from __future__ import annotations
from dataclasses import dataclass
from .Provider import RetryProvider, ProviderType
from .Provider import (
Chatgpt4Online,
PerplexityLabs,
ChatgptDemoAi,
GeminiProChat,
ChatgptNext,
HuggingChat,
ChatgptDemo,
FreeChatgpt,
GptForLove,
ChatgptAi,
DeepInfra,
ChatBase,
Liaobots,
GeekGpt,
FakeGpt,
FreeGpt,
Llama2,
Vercel,
Phind,
GptGo,
Gpt6,
Bard,
Bing,
You,
Pi,
)
@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 = RetryProvider([
Bing,
ChatgptAi, GptGo, GeekGpt,
You,
Chatgpt4Online
])
)
# GPT-3.5 too, but all providers supports long requests and responses
gpt_35_long = Model(
name = 'gpt-3.5-turbo',
base_provider = 'openai',
best_provider = RetryProvider([
FreeGpt, You,
GeekGpt, FakeGpt,
Chatgpt4Online,
ChatgptDemoAi,
ChatgptNext,
ChatgptDemo,
Gpt6,
])
)
# GPT-3.5 / GPT-4
gpt_35_turbo = Model(
name = 'gpt-3.5-turbo',
base_provider = 'openai',
best_provider = RetryProvider([
GptGo, You,
GptForLove, ChatBase,
Chatgpt4Online,
])
)
gpt_4 = Model(
name = 'gpt-4',
base_provider = 'openai',
best_provider = RetryProvider([
Bing, Liaobots,
])
)
gpt_4_turbo = Model(
name = 'gpt-4-turbo',
base_provider = 'openai',
best_provider = Bing
)
llama2_7b = Model(
name = "meta-llama/Llama-2-7b-chat-hf",
base_provider = 'huggingface',
best_provider = RetryProvider([Llama2, DeepInfra])
)
llama2_13b = Model(
name = "meta-llama/Llama-2-13b-chat-hf",
base_provider = 'huggingface',
best_provider = RetryProvider([Llama2, DeepInfra])
)
llama2_70b = Model(
name = "meta-llama/Llama-2-70b-chat-hf",
base_provider = "huggingface",
best_provider = RetryProvider([Llama2, DeepInfra, HuggingChat, PerplexityLabs])
)
codellama_34b_instruct = Model(
name = "codellama/CodeLlama-34b-Instruct-hf",
base_provider = "huggingface",
best_provider = RetryProvider([HuggingChat, PerplexityLabs, DeepInfra])
)
# Mistral
mixtral_8x7b = Model(
name = "mistralai/Mixtral-8x7B-Instruct-v0.1",
base_provider = "huggingface",
best_provider = RetryProvider([DeepInfra, HuggingChat, PerplexityLabs])
)
mistral_7b = Model(
name = "mistralai/Mistral-7B-Instruct-v0.1",
base_provider = "huggingface",
best_provider = RetryProvider([DeepInfra, HuggingChat, PerplexityLabs])
)
# Misc models
dolphin_mixtral_8x7b = Model(
name = "cognitivecomputations/dolphin-2.6-mixtral-8x7b",
base_provider = "huggingface",
best_provider = DeepInfra
)
lzlv_70b = Model(
name = "lizpreciatior/lzlv_70b_fp16_hf",
base_provider = "huggingface",
best_provider = DeepInfra
)
airoboros_70b = Model(
name = "deepinfra/airoboros-70b",
base_provider = "huggingface",
best_provider = DeepInfra
)
airoboros_l2_70b = Model(
name = "jondurbin/airoboros-l2-70b-gpt4-1.4.1",
base_provider = "huggingface",
best_provider = DeepInfra
)
openchat_35 = Model(
name = "openchat/openchat_3.5",
base_provider = "huggingface",
best_provider = RetryProvider([DeepInfra, HuggingChat])
)
# Bard
bard = palm = Model(
name = 'palm',
base_provider = 'google',
best_provider = Bard
)
claude_v2 = Model(
name = 'claude-v2',
base_provider = 'anthropic',
best_provider = RetryProvider([FreeChatgpt, Vercel])
)
gpt_35_turbo_16k = Model(
name = 'gpt-3.5-turbo-16k',
base_provider = 'openai',
best_provider = gpt_35_long.best_provider
)
gpt_35_turbo_16k_0613 = Model(
name = 'gpt-3.5-turbo-16k-0613',
base_provider = 'openai',
best_provider = gpt_35_long.best_provider
)
gpt_35_turbo_0613 = Model(
name = 'gpt-3.5-turbo-0613',
base_provider = 'openai',
best_provider = gpt_35_turbo.best_provider
)
gpt_4_0613 = Model(
name = 'gpt-4-0613',
base_provider = 'openai',
best_provider = gpt_4.best_provider
)
gpt_4_32k = Model(
name = 'gpt-4-32k',
base_provider = 'openai',
best_provider = gpt_4.best_provider
)
gpt_4_32k_0613 = Model(
name = 'gpt-4-32k-0613',
base_provider = 'openai',
best_provider = gpt_4.best_provider
)
gemini_pro = Model(
name = 'gemini-pro',
base_provider = 'google',
best_provider = RetryProvider([FreeChatgpt, GeminiProChat])
)
pi = Model(
name = 'pi',
base_provider = 'inflection',
best_provider = Pi
)
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] = {
# gpt-3.5
'gpt-3.5-turbo' : gpt_35_turbo,
'gpt-3.5-turbo-0613' : gpt_35_turbo_0613,
'gpt-3.5-turbo-16k' : gpt_35_turbo_16k,
'gpt-3.5-turbo-16k-0613' : gpt_35_turbo_16k_0613,
'gpt-3.5-long': gpt_35_long,
# gpt-4
'gpt-4' : gpt_4,
'gpt-4-0613' : gpt_4_0613,
'gpt-4-32k' : gpt_4_32k,
'gpt-4-32k-0613' : gpt_4_32k_0613,
'gpt-4-turbo' : gpt_4_turbo,
# Llama 2
'llama2-7b' : llama2_7b,
'llama2-13b': llama2_13b,
'llama2-70b': llama2_70b,
'codellama-34b-instruct': codellama_34b_instruct,
'mixtral-8x7b': mixtral_8x7b,
'mistral-7b': mistral_7b,
'dolphin-mixtral-8x7b': dolphin_mixtral_8x7b,
'lzlv-70b': lzlv_70b,
'airoboros-70b': airoboros_70b,
'airoboros-l2-70b': airoboros_l2_70b,
'openchat_3.5': openchat_35,
'gemini-pro': gemini_pro,
'bard': bard,
'claude-v2': claude_v2,
'pi': pi
}
_all_models = list(ModelUtils.convert.keys())