mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-12-25 12:16:17 +03:00
414 lines
15 KiB
Python
414 lines
15 KiB
Python
from __future__ import annotations
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import random
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import json
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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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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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working = True
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default_model = 'llama-3-70b-chat'
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supports_gpt_35_turbo = True
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supports_gpt_4 = 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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text_models = [
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# anthorpic
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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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# openai
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'chatgpt-4o-latest',
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'gpt-4',
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#'gpt-4-0613',
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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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#'gpt-3.5-turbo-16k', # No response from the API.
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#'gpt-3.5-turbo-0613', # No response from the API.
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#'gpt-3.5-turbo-16k-0613', # No response from the API.
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'gpt-4o',
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#'o1-mini', # No response from the API.
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# meta-llama
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'llama-3-70b-chat',
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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-2-70b-chat', # Failed to load response after multiple retries.
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'llama-2-13b-chat',
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#'llama-2-7b-chat', # Failed to load response after multiple retries.
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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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# codellama
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#'CodeLlama-7b-Python-hf', # Failed to load response after multiple retries.
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#'CodeLlama-7b-Python',
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#'CodeLlama-13b-Python-hf', # Failed to load response after multiple retries.
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#'CodeLlama-34b-Python-hf', # Failed to load response after multiple retries.
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#'CodeLlama-70b-Python-hf', # Failed to load response after multiple retries.
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# 01-ai
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#'Yi-34B-Chat', # Failed to load response after multiple retries.
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#'Yi-34B', # Failed to load response after multiple retries.
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#'Yi-6B', # Failed to load response after multiple retries.
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# mistral-ai
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#'Mixtral-8x7B-v0.1',
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#'Mixtral-8x22B', # Failed to load response after multiple retries.
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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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# openchat
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#'openchat-3.5', # Failed to load response after multiple retries.
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# wizardlm
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#'WizardLM-13B-V1.2', # Failed to load response after multiple retries.
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#'WizardCoder-Python-34B-V1.0', # Failed to load response after multiple retries.
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# qwen
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#'Qwen1.5-0.5B-Chat', # Failed to load response after multiple retries.
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#'Qwen1.5-1.8B-Chat', # Failed to load response after multiple retries.
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#'Qwen1.5-4B-Chat', # Failed to load response after multiple retries.
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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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# google
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'gemma-2b-it',
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#'gemma-7b-it', # Failed to load response after multiple retries.
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#'gemma-2b', # Failed to load response after multiple retries.
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#'gemma-7b', # Failed to load response after multiple retries.
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'gemma-2-9b-it', # fix bug
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'gemma-2-27b-it',
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# gemini
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'gemini-1.5-flash',
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'gemini-1.5-pro',
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# databricks
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'dbrx-instruct',
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# lmsys
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#'vicuna-7b-v1.5', # Failed to load response after multiple retries.
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#'vicuna-13b-v1.5', # Failed to load response after multiple retries.
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# cognitivecomputations
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#'dolphin-2.5-mixtral-8x7b', # Failed to load response after multiple retries.
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# deepseek-ai
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#'deepseek-coder-33b-instruct', # No response from the API.
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#'deepseek-coder-67b-instruct', # Failed to load response after multiple retries.
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'deepseek-llm-67b-chat',
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# NousResearch
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#'Nous-Capybara-7B-V1p9', # Failed to load response after multiple retries.
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'Nous-Hermes-2-Mixtral-8x7B-DPO',
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#'Nous-Hermes-2-Mixtral-8x7B-SFT', # Failed to load response after multiple retries.
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#'Nous-Hermes-llama-2-7b', # Failed to load response after multiple retries.
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#'Nous-Hermes-Llama2-13b', # Failed to load response after multiple retries.
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'Nous-Hermes-2-Yi-34B',
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# Open-Orca
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#'Mistral-7B-OpenOrca', # Failed to load response after multiple retries.
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# togethercomputer
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#'alpaca-7b', # Failed to load response after multiple retries.
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# teknium
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#'OpenHermes-2-Mistral-7B', # Failed to load response after multiple retries.
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#'OpenHermes-2.5-Mistral-7B', # Failed to load response after multiple retries.
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# microsoft
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'WizardLM-2-8x22B',
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# Nexusflow
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#'NexusRaven-V2-13B', # Failed to load response after multiple retries.
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# Phind
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#'Phind-CodeLlama-34B-v2', # Failed to load response after multiple retries.
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# Snoflake
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#'snowflake-arctic-instruct', # No response from the API.
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# upstage
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'SOLAR-10.7B-Instruct-v1.0',
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# togethercomputer
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#'StripedHyena-Hessian-7B', # Failed to load response after multiple retries.
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#'StripedHyena-Nous-7B', # Failed to load response after multiple retries.
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#'Llama-2-7B-32K-Instruct', # Failed to load response after multiple retries.
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#'CodeLlama-13b-Instruct', # No response from the API.
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#'evo-1-131k-base', # Failed to load response after multiple retries.
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#'OLMo-7B-Instruct', # Failed to load response after multiple retries.
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# garage-bAInd
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#'Platypus2-70B-instruct', # Failed to load response after multiple retries.
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# snorkelai
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#'Snorkel-Mistral-PairRM-DPO', # Failed to load response after multiple retries.
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# Undi95
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#'ReMM-SLERP-L2-13B', # Failed to load response after multiple retries.
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# Gryphe
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'MythoMax-L2-13b',
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# Autism
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#'chronos-hermes-13b', # Failed to load response after multiple retries.
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# Undi95
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#'Toppy-M-7B', # Failed to load response after multiple retries.
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# iFlytek
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#'sparkdesk', # Failed to load response after multiple retries.
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# pawan
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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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'dall-e-3',
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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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model_aliases = {
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# anthorpic
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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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"claude-3-5-sonnet": "claude-3-5-sonnet-20240620",
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"claude-3-opus": "claude-3-opus-20240229",
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# openai
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"gpt-4o": "chatgpt-4o-latest",
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"gpt-4o-mini": "gpt-4o-mini-2024-07-18",
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"gpt-3.5-turbo": "gpt-3.5-turbo-0125",
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"gpt-3.5-turbo": "gpt-3.5-turbo-1106",
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# meta-llama
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"llama-3-70b": "llama-3-70b-chat",
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"llama-3-70b": "llama-3-70b-chat-turbo",
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"llama-3-8b": "llama-3-8b-chat",
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"llama-3-8b": "llama-3-8b-chat-turbo",
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"llama-3-70b": "llama-3-70b-chat-lite",
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"llama-3-8b": "llama-3-8b-chat-lite",
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"llama-2-13b": "llama-2-13b-chat",
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"llama-3.1-405b": "llama-3.1-405b-turbo",
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"llama-3.1-70b": "llama-3.1-70b-turbo",
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"llama-3.1-8b": "llama-3.1-8b-turbo",
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"llamaguard-2-8b": "LlamaGuard-2-8b",
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"llamaguard-7b": "Llama-Guard-7b",
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"llama-3.2-90b": "Llama-3.2-90B-Vision-Instruct-Turbo",
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# mistral-ai
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"mixtral-8x7b": "Mixtral-8x7B-Instruct-v0.1",
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"mixtral-8x22b": "Mixtral-8x22B-Instruct-v0.1",
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"mistral-7b": "Mistral-7B-Instruct-v0.1",
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"mistral-7b": "Mistral-7B-Instruct-v0.2",
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"mistral-7b": "Mistral-7B-Instruct-v0.3",
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# qwen
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"qwen-1.5-7b": "Qwen1.5-7B-Chat",
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"qwen-1.5-14b": "Qwen1.5-14B-Chat",
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"qwen-1.5-72b": "Qwen1.5-72B-Chat",
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"qwen-1.5-110b": "Qwen1.5-110B-Chat",
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"qwen-2-72b": "Qwen2-72B-Instruct",
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# google
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"gemma-2b": "gemma-2b-it",
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"gemma-2-9b": "gemma-2-9b-it",
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"gemma-2-27b": "gemma-2-27b-it",
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# gemini
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"gemini-flash": "gemini-1.5-flash",
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"gemini-pro": "gemini-1.5-pro",
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# deepseek-ai
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"deepseek": "deepseek-llm-67b-chat",
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# NousResearch
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"mixtral-8x7b-dpo": "Nous-Hermes-2-Mixtral-8x7B-DPO",
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"yi-34b": "Nous-Hermes-2-Yi-34B",
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# microsoft
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"wizardlm-2-8x22b": "WizardLM-2-8x22B",
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# upstage
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"solar-10.7b": "SOLAR-10.7B-Instruct-v1.0",
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# Gryphe
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"mythomax-l2-13b": "MythoMax-L2-13b",
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}
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@classmethod
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def get_model(cls, model: str) -> str:
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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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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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model = cls.get_model(model)
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# If the model is an image model, use the image API
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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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# If the model is a text model, use the text API
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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 seed is None:
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seed = random.randint(0, 100000)
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# Assume the first message is the prompt for the image
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prompt = messages[0]['content']
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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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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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"""Formats messages for text generation."""
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return " ".join([msg['content'] for msg in messages])
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