from __future__ import annotations
from dataclasses import dataclass
from .Provider import IterListProvider, ProviderType
from .Provider import (
AIChatFree,
Airforce,
Allyfy,
AmigoChat,
Bing,
Blackbox,
ChatGpt,
Chatgpt4Online,
ChatGptEs,
ChatgptFree,
ChatHub,
ChatifyAI,
Cloudflare,
DarkAI,
DDG,
DeepInfra,
DeepInfraChat,
DeepInfraImage,
Free2GPT,
FreeChatgpt,
FreeGpt,
FreeNetfly,
Gemini,
GeminiPro,
GigaChat,
GPROChat,
HuggingChat,
HuggingFace,
Koala,
Liaobots,
MagickPen,
MetaAI,
NexraBlackbox,
NexraChatGPT,
NexraChatGPT4o,
NexraChatGptV2,
NexraChatGptWeb,
NexraDallE,
NexraDallE2,
NexraDalleMini,
NexraEmi,
NexraFluxPro,
NexraLLaMA31,
NexraQwen,
OpenaiChat,
PerplexityLabs,
Pi,
Pizzagpt,
Reka,
Replicate,
ReplicateHome,
TeachAnything,
Upstage,
)
@dataclass(unsafe_hash=True)
class Model:
"""
Represents a machine learning model configuration.
Attributes:
name (str): Name of the model.
base_provider (str): Default provider for the model.
best_provider (ProviderType): The preferred provider for the model, typically with retry logic.
"""
name: str
base_provider: str
best_provider: ProviderType = None
@staticmethod
def __all__() -> list[str]:
"""Returns a list of all model names."""
return _all_models
default = Model(
name = "",
base_provider = "",
best_provider = IterListProvider([
DDG,
FreeChatgpt,
HuggingChat,
Pizzagpt,
ReplicateHome,
Upstage,
Blackbox,
Free2GPT,
MagickPen,
DeepInfraChat,
Airforce,
ChatHub,
ChatGptEs,
ChatHub,
AmigoChat,
ChatifyAI,
Cloudflare,
])
)
############
### Text ###
############
### OpenAI ###
# gpt-3
gpt_3 = Model(
name = 'gpt-3',
base_provider = 'OpenAI',
best_provider = NexraChatGPT
)
# gpt-3.5
gpt_35_turbo = Model(
name = 'gpt-3.5-turbo',
base_provider = 'OpenAI',
best_provider = IterListProvider([Allyfy, NexraChatGPT, Airforce, DarkAI, Liaobots])
)
# gpt-4
gpt_4o = Model(
name = 'gpt-4o',
base_provider = 'OpenAI',
best_provider = IterListProvider([NexraChatGPT4o, ChatGptEs, AmigoChat, DarkAI, Liaobots, Airforce, OpenaiChat])
)
gpt_4o_mini = Model(
name = 'gpt-4o-mini',
base_provider = 'OpenAI',
best_provider = IterListProvider([DDG, ChatGptEs, FreeNetfly, Pizzagpt, MagickPen, AmigoChat, Liaobots, Airforce, ChatgptFree, Koala, OpenaiChat, ChatGpt])
)
gpt_4_turbo = Model(
name = 'gpt-4-turbo',
base_provider = 'OpenAI',
best_provider = IterListProvider([Liaobots, Airforce, Bing])
)
gpt_4 = Model(
name = 'gpt-4',
base_provider = 'OpenAI',
best_provider = IterListProvider([NexraChatGPT, NexraChatGptV2, NexraChatGptWeb, Airforce, Chatgpt4Online, Bing, OpenaiChat])
)
# o1
o1 = Model(
name = 'o1',
base_provider = 'OpenAI',
best_provider = AmigoChat
)
o1_mini = Model(
name = 'o1-mini',
base_provider = 'OpenAI',
best_provider = AmigoChat
)
### GigaChat ###
gigachat = Model(
name = 'GigaChat:latest',
base_provider = 'gigachat',
best_provider = GigaChat
)
### Meta ###
meta = Model(
name = "meta-ai",
base_provider = "Meta",
best_provider = MetaAI
)
# llama 2
llama_2_7b = Model(
name = "llama-2-7b",
base_provider = "Meta Llama",
best_provider = Cloudflare
)
llama_2_13b = Model(
name = "llama-2-13b",
base_provider = "Meta Llama",
best_provider = Airforce
)
# llama 3
llama_3_8b = Model(
name = "llama-3-8b",
base_provider = "Meta Llama",
best_provider = IterListProvider([Cloudflare, Airforce, DeepInfra, Replicate])
)
llama_3_70b = Model(
name = "llama-3-70b",
base_provider = "Meta Llama",
best_provider = IterListProvider([ReplicateHome, Airforce, DeepInfra, Replicate])
)
# llama 3.1
llama_3_1_8b = Model(
name = "llama-3.1-8b",
base_provider = "Meta Llama",
best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, NexraLLaMA31, 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, HuggingFace, PerplexityLabs])
)
llama_3_1_405b = Model(
name = "llama-3.1-405b",
base_provider = "Meta Llama",
best_provider = IterListProvider([DeepInfraChat, Blackbox, AmigoChat, DarkAI, Airforce])
)
# llama 3.2
llama_3_2_1b = Model(
name = "llama-3.2-1b",
base_provider = "Meta Llama",
best_provider = Cloudflare
)
llama_3_2_3b = Model(
name = "llama-3.2-3b",
base_provider = "Meta Llama",
best_provider = Cloudflare
)
llama_3_2_11b = Model(
name = "llama-3.2-11b",
base_provider = "Meta Llama",
best_provider = IterListProvider([Cloudflare, HuggingChat, HuggingFace])
)
llama_3_2_90b = Model(
name = "llama-3.2-90b",
base_provider = "Meta Llama",
best_provider = IterListProvider([AmigoChat, Airforce])
)
# llamaguard
llamaguard_7b = Model(
name = "llamaguard-7b",
base_provider = "Meta Llama",
best_provider = Airforce
)
llamaguard_2_8b = Model(
name = "llamaguard-2-8b",
base_provider = "Meta Llama",
best_provider = Airforce
)
### Mistral ###
mistral_7b = Model(
name = "mistral-7b",
base_provider = "Mistral",
best_provider = IterListProvider([DeepInfraChat, Cloudflare, Airforce, DeepInfra])
)
mixtral_8x7b = Model(
name = "mixtral-8x7b",
base_provider = "Mistral",
best_provider = IterListProvider([DDG, ReplicateHome, DeepInfraChat, ChatHub, Airforce, DeepInfra])
)
mixtral_8x22b = Model(
name = "mixtral-8x22b",
base_provider = "Mistral",
best_provider = IterListProvider([DeepInfraChat, Airforce])
)
mistral_nemo = Model(
name = "mistral-nemo",
base_provider = "Mistral",
best_provider = IterListProvider([HuggingChat, HuggingFace])
)
### NousResearch ###
mixtral_8x7b_dpo = Model(
name = "mixtral-8x7b-dpo",
base_provider = "NousResearch",
best_provider = Airforce
)
yi_34b = Model(
name = "yi-34b",
base_provider = "NousResearch",
best_provider = Airforce
)
hermes_3 = Model(
name = "hermes-3",
base_provider = "NousResearch",
best_provider = IterListProvider([HuggingChat, HuggingFace])
)
### Microsoft ###
phi_2 = Model(
name = "phi-2",
base_provider = "Microsoft",
best_provider = Cloudflare
)
phi_3_medium_4k = Model(
name = "phi-3-medium-4k",
base_provider = "Microsoft",
best_provider = DeepInfraChat
)
phi_3_5_mini = Model(
name = "phi-3.5-mini",
base_provider = "Microsoft",
best_provider = IterListProvider([HuggingChat, HuggingFace])
)
### Google DeepMind ###
# gemini
gemini_pro = Model(
name = 'gemini-pro',
base_provider = 'Google DeepMind',
best_provider = IterListProvider([GeminiPro, Blackbox, AIChatFree, GPROChat, AmigoChat, Liaobots, Airforce])
)
gemini_flash = Model(
name = 'gemini-flash',
base_provider = 'Google DeepMind',
best_provider = IterListProvider([Blackbox, Liaobots, Airforce])
)
gemini = Model(
name = 'gemini',
base_provider = 'Google DeepMind',
best_provider = Gemini
)
# gemma
gemma_2b_9b = Model(
name = 'gemma-2b-9b',
base_provider = 'Google',
best_provider = Airforce
)
gemma_2b_27b = Model(
name = 'gemma-2b-27b',
base_provider = 'Google',
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',
best_provider = Cloudflare
)
# 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
)
### Anthropic ###
claude_2_1 = Model(
name = 'claude-2.1',
base_provider = 'Anthropic',
best_provider = Liaobots
)
# claude 3
claude_3_opus = Model(
name = 'claude-3-opus',
base_provider = 'Anthropic',
best_provider = IterListProvider([Airforce, Liaobots])
)
claude_3_sonnet = Model(
name = 'claude-3-sonnet',
base_provider = 'Anthropic',
best_provider = IterListProvider([Airforce, Liaobots])
)
claude_3_haiku = Model(
name = 'claude-3-haiku',
base_provider = 'Anthropic',
best_provider = IterListProvider([DDG, Airforce, Liaobots])
)
# claude 3.5
claude_3_5_sonnet = Model(
name = 'claude-3.5-sonnet',
base_provider = 'Anthropic',
best_provider = IterListProvider([Blackbox, Airforce, AmigoChat, Liaobots])
)
### Reka AI ###
reka_core = Model(
name = 'reka-core',
base_provider = 'Reka AI',
best_provider = Reka
)
### Blackbox AI ###
blackboxai = Model(
name = 'blackboxai',
base_provider = 'Blackbox AI',
best_provider = IterListProvider([Blackbox, NexraBlackbox])
)
blackboxai_pro = Model(
name = 'blackboxai-pro',
base_provider = 'Blackbox AI',
best_provider = Blackbox
)
### Databricks ###
dbrx_instruct = Model(
name = 'dbrx-instruct',
base_provider = 'Databricks',
best_provider = IterListProvider([Airforce, DeepInfra])
)
### CohereForAI ###
command_r_plus = Model(
name = 'command-r-plus',
base_provider = 'CohereForAI',
best_provider = HuggingChat
)
### iFlytek ###
sparkdesk_v1_1 = Model(
name = 'sparkdesk-v1.1',
base_provider = 'iFlytek',
best_provider = FreeChatgpt
)
### Qwen ###
# qwen 1
qwen_1_5_0_5b = Model(
name = 'qwen-1.5-0.5b',
base_provider = 'Qwen',
best_provider = Cloudflare
)
qwen_1_5_7b = Model(
name = 'qwen-1.5-7b',
base_provider = 'Qwen',
best_provider = IterListProvider([Cloudflare, Airforce])
)
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
)
# qwen 2
qwen_2_72b = Model(
name = 'qwen-2-72b',
base_provider = 'Qwen',
best_provider = IterListProvider([DeepInfraChat, HuggingChat, Airforce, HuggingFace])
)
qwen = Model(
name = 'qwen',
base_provider = 'Qwen',
best_provider = NexraQwen
)
### Zhipu AI ###
glm_3_6b = Model(
name = 'glm-3-6b',
base_provider = 'Zhipu AI',
best_provider = FreeChatgpt
)
glm_4_9b = Model(
name = 'glm-4-9B',
base_provider = 'Zhipu AI',
best_provider = FreeChatgpt
)
### 01-ai ###
yi_1_5_9b = Model(
name = 'yi-1.5-9b',
base_provider = '01-ai',
best_provider = FreeChatgpt
)
### 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_pro = Model(
name = 'solar-pro',
base_provider = 'Upstage',
best_provider = Upstage
)
### Inflection ###
pi = Model(
name = 'pi',
base_provider = 'Inflection',
best_provider = Pi
)
### DeepSeek ###
deepseek = Model(
name = 'deepseek',
base_provider = 'DeepSeek',
best_provider = Airforce
)
### WizardLM ###
wizardlm_2_7b = Model(
name = 'wizardlm-2-7b',
base_provider = 'WizardLM',
best_provider = DeepInfraChat
)
wizardlm_2_8x22b = Model(
name = 'wizardlm-2-8x22b',
base_provider = 'WizardLM',
best_provider = IterListProvider([DeepInfraChat, Airforce])
)
### Yorickvp ###
llava_13b = Model(
name = 'llava-13b',
base_provider = 'Yorickvp',
best_provider = ReplicateHome
)
### OpenBMB ###
minicpm_llama_3_v2_5 = Model(
name = 'minicpm-llama-3-v2.5',
base_provider = 'OpenBMB',
best_provider = DeepInfraChat
)
### Lzlv ###
lzlv_70b = Model(
name = 'lzlv-70b',
base_provider = 'Lzlv',
best_provider = DeepInfraChat
)
### OpenChat ###
openchat_3_5 = Model(
name = 'openchat-3.5',
base_provider = 'OpenChat',
best_provider = Cloudflare
)
openchat_3_6_8b = Model(
name = 'openchat-3.6-8b',
base_provider = 'OpenChat',
best_provider = DeepInfraChat
)
### Phind ###
phind_codellama_34b_v2 = Model(
name = 'phind-codellama-34b-v2',
base_provider = 'Phind',
best_provider = DeepInfraChat
)
### Cognitive Computations ###
dolphin_2_9_1_llama_3_70b = Model(
name = 'dolphin-2.9.1-llama-3-70b',
base_provider = 'Cognitive Computations',
best_provider = DeepInfraChat
)
### x.ai ###
grok_2 = Model(
name = 'grok-2',
base_provider = 'x.ai',
best_provider = Liaobots
)
grok_2_mini = Model(
name = 'grok-2-mini',
base_provider = 'x.ai',
best_provider = Liaobots
)
### Perplexity AI ###
sonar_online = Model(
name = 'sonar-online',
base_provider = 'Perplexity AI',
best_provider = IterListProvider([ChatHub, PerplexityLabs])
)
sonar_chat = Model(
name = 'sonar-chat',
base_provider = 'Perplexity AI',
best_provider = PerplexityLabs
)
### Gryphe ###
mythomax_l2_13b = Model(
name = 'mythomax-l2-13b',
base_provider = 'Gryphe',
best_provider = Airforce
)
### Pawan ###
cosmosrp = Model(
name = 'cosmosrp',
base_provider = 'Pawan',
best_provider = Airforce
)
### TheBloke ###
german_7b = Model(
name = 'german-7b',
base_provider = 'TheBloke',
best_provider = Cloudflare
)
### 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
)
#############
### Image ###
#############
### Stability AI ###
sdxl = Model(
name = 'sdxl',
base_provider = 'Stability AI',
best_provider = IterListProvider([ReplicateHome, DeepInfraImage])
)
sd_3 = Model(
name = 'sd-3',
base_provider = 'Stability AI',
best_provider = ReplicateHome
)
### Playground ###
playground_v2_5 = Model(
name = 'playground-v2.5',
base_provider = 'Playground AI',
best_provider = ReplicateHome
)
### Flux AI ###
flux = Model(
name = 'flux',
base_provider = 'Flux AI',
best_provider = IterListProvider([Airforce, Blackbox])
)
flux_pro = Model(
name = 'flux-pro',
base_provider = 'Flux AI',
best_provider = IterListProvider([NexraFluxPro, AmigoChat])
)
flux_realism = Model(
name = 'flux-realism',
base_provider = 'Flux AI',
best_provider = IterListProvider([Airforce, AmigoChat])
)
flux_anime = Model(
name = 'flux-anime',
base_provider = 'Flux AI',
best_provider = Airforce
)
flux_3d = Model(
name = 'flux-3d',
base_provider = 'Flux AI',
best_provider = Airforce
)
flux_disney = Model(
name = 'flux-disney',
base_provider = 'Flux AI',
best_provider = Airforce
)
flux_pixel = Model(
name = 'flux-pixel',
base_provider = 'Flux AI',
best_provider = Airforce
)
flux_4o = Model(
name = 'flux-4o',
base_provider = 'Flux AI',
best_provider = Airforce
)
flux_schnell = Model(
name = 'flux-schnell',
base_provider = 'Flux AI',
best_provider = ReplicateHome
)
### OpenAI ###
dalle_2 = Model(
name = 'dalle-2',
base_provider = 'OpenAI',
best_provider = NexraDallE2
)
dalle_3 = Model(
name = 'dalle-3',
base_provider = 'OpenAI',
best_provider = Airforce
)
dalle = Model(
name = 'dalle',
base_provider = 'OpenAI',
best_provider = NexraDallE
)
dalle_mini = Model(
name = 'dalle-mini',
base_provider = 'OpenAI',
best_provider = NexraDalleMini
)
### Other ###
emi = Model(
name = 'emi',
base_provider = '',
best_provider = NexraEmi
)
any_dark = Model(
name = 'any-dark',
base_provider = '',
best_provider = Airforce
)
class ModelUtils:
"""
Utility class for mapping string identifiers to Model instances.
Attributes:
convert (dict[str, Model]): Dictionary mapping model string identifiers to Model instances.
"""
convert: dict[str, Model] = {
############
### Text ###
############
### OpenAI ###
# gpt-3
'gpt-3': gpt_3,
# gpt-3.5
'gpt-3.5-turbo': gpt_35_turbo,
# gpt-4
'gpt-4o': gpt_4o,
'gpt-4o-mini': gpt_4o_mini,
'gpt-4': gpt_4,
'gpt-4-turbo': gpt_4_turbo,
# o1
'o1': o1,
'o1-mini': o1_mini,
### Meta ###
"meta-ai": meta,
# llama-2
'llama-2-7b': llama_2_7b,
'llama-2-13b': llama_2_13b,
# llama-3
'llama-3-8b': llama_3_8b,
'llama-3-70b': llama_3_70b,
# llama-3.1
'llama-3.1-8b': llama_3_1_8b,
'llama-3.1-70b': llama_3_1_70b,
'llama-3.1-405b': llama_3_1_405b,
# llama-3.2
'llama-3.2-1b': llama_3_2_1b,
'llama-3.2-3b': llama_3_2_3b,
'llama-3.2-11b': llama_3_2_11b,
'llama-3.2-90b': llama_3_2_90b,
# llamaguard
'llamaguard-7b': llamaguard_7b,
'llamaguard-2-8b': llamaguard_2_8b,
### Mistral ###
'mistral-7b': mistral_7b,
'mixtral-8x7b': mixtral_8x7b,
'mixtral-8x22b': mixtral_8x22b,
'mistral-nemo': mistral_nemo,
### NousResearch ###
'mixtral-8x7b-dpo': mixtral_8x7b_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,
'gemini-pro': gemini_pro,
'gemini-flash': gemini_flash,
# 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,
### Anthropic ###
'claude-2.1': claude_2_1,
# claude 3
'claude-3-opus': claude_3_opus,
'claude-3-sonnet': claude_3_sonnet,
'claude-3-haiku': claude_3_haiku,
# claude 3.5
'claude-3.5-sonnet': claude_3_5_sonnet,
### Reka AI ###
'reka-core': reka_core,
### Blackbox AI ###
'blackboxai': blackboxai,
'blackboxai-pro': blackboxai_pro,
### CohereForAI ###
'command-r+': command_r_plus,
### Databricks ###
'dbrx-instruct': dbrx_instruct,
### GigaChat ###
'gigachat': gigachat,
### iFlytek ###
'sparkdesk-v1.1': sparkdesk_v1_1,
### Qwen ###
'qwen': qwen,
'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,
### Zhipu AI ###
'glm-3-6b': glm_3_6b,
'glm-4-9b': glm_4_9b,
### 01-ai ###
'yi-1.5-9b': yi_1_5_9b,
### Upstage ###
'solar-1-mini': solar_1_mini,
'solar-10-7b': solar_10_7b,
'solar-pro': solar_pro,
### Inflection ###
'pi': pi,
### DeepSeek ###
'deepseek': deepseek,
### Yorickvp ###
'llava-13b': llava_13b,
### WizardLM ###
'wizardlm-2-7b': wizardlm_2_7b,
'wizardlm-2-8x22b': wizardlm_2_8x22b,
### OpenBMB ###
'minicpm-llama-3-v2.5': minicpm_llama_3_v2_5,
### Lzlv ###
'lzlv-70b': lzlv_70b,
### OpenChat ###
'openchat-3.5': openchat_3_5,
'openchat-3.6-8b': openchat_3_6_8b,
### Phind ###
'phind-codellama-34b-v2': phind_codellama_34b_v2,
### Cognitive Computations ###
'dolphin-2.9.1-llama-3-70b': dolphin_2_9_1_llama_3_70b,
### x.ai ###
'grok-2': grok_2,
'grok-2-mini': grok_2_mini,
### 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,
#############
### Image ###
#############
### Stability AI ###
'sdxl': sdxl,
'sd-3': sd_3,
### Playground ###
'playground-v2.5': playground_v2_5,
### Flux AI ###
'flux': flux,
'flux-pro': flux_pro,
'flux-realism': flux_realism,
'flux-anime': flux_anime,
'flux-3d': flux_3d,
'flux-disney': flux_disney,
'flux-pixel': flux_pixel,
'flux-4o': flux_4o,
'flux-schnell': flux_schnell,
### OpenAI ###
'dalle': dalle,
'dalle-2': dalle_2,
'dalle-3': dalle_3,
'dalle-mini': dalle_mini,
### Other ###
'emi': emi,
'any-dark': any_dark,
}
_all_models = list(ModelUtils.convert.keys())
