonnet-20240229",
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"gpt-4o": "chatgpt-4o-latest",
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"llama-3-70b": "llama-3-70b-chat",
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"llama-3-8b": "llama-3-8b-chat",
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"mixtral-8x7b": "Mixtral-8x7B-Instruct-v0.1",
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"qwen-1.5-7b": "Qwen1.5-7B-Chat",
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"gemma-2b": "gemma-2b-it",
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"gemini-flash": "gemini-1.5-flash",
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"mythomax-l2-13b": "MythoMax-L2-13b",
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"solar-10.7b": "SOLAR-10.7B-Instruct-v1.0",
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**AirforceChat.model_aliases,
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**AirforceImage.model_aliases
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}
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@classmethod
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@ -107,139 +32,28 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
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if model in cls.models:
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return model
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elif model in cls.model_aliases:
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return cls.model_aliases.get(model, cls.default_model)
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return cls.model_aliases[model]
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else:
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return cls.default_model
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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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seed: int = None,
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size: str = "1:1",
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stream: bool = False,
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**kwargs
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) -> AsyncResult:
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async def create_async_generator(cls, model: str, messages: Messages, **kwargs) -> AsyncResult:
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model = cls.get_model(model)
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provider = AirforceChat if model in AirforceChat.text_models else AirforceImage
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if model in cls.image_models:
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async for result in cls._generate_image(model, messages, proxy, seed, size):
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yield result
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elif model in cls.text_models:
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async for result in cls._generate_text(model, messages, proxy, stream):
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yield result
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@classmethod
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async def _generate_image(
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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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seed: int = None,
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size: str = "1:1",
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**kwargs
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) -> AsyncResult:
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headers = {
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"accept": "*/*",
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"accept-language": "en-US,en;q=0.9",
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"cache-control": "no-cache",
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"origin": "https://llmplayground.net",
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"user-agent": "Mozilla/5.0"
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}
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if model not in provider.models:
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raise ValueError(f"Unsupported model: {model}")
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if seed is None:
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seed = random.randint(0, 100000)
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# Get the signature of the provider's create_async_generator method
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sig = inspect.signature(provider.create_async_generator)
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# Filter kwargs to only include parameters that the provider's method accepts
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filtered_kwargs = {k: v for k, v in kwargs.items() if k in sig.parameters}
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prompt = messages[-1]['content']
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# Add model and messages to filtered_kwargs
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filtered_kwargs['model'] = model
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filtered_kwargs['messages'] = messages
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async with ClientSession(headers=headers) as session:
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params = {
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"model": model,
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"prompt": prompt,
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"size": size,
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"seed": seed
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}
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async with session.get(f"{cls.image_api_endpoint}", params=params, proxy=proxy) as response:
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response.raise_for_status()
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content_type = response.headers.get('Content-Type', '').lower()
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if 'application/json' in content_type:
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async for chunk in response.content.iter_chunked(1024):
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if chunk:
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yield chunk.decode('utf-8')
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elif 'image' in content_type:
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image_data = b""
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async for chunk in response.content.iter_chunked(1024):
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if chunk:
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image_data += chunk
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image_url = f"{cls.image_api_endpoint}?model={model}&prompt={prompt}&size={size}&seed={seed}"
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alt_text = f"Generated image for prompt: {prompt}"
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yield ImageResponse(images=image_url, alt=alt_text)
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@classmethod
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async def _generate_text(
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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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stream: bool = False,
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**kwargs
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) -> AsyncResult:
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headers = {
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"accept": "*/*",
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"accept-language": "en-US,en;q=0.9",
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"authorization": "Bearer missing api key",
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"content-type": "application/json",
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"user-agent": "Mozilla/5.0"
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}
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async with ClientSession(headers=headers) as session:
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formatted_prompt = cls._format_messages(messages)
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prompt_parts = split_long_message(formatted_prompt)
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full_response = ""
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for part in prompt_parts:
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data = {
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"messages": [{"role": "user", "content": part}],
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"model": model,
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"max_tokens": 4096,
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"temperature": 1,
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"top_p": 1,
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"stream": stream
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}
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async with session.post(cls.text_api_endpoint, json=data, proxy=proxy) as response:
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response.raise_for_status()
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part_response = ""
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if stream:
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async for line in response.content:
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if line:
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line = line.decode('utf-8').strip()
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if line.startswith("data: ") and line != "data: [DONE]":
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json_data = json.loads(line[6:])
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content = json_data['choices'][0]['delta'].get('content', '')
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part_response += content
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else:
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json_data = await response.json()
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content = json_data['choices'][0]['message']['content']
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part_response = content
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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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full_response += part_response
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yield full_response
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@classmethod
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def _format_messages(cls, messages: Messages) -> str:
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return " ".join([msg['content'] for msg in messages])
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async for result in provider.create_async_generator(**filtered_kwargs):
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yield result
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375
g4f/Provider/airforce/AirforceChat.py
Normal file
375
g4f/Provider/airforce/AirforceChat.py
Normal file
@ -0,0 +1,375 @@
|
||||
from __future__ import annotations
|
||||
import re
|
||||
from aiohttp import ClientSession
|
||||
import json
|
||||
from typing import List
|
||||
|
||||
from ...typing import AsyncResult, Messages
|
||||
from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
|
||||
from ..helper import format_prompt
|
||||
|
||||
def clean_response(text: str) -> str:
|
||||
"""Clean response from unwanted patterns."""
|
||||
patterns = [
|
||||
r"One message exceeds the \d+chars per message limit\..+https:\/\/discord\.com\/invite\/\S+",
|
||||
r"Rate limit \(\d+\/minute\) exceeded\. Join our discord for more: .+https:\/\/discord\.com\/invite\/\S+",
|
||||
r"Rate limit \(\d+\/hour\) exceeded\. Join our discord for more: https:\/\/discord\.com\/invite\/\S+",
|
||||
r"</s>", # zephyr-7b-beta
|
||||
]
|
||||
|
||||
for pattern in patterns:
|
||||
text = re.sub(pattern, '', text)
|
||||
return text.strip()
|
||||
|
||||
def split_message(message: dict, chunk_size: int = 995) -> List[dict]:
|
||||
"""Split a message into chunks of specified size."""
|
||||
content = message.get('content', '')
|
||||
if len(content) <= chunk_size:
|
||||
return [message]
|
||||
|
||||
chunks = []
|
||||
while content:
|
||||
chunk = content[:chunk_size]
|
||||
content = content[chunk_size:]
|
||||
chunks.append({
|
||||
'role': message['role'],
|
||||
'content': chunk
|
||||
})
|
||||
return chunks
|
||||
|
||||
def split_messages(messages: Messages, chunk_size: int = 995) -> Messages:
|
||||
"""Split all messages that exceed chunk_size into smaller messages."""
|
||||
result = []
|
||||
for message in messages:
|
||||
result.extend(split_message(message, chunk_size))
|
||||
return result
|
||||
|
||||
class AirforceChat(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
label = "AirForce Chat"
|
||||
api_endpoint_completions = "https://api.airforce/chat/completions" # Замініть на реальний ендпоінт
|
||||
supports_stream = True
|
||||
supports_system_message = True
|
||||
supports_message_history = True
|
||||
|
||||
default_model = 'llama-3-70b-chat'
|
||||
text_models = [
|
||||
# anthropic
|
||||
'claude-3-haiku-20240307',
|
||||
'claude-3-sonnet-20240229',
|
||||
'claude-3-5-sonnet-20240620',
|
||||
'claude-3-5-sonnet-20241022',
|
||||
'claude-3-opus-20240229',
|
||||
|
||||
# openai
|
||||
'chatgpt-4o-latest',
|
||||
'gpt-4',
|
||||
'gpt-4-turbo',
|
||||
'gpt-4o-2024-05-13',
|
||||
'gpt-4o-mini-2024-07-18',
|
||||
'gpt-4o-mini',
|
||||
'gpt-4o-2024-08-06',
|
||||
'gpt-3.5-turbo',
|
||||
'gpt-3.5-turbo-0125',
|
||||
'gpt-3.5-turbo-1106',
|
||||
'gpt-4o',
|
||||
'gpt-4-turbo-2024-04-09',
|
||||
'gpt-4-0125-preview',
|
||||
'gpt-4-1106-preview',
|
||||
|
||||
# meta-llama
|
||||
default_model,
|
||||
'llama-3-70b-chat-turbo',
|
||||
'llama-3-8b-chat',
|
||||
'llama-3-8b-chat-turbo',
|
||||
'llama-3-70b-chat-lite',
|
||||
'llama-3-8b-chat-lite',
|
||||
'llama-2-13b-chat',
|
||||
'llama-3.1-405b-turbo',
|
||||
'llama-3.1-70b-turbo',
|
||||
'llama-3.1-8b-turbo',
|
||||
'LlamaGuard-2-8b',
|
||||
'llamaguard-7b',
|
||||
'Llama-Vision-Free',
|
||||
'Llama-Guard-7b',
|
||||
'Llama-3.2-90B-Vision-Instruct-Turbo',
|
||||
'Meta-Llama-Guard-3-8B',
|
||||
'Llama-3.2-11B-Vision-Instruct-Turbo',
|
||||
'Llama-Guard-3-11B-Vision-Turbo',
|
||||
'Llama-3.2-3B-Instruct-Turbo',
|
||||
'Llama-3.2-1B-Instruct-Turbo',
|
||||
'llama-2-7b-chat-int8',
|
||||
'llama-2-7b-chat-fp16',
|
||||
'Llama 3.1 405B Instruct',
|
||||
'Llama 3.1 70B Instruct',
|
||||
'Llama 3.1 8B Instruct',
|
||||
|
||||
# mistral-ai
|
||||
'Mixtral-8x7B-Instruct-v0.1',
|
||||
'Mixtral-8x22B-Instruct-v0.1',
|
||||
'Mistral-7B-Instruct-v0.1',
|
||||
'Mistral-7B-Instruct-v0.2',
|
||||
'Mistral-7B-Instruct-v0.3',
|
||||
|
||||
# Gryphe
|
||||
'MythoMax-L2-13b-Lite',
|
||||
'MythoMax-L2-13b',
|
||||
|
||||
# openchat
|
||||
'openchat-3.5-0106',
|
||||
|
||||
# qwen
|
||||
#'Qwen1.5-72B-Chat', Пуста відповідь
|
||||
#'Qwen1.5-110B-Chat', Пуста відповідь
|
||||
'Qwen2-72B-Instruct',
|
||||
'Qwen2.5-7B-Instruct-Turbo',
|
||||
'Qwen2.5-72B-Instruct-Turbo',
|
||||
|
||||
# google
|
||||
'gemma-2b-it',
|
||||
'gemma-2-9b-it',
|
||||
'gemma-2-27b-it',
|
||||
|
||||
# gemini
|
||||
'gemini-1.5-flash',
|
||||
'gemini-1.5-pro',
|
||||
|
||||
# databricks
|
||||
'dbrx-instruct',
|
||||
|
||||
# deepseek-ai
|
||||
'deepseek-coder-6.7b-base',
|
||||
'deepseek-coder-6.7b-instruct',
|
||||
'deepseek-math-7b-instruct',
|
||||
|
||||
# NousResearch
|
||||
'deepseek-math-7b-instruct',
|
||||
'Nous-Hermes-2-Mixtral-8x7B-DPO',
|
||||
'hermes-2-pro-mistral-7b',
|
||||
|
||||
# teknium
|
||||
'openhermes-2.5-mistral-7b',
|
||||
|
||||
# microsoft
|
||||
'WizardLM-2-8x22B',
|
||||
'phi-2',
|
||||
|
||||
# upstage
|
||||
'SOLAR-10.7B-Instruct-v1.0',
|
||||
|
||||
# pawan
|
||||
'cosmosrp',
|
||||
|
||||
# liquid
|
||||
'lfm-40b-moe',
|
||||
|
||||
# DiscoResearch
|
||||
'discolm-german-7b-v1',
|
||||
|
||||
# tiiuae
|
||||
'falcon-7b-instruct',
|
||||
|
||||
# defog
|
||||
'sqlcoder-7b-2',
|
||||
|
||||
# tinyllama
|
||||
'tinyllama-1.1b-chat',
|
||||
|
||||
# HuggingFaceH4
|
||||
'zephyr-7b-beta',
|
||||
]
|
||||
|
||||
models = [*text_models]
|
||||
|
||||
model_aliases = {
|
||||
# anthropic
|
||||
"claude-3-haiku": "claude-3-haiku-20240307",
|
||||
"claude-3-sonnet": "claude-3-sonnet-20240229",
|
||||
"claude-3.5-sonnet": "claude-3-5-sonnet-20240620",
|
||||
"claude-3.5-sonnet": "claude-3-5-sonnet-20241022",
|
||||
"claude-3-opus": "claude-3-opus-20240229",
|
||||
|
||||
# openai
|
||||
"gpt-4o": "chatgpt-4o-latest",
|
||||
#"gpt-4": "gpt-4",
|
||||
#"gpt-4-turbo": "gpt-4-turbo",
|
||||
"gpt-4o": "gpt-4o-2024-05-13",
|
||||
"gpt-4o-mini": "gpt-4o-mini-2024-07-18",
|
||||
#"gpt-4o-mini": "gpt-4o-mini",
|
||||
"gpt-4o": "gpt-4o-2024-08-06",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-0125",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-1106",
|
||||
#"gpt-4o": "gpt-4o",
|
||||
"gpt-4-turbo": "gpt-4-turbo-2024-04-09",
|
||||
"gpt-4": "gpt-4-0125-preview",
|
||||
"gpt-4": "gpt-4-1106-preview",
|
||||
|
||||
# meta-llama
|
||||
"llama-3-70b": "llama-3-70b-chat",
|
||||
"llama-3-8b": "llama-3-8b-chat",
|
||||
"llama-3-8b": "llama-3-8b-chat-turbo",
|
||||
"llama-3-70b": "llama-3-70b-chat-lite",
|
||||
"llama-3-8b": "llama-3-8b-chat-lite",
|
||||
"llama-2-13b": "llama-2-13b-chat",
|
||||
"llama-3.1-405b": "llama-3.1-405b-turbo",
|
||||
"llama-3.1-70b": "llama-3.1-70b-turbo",
|
||||
"llama-3.1-8b": "llama-3.1-8b-turbo",
|
||||
"llamaguard-2-8b": "LlamaGuard-2-8b",
|
||||
"llamaguard-7b": "llamaguard-7b",
|
||||
#"llama_vision_free": "Llama-Vision-Free", # Unknown
|
||||
"llamaguard-7b": "Llama-Guard-7b",
|
||||
"llama-3.2-90b": "Llama-3.2-90B-Vision-Instruct-Turbo",
|
||||
"llamaguard-3-8b": "Meta-Llama-Guard-3-8B",
|
||||
"llama-3.2-11b": "Llama-3.2-11B-Vision-Instruct-Turbo",
|
||||
"llamaguard-3-11b": "Llama-Guard-3-11B-Vision-Turbo",
|
||||
"llama-3.2-3b": "Llama-3.2-3B-Instruct-Turbo",
|
||||
"llama-3.2-1b": "Llama-3.2-1B-Instruct-Turbo",
|
||||
"llama-2-7b": "llama-2-7b-chat-int8",
|
||||
"llama-2-7b": "llama-2-7b-chat-fp16",
|
||||
"llama-3.1-405b": "Llama 3.1 405B Instruct",
|
||||
"llama-3.1-70b": "Llama 3.1 70B Instruct",
|
||||
"llama-3.1-8b": "Llama 3.1 8B Instruct",
|
||||
|
||||
# mistral-ai
|
||||
"mixtral-8x7b": "Mixtral-8x7B-Instruct-v0.1",
|
||||
"mixtral-8x22b": "Mixtral-8x22B-Instruct-v0.1",
|
||||
"mixtral-8x7b": "Mistral-7B-Instruct-v0.1",
|
||||
"mixtral-8x7b": "Mistral-7B-Instruct-v0.2",
|
||||
"mixtral-8x7b": "Mistral-7B-Instruct-v0.3",
|
||||
|
||||
# Gryphe
|
||||
"mythomax-13b": "MythoMax-L2-13b-Lite",
|
||||
"mythomax-13b": "MythoMax-L2-13b",
|
||||
|
||||
# openchat
|
||||
"openchat-3.5": "openchat-3.5-0106",
|
||||
|
||||
# qwen
|
||||
#"qwen-1.5-72b": "Qwen1.5-72B-Chat", # Empty answer
|
||||
#"qwen-1.5-110b": "Qwen1.5-110B-Chat", # Empty answer
|
||||
"qwen-2-72b": "Qwen2-72B-Instruct",
|
||||
"qwen-2-5-7b": "Qwen2.5-7B-Instruct-Turbo",
|
||||
"qwen-2-5-72b": "Qwen2.5-72B-Instruct-Turbo",
|
||||
|
||||
# google
|
||||
"gemma-2b": "gemma-2b-it",
|
||||
"gemma-2-9b": "gemma-2-9b-it",
|
||||
"gemma-2b-27b": "gemma-2-27b-it",
|
||||
|
||||
# gemini
|
||||
"gemini-flash": "gemini-1.5-flash",
|
||||
"gemini-pro": "gemini-1.5-pro",
|
||||
|
||||
# databricks
|
||||
"dbrx-instruct": "dbrx-instruct",
|
||||
|
||||
# deepseek-ai
|
||||
#"deepseek-coder": "deepseek-coder-6.7b-base",
|
||||
"deepseek-coder": "deepseek-coder-6.7b-instruct",
|
||||
#"deepseek-math": "deepseek-math-7b-instruct",
|
||||
|
||||
# NousResearch
|
||||
#"deepseek-math": "deepseek-math-7b-instruct",
|
||||
"hermes-2-dpo": "Nous-Hermes-2-Mixtral-8x7B-DPO",
|
||||
"hermes-2": "hermes-2-pro-mistral-7b",
|
||||
|
||||
# teknium
|
||||
"openhermes-2.5": "openhermes-2.5-mistral-7b",
|
||||
|
||||
# microsoft
|
||||
"wizardlm-2-8x22b": "WizardLM-2-8x22B",
|
||||
#"phi-2": "phi-2",
|
||||
|
||||
# upstage
|
||||
"solar-10-7b": "SOLAR-10.7B-Instruct-v1.0",
|
||||
|
||||
# pawan
|
||||
#"cosmosrp": "cosmosrp",
|
||||
|
||||
# liquid
|
||||
"lfm-40b": "lfm-40b-moe",
|
||||
|
||||
# DiscoResearch
|
||||
"german-7b": "discolm-german-7b-v1",
|
||||
|
||||
# tiiuae
|
||||
#"falcon-7b": "falcon-7b-instruct",
|
||||
|
||||
# defog
|
||||
#"sqlcoder-7b": "sqlcoder-7b-2",
|
||||
|
||||
# tinyllama
|
||||
#"tinyllama-1b": "tinyllama-1.1b-chat",
|
||||
|
||||
# HuggingFaceH4
|
||||
"zephyr-7b": "zephyr-7b-beta",
|
||||
}
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
stream: bool = False,
|
||||
proxy: str = None,
|
||||
max_tokens: str = 4096,
|
||||
temperature: str = 1,
|
||||
top_p: str = 1,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
chunked_messages = split_messages(messages)
|
||||
|
||||
headers = {
|
||||
'accept': '*/*',
|
||||
'accept-language': 'en-US,en;q=0.9',
|
||||
'authorization': 'Bearer missing api key',
|
||||
'cache-control': 'no-cache',
|
||||
'content-type': 'application/json',
|
||||
'origin': 'https://llmplayground.net',
|
||||
'pragma': 'no-cache',
|
||||
'priority': 'u=1, i',
|
||||
'referer': 'https://llmplayground.net/',
|
||||
'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': 'cross-site',
|
||||
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36'
|
||||
}
|
||||
|
||||
data = {
|
||||
"messages": chunked_messages,
|
||||
"model": model,
|
||||
"max_tokens": max_tokens,
|
||||
"temperature": temperature,
|
||||
"top_p": top_p,
|
||||
"stream": stream
|
||||
}
|
||||
|
||||
async with ClientSession(headers=headers) as session:
|
||||
async with session.post(cls.api_endpoint_completions, json=data, proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
text = ""
|
||||
if stream:
|
||||
async for line in response.content:
|
||||
line = line.decode('utf-8')
|
||||
if line.startswith('data: '):
|
||||
json_str = line[6:]
|
||||
try:
|
||||
chunk = json.loads(json_str)
|
||||
if 'choices' in chunk and chunk['choices']:
|
||||
content = chunk['choices'][0].get('delta', {}).get('content', '')
|
||||
text += content # Збираємо дельти
|
||||
except json.JSONDecodeError as e:
|
||||
print(f"Error decoding JSON: {json_str}, Error: {e}")
|
||||
elif line.strip() == "[DONE]":
|
||||
break
|
||||
yield clean_response(text)
|
||||
else:
|
||||
response_json = await response.json()
|
||||
text = response_json["choices"][0]["message"]["content"]
|
||||
yield clean_response(text)
|
||||
|
||||
97
g4f/Provider/airforce/AirforceImage.py
Normal file
97
g4f/Provider/airforce/AirforceImage.py
Normal file
@ -0,0 +1,97 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from aiohttp import ClientSession
|
||||
import random
|
||||
|
||||
from ...typing import AsyncResult, Messages
|
||||
from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
|
||||
from ...image import ImageResponse
|
||||
|
||||
|
||||
class AirforceImage(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
label = "Airforce Image"
|
||||
#url = "https://api.airforce"
|
||||
api_endpoint_imagine2 = "https://api.airforce/imagine2"
|
||||
#working = True
|
||||
|
||||
default_model = 'flux'
|
||||
image_models = [
|
||||
'flux',
|
||||
'flux-realism',
|
||||
'flux-anime',
|
||||
'flux-3d',
|
||||
'flux-disney',
|
||||
'flux-pixel',
|
||||
'flux-4o',
|
||||
'any-dark',
|
||||
'stable-diffusion-xl-base',
|
||||
'stable-diffusion-xl-lightning',
|
||||
]
|
||||
models = [*image_models]
|
||||
|
||||
model_aliases = {
|
||||
"sdxl": "stable-diffusion-xl-base",
|
||||
"sdxl": "stable-diffusion-xl-lightning",
|
||||
}
|
||||
|
||||
|
||||
@classmethod
|
||||
def get_model(cls, model: str) -> str:
|
||||
if model in cls.models:
|
||||
return model
|
||||
elif model in cls.model_aliases:
|
||||
return cls.model_aliases[model]
|
||||
else:
|
||||
return cls.default_model
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
size: str = '1:1',
|
||||
proxy: str = None,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
headers = {
|
||||
'accept': '*/*',
|
||||
'accept-language': 'en-US,en;q=0.9',
|
||||
'authorization': 'Bearer missing api key',
|
||||
'cache-control': 'no-cache',
|
||||
'origin': 'https://llmplayground.net',
|
||||
'pragma': 'no-cache',
|
||||
'priority': 'u=1, i',
|
||||
'referer': 'https://llmplayground.net/',
|
||||
'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': 'cross-site',
|
||||
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36'
|
||||
}
|
||||
|
||||
async with ClientSession(headers=headers) as session:
|
||||
prompt = messages[-1]['content']
|
||||
seed = random.randint(0, 4294967295)
|
||||
params = {
|
||||
'model': model,
|
||||
'prompt': prompt,
|
||||
'size': size,
|
||||
'seed': str(seed)
|
||||
}
|
||||
async with session.get(cls.api_endpoint_imagine2, params=params, proxy=proxy) as response:
|
||||
response.raise_for_status()
|
||||
if response.status == 200:
|
||||
content_type = response.headers.get('Content-Type', '')
|
||||
if 'image' in content_type:
|
||||
image_url = str(response.url)
|
||||
yield ImageResponse(image_url, alt="Airforce generated image")
|
||||
else:
|
||||
content = await response.text()
|
||||
yield f"Unexpected content type: {content_type}\nResponse content: {content}"
|
||||
else:
|
||||
error_content = await response.text()
|
||||
yield f"Error: {error_content}"
|
||||
2
g4f/Provider/airforce/__init__.py
Normal file
2
g4f/Provider/airforce/__init__.py
Normal file
@ -0,0 +1,2 @@
|
||||
from .AirforceChat import AirforceChat
|
||||
from .AirforceImage import AirforceImage
|
||||
251
g4f/models.py
251
g4f/models.py
@ -130,7 +130,7 @@ gpt_3 = Model(
|
||||
gpt_35_turbo = Model(
|
||||
name = 'gpt-3.5-turbo',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([Allyfy, NexraChatGPT, Airforce, DarkAI, Liaobots])
|
||||
best_provider = IterListProvider([Allyfy, NexraChatGPT, DarkAI, Airforce, Liaobots])
|
||||
)
|
||||
|
||||
# gpt-4
|
||||
@ -191,7 +191,7 @@ meta = Model(
|
||||
llama_2_7b = Model(
|
||||
name = "llama-2-7b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = Cloudflare
|
||||
best_provider = IterListProvider([Cloudflare, Airforce])
|
||||
)
|
||||
|
||||
llama_2_13b = Model(
|
||||
@ -217,13 +217,13 @@ llama_3_70b = Model(
|
||||
llama_3_1_8b = Model(
|
||||
name = "llama-3.1-8b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, Airforce, GizAI, PerplexityLabs])
|
||||
best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, GizAI, Airforce, PerplexityLabs])
|
||||
)
|
||||
|
||||
llama_3_1_70b = Model(
|
||||
name = "llama-3.1-70b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, DarkAI, Airforce, AiMathGPT, RubiksAI, GizAI, HuggingFace, PerplexityLabs])
|
||||
best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, DarkAI, AiMathGPT, RubiksAI, GizAI, Airforce, HuggingFace, PerplexityLabs])
|
||||
)
|
||||
|
||||
llama_3_1_405b = Model(
|
||||
@ -236,19 +236,19 @@ llama_3_1_405b = Model(
|
||||
llama_3_2_1b = Model(
|
||||
name = "llama-3.2-1b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = Cloudflare
|
||||
best_provider = IterListProvider([Cloudflare, Airforce])
|
||||
)
|
||||
|
||||
llama_3_2_3b = Model(
|
||||
name = "llama-3.2-3b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = Cloudflare
|
||||
best_provider = IterListProvider([Cloudflare, Airforce])
|
||||
)
|
||||
|
||||
llama_3_2_11b = Model(
|
||||
name = "llama-3.2-11b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([Cloudflare, HuggingChat, HuggingFace])
|
||||
best_provider = IterListProvider([Cloudflare, HuggingChat, Airforce, HuggingFace])
|
||||
)
|
||||
|
||||
llama_3_2_90b = Model(
|
||||
@ -271,6 +271,18 @@ llamaguard_2_8b = Model(
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
llamaguard_3_8b = Model(
|
||||
name = "llamaguard-3-8b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
llamaguard_3_11b = Model(
|
||||
name = "llamaguard-3-11b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
|
||||
### Mistral ###
|
||||
mistral_7b = Model(
|
||||
@ -305,14 +317,14 @@ mistral_large = Model(
|
||||
|
||||
|
||||
### NousResearch ###
|
||||
mixtral_8x7b_dpo = Model(
|
||||
name = "mixtral-8x7b-dpo",
|
||||
hermes_2 = Model(
|
||||
name = "hermes-2",
|
||||
base_provider = "NousResearch",
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
yi_34b = Model(
|
||||
name = "yi-34b",
|
||||
hermes_2_dpo = Model(
|
||||
name = "hermes-2-dpo",
|
||||
base_provider = "NousResearch",
|
||||
best_provider = Airforce
|
||||
)
|
||||
@ -328,7 +340,7 @@ hermes_3 = Model(
|
||||
phi_2 = Model(
|
||||
name = "phi-2",
|
||||
base_provider = "Microsoft",
|
||||
best_provider = Cloudflare
|
||||
best_provider = IterListProvider([Cloudflare, Airforce])
|
||||
)
|
||||
|
||||
phi_3_medium_4k = Model(
|
||||
@ -364,10 +376,10 @@ gemini = Model(
|
||||
)
|
||||
|
||||
# gemma
|
||||
gemma_2b_9b = Model(
|
||||
name = 'gemma-2b-9b',
|
||||
gemma_2b = Model(
|
||||
name = 'gemma-2b',
|
||||
base_provider = 'Google',
|
||||
best_provider = Airforce
|
||||
best_provider = IterListProvider([ReplicateHome, Airforce])
|
||||
)
|
||||
|
||||
gemma_2b_27b = Model(
|
||||
@ -376,12 +388,6 @@ gemma_2b_27b = Model(
|
||||
best_provider = IterListProvider([DeepInfraChat, Airforce])
|
||||
)
|
||||
|
||||
gemma_2b = Model(
|
||||
name = 'gemma-2b',
|
||||
base_provider = 'Google',
|
||||
best_provider = IterListProvider([ReplicateHome, Airforce])
|
||||
)
|
||||
|
||||
gemma_7b = Model(
|
||||
name = 'gemma-7b',
|
||||
base_provider = 'Google',
|
||||
@ -389,18 +395,18 @@ gemma_7b = Model(
|
||||
)
|
||||
|
||||
# gemma 2
|
||||
gemma_2_27b = Model(
|
||||
name = 'gemma-2-27b',
|
||||
base_provider = 'Google',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
gemma_2 = Model(
|
||||
name = 'gemma-2',
|
||||
base_provider = 'Google',
|
||||
best_provider = ChatHub
|
||||
)
|
||||
|
||||
gemma_2_9b = Model(
|
||||
name = 'gemma-2-9b',
|
||||
base_provider = 'Google',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
|
||||
### Anthropic ###
|
||||
claude_2_1 = Model(
|
||||
@ -413,26 +419,26 @@ claude_2_1 = Model(
|
||||
claude_3_opus = Model(
|
||||
name = 'claude-3-opus',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([Airforce, Liaobots])
|
||||
best_provider = IterListProvider([Liaobots])
|
||||
)
|
||||
|
||||
claude_3_sonnet = Model(
|
||||
name = 'claude-3-sonnet',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([Airforce, Liaobots])
|
||||
best_provider = IterListProvider([Liaobots])
|
||||
)
|
||||
|
||||
claude_3_haiku = Model(
|
||||
name = 'claude-3-haiku',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([DDG, Airforce, GizAI, Liaobots])
|
||||
best_provider = IterListProvider([DDG, GizAI, Liaobots])
|
||||
)
|
||||
|
||||
# claude 3.5
|
||||
claude_3_5_sonnet = Model(
|
||||
name = 'claude-3.5-sonnet',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([Blackbox, Editee, AmigoChat, Airforce, GizAI, Liaobots])
|
||||
best_provider = IterListProvider([Blackbox, Editee, AmigoChat, GizAI, Liaobots])
|
||||
)
|
||||
|
||||
|
||||
@ -493,31 +499,13 @@ qwen_1_5_0_5b = Model(
|
||||
qwen_1_5_7b = Model(
|
||||
name = 'qwen-1.5-7b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = IterListProvider([Cloudflare, Airforce])
|
||||
best_provider = IterListProvider([Cloudflare])
|
||||
)
|
||||
|
||||
qwen_1_5_14b = Model(
|
||||
name = 'qwen-1.5-14b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = IterListProvider([FreeChatgpt, Cloudflare, Airforce])
|
||||
)
|
||||
|
||||
qwen_1_5_72b = Model(
|
||||
name = 'qwen-1.5-72b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
qwen_1_5_110b = Model(
|
||||
name = 'qwen-1.5-110b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
qwen_1_5_1_8b = Model(
|
||||
name = 'qwen-1.5-1.8b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = Airforce
|
||||
best_provider = IterListProvider([FreeChatgpt, Cloudflare])
|
||||
)
|
||||
|
||||
# qwen 2
|
||||
@ -527,6 +515,18 @@ qwen_2_72b = Model(
|
||||
best_provider = IterListProvider([DeepInfraChat, HuggingChat, Airforce, HuggingFace])
|
||||
)
|
||||
|
||||
qwen_2_5_7b = Model(
|
||||
name = 'qwen-2-5-7b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
qwen_2_5_72b = Model(
|
||||
name = 'qwen-2-5-72b',
|
||||
base_provider = 'Qwen',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
qwen = Model(
|
||||
name = 'qwen',
|
||||
base_provider = 'Qwen',
|
||||
@ -556,18 +556,18 @@ yi_1_5_9b = Model(
|
||||
)
|
||||
|
||||
### Upstage ###
|
||||
solar_1_mini = Model(
|
||||
name = 'solar-1-mini',
|
||||
base_provider = 'Upstage',
|
||||
best_provider = Upstage
|
||||
)
|
||||
|
||||
solar_10_7b = Model(
|
||||
name = 'solar-10-7b',
|
||||
base_provider = 'Upstage',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
solar_mini = Model(
|
||||
name = 'solar-mini',
|
||||
base_provider = 'Upstage',
|
||||
best_provider = Upstage
|
||||
)
|
||||
|
||||
solar_pro = Model(
|
||||
name = 'solar-pro',
|
||||
base_provider = 'Upstage',
|
||||
@ -583,8 +583,8 @@ pi = Model(
|
||||
)
|
||||
|
||||
### DeepSeek ###
|
||||
deepseek = Model(
|
||||
name = 'deepseek',
|
||||
deepseek_coder = Model(
|
||||
name = 'deepseek-coder',
|
||||
base_provider = 'DeepSeek',
|
||||
best_provider = Airforce
|
||||
)
|
||||
@ -630,7 +630,7 @@ lzlv_70b = Model(
|
||||
openchat_3_5 = Model(
|
||||
name = 'openchat-3.5',
|
||||
base_provider = 'OpenChat',
|
||||
best_provider = Cloudflare
|
||||
best_provider = IterListProvider([Cloudflare])
|
||||
)
|
||||
|
||||
openchat_3_6_8b = Model(
|
||||
@ -683,11 +683,34 @@ sonar_chat = Model(
|
||||
best_provider = PerplexityLabs
|
||||
)
|
||||
|
||||
### TheBloke ###
|
||||
german_7b = Model(
|
||||
name = 'german-7b',
|
||||
base_provider = 'TheBloke',
|
||||
best_provider = Cloudflare
|
||||
)
|
||||
|
||||
### Gryphe ###
|
||||
mythomax_l2_13b = Model(
|
||||
name = 'mythomax-l2-13b',
|
||||
base_provider = 'Gryphe',
|
||||
|
||||
### Fblgit ###
|
||||
cybertron_7b = Model(
|
||||
name = 'cybertron-7b',
|
||||
base_provider = 'Fblgit',
|
||||
best_provider = Cloudflare
|
||||
)
|
||||
|
||||
|
||||
### Nvidia ###
|
||||
nemotron_70b = Model(
|
||||
name = 'nemotron-70b',
|
||||
base_provider = 'Nvidia',
|
||||
best_provider = IterListProvider([HuggingChat, HuggingFace])
|
||||
)
|
||||
|
||||
|
||||
### Teknium ###
|
||||
openhermes_2_5 = Model(
|
||||
name = 'openhermes-2.5',
|
||||
base_provider = 'Teknium',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
@ -700,34 +723,27 @@ cosmosrp = Model(
|
||||
)
|
||||
|
||||
|
||||
### TheBloke ###
|
||||
### Liquid ###
|
||||
lfm_40b = Model(
|
||||
name = 'lfm-40b',
|
||||
base_provider = 'Liquid',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
|
||||
### DiscoResearch ###
|
||||
german_7b = Model(
|
||||
name = 'german-7b',
|
||||
base_provider = 'TheBloke',
|
||||
best_provider = Cloudflare
|
||||
base_provider = 'DiscoResearch',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
|
||||
### Tinyllama ###
|
||||
tinyllama_1_1b = Model(
|
||||
name = 'tinyllama-1.1b',
|
||||
base_provider = 'Tinyllama',
|
||||
best_provider = Cloudflare
|
||||
)
|
||||
|
||||
|
||||
### Fblgit ###
|
||||
cybertron_7b = Model(
|
||||
name = 'cybertron-7b',
|
||||
base_provider = 'Fblgit',
|
||||
best_provider = Cloudflare
|
||||
)
|
||||
|
||||
### Nvidia ###
|
||||
nemotron_70b = Model(
|
||||
name = 'nemotron-70b',
|
||||
base_provider = 'Nvidia',
|
||||
best_provider = IterListProvider([HuggingChat, HuggingFace])
|
||||
### HuggingFaceH4 ###
|
||||
zephyr_7b = Model(
|
||||
name = 'zephyr-7b',
|
||||
base_provider = 'HuggingFaceH4',
|
||||
best_provider = Airforce
|
||||
)
|
||||
|
||||
|
||||
@ -754,7 +770,7 @@ sdxl_lora = Model(
|
||||
sdxl = Model(
|
||||
name = 'sdxl',
|
||||
base_provider = 'Stability AI',
|
||||
best_provider = IterListProvider([ReplicateHome])
|
||||
best_provider = IterListProvider([ReplicateHome, Airforce])
|
||||
|
||||
)
|
||||
|
||||
@ -947,6 +963,8 @@ class ModelUtils:
|
||||
# llamaguard
|
||||
'llamaguard-7b': llamaguard_7b,
|
||||
'llamaguard-2-8b': llamaguard_2_8b,
|
||||
'llamaguard-3-8b': llamaguard_3_8b,
|
||||
'llamaguard-3-11b': llamaguard_3_11b,
|
||||
|
||||
|
||||
### Mistral ###
|
||||
@ -958,17 +976,17 @@ class ModelUtils:
|
||||
|
||||
|
||||
### NousResearch ###
|
||||
'mixtral-8x7b-dpo': mixtral_8x7b_dpo,
|
||||
'hermes-2': hermes_2,
|
||||
'hermes-2-dpo': hermes_2_dpo,
|
||||
'hermes-3': hermes_3,
|
||||
|
||||
'yi-34b': yi_34b,
|
||||
|
||||
|
||||
|
||||
|
||||
### Microsoft ###
|
||||
'phi-2': phi_2,
|
||||
'phi_3_medium-4k': phi_3_medium_4k,
|
||||
'phi-3.5-mini': phi_3_5_mini,
|
||||
|
||||
|
||||
### Google ###
|
||||
# gemini
|
||||
'gemini': gemini,
|
||||
@ -977,13 +995,12 @@ class ModelUtils:
|
||||
|
||||
# gemma
|
||||
'gemma-2b': gemma_2b,
|
||||
'gemma-2b-9b': gemma_2b_9b,
|
||||
'gemma-2b-27b': gemma_2b_27b,
|
||||
'gemma-7b': gemma_7b,
|
||||
|
||||
# gemma-2
|
||||
'gemma-2': gemma_2,
|
||||
'gemma-2-27b': gemma_2_27b,
|
||||
'gemma-2-9b': gemma_2_9b,
|
||||
|
||||
|
||||
### Anthropic ###
|
||||
@ -1028,10 +1045,9 @@ class ModelUtils:
|
||||
'qwen-1.5-0.5b': qwen_1_5_0_5b,
|
||||
'qwen-1.5-7b': qwen_1_5_7b,
|
||||
'qwen-1.5-14b': qwen_1_5_14b,
|
||||
'qwen-1.5-72b': qwen_1_5_72b,
|
||||
'qwen-1.5-110b': qwen_1_5_110b,
|
||||
'qwen-1.5-1.8b': qwen_1_5_1_8b,
|
||||
'qwen-2-72b': qwen_2_72b,
|
||||
'qwen-2-5-7b': qwen_2_5_7b,
|
||||
'qwen-2-5-72b': qwen_2_5_72b,
|
||||
|
||||
|
||||
### Zhipu AI ###
|
||||
@ -1044,16 +1060,17 @@ class ModelUtils:
|
||||
|
||||
|
||||
### Upstage ###
|
||||
'solar-mini': solar_1_mini,
|
||||
'solar-10-7b': solar_10_7b,
|
||||
'solar-mini': solar_mini,
|
||||
'solar-pro': solar_pro,
|
||||
|
||||
|
||||
### Inflection ###
|
||||
'pi': pi,
|
||||
|
||||
|
||||
### DeepSeek ###
|
||||
'deepseek': deepseek,
|
||||
'deepseek-coder': deepseek_coder,
|
||||
|
||||
|
||||
### Yorickvp ###
|
||||
@ -1094,30 +1111,38 @@ class ModelUtils:
|
||||
### Perplexity AI ###
|
||||
'sonar-online': sonar_online,
|
||||
'sonar-chat': sonar_chat,
|
||||
|
||||
|
||||
### Gryphe ###
|
||||
'mythomax-l2-13b': sonar_chat,
|
||||
|
||||
|
||||
### Pawan ###
|
||||
'cosmosrp': cosmosrp,
|
||||
|
||||
|
||||
|
||||
### TheBloke ###
|
||||
'german-7b': german_7b,
|
||||
|
||||
|
||||
### Tinyllama ###
|
||||
'tinyllama-1.1b': tinyllama_1_1b,
|
||||
|
||||
|
||||
### Fblgit ###
|
||||
'cybertron-7b': cybertron_7b,
|
||||
|
||||
|
||||
### Nvidia ###
|
||||
'nemotron-70b': nemotron_70b,
|
||||
|
||||
|
||||
### Teknium ###
|
||||
'openhermes-2.5': openhermes_2_5,
|
||||
|
||||
|
||||
### Pawan ###
|
||||
'cosmosrp': cosmosrp,
|
||||
|
||||
|
||||
### Liquid ###
|
||||
'lfm-40b': lfm_40b,
|
||||
|
||||
|
||||
### DiscoResearch ###
|
||||
'german-7b': german_7b,
|
||||
|
||||
|
||||
### HuggingFaceH4 ###
|
||||
'zephyr-7b': zephyr_7b,
|
||||
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user