mirror of https://github.com/xtekky/gpt4free
You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
498 lines
10 KiB
Python
498 lines
10 KiB
Python
from __future__ import annotations
|
|
|
|
from dataclasses import dataclass
|
|
|
|
from .Provider import IterListProvider, ProviderType
|
|
from .Provider import (
|
|
AI365VIP,
|
|
Bing,
|
|
Blackbox,
|
|
Chatgpt4o,
|
|
ChatgptFree,
|
|
DDG,
|
|
DeepInfra,
|
|
DeepInfraImage,
|
|
FreeChatgpt,
|
|
FreeGpt,
|
|
Gemini,
|
|
GeminiPro,
|
|
GeminiProChat,
|
|
GigaChat,
|
|
HuggingChat,
|
|
HuggingFace,
|
|
Koala,
|
|
Liaobots,
|
|
MetaAI,
|
|
OpenaiChat,
|
|
PerplexityLabs,
|
|
Pi,
|
|
Pizzagpt,
|
|
Reka,
|
|
Replicate,
|
|
ReplicateHome,
|
|
Vercel,
|
|
You,
|
|
)
|
|
|
|
@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([
|
|
Bing,
|
|
You,
|
|
OpenaiChat,
|
|
FreeChatgpt,
|
|
AI365VIP,
|
|
Chatgpt4o,
|
|
DDG,
|
|
ChatgptFree,
|
|
Koala,
|
|
Pizzagpt,
|
|
])
|
|
)
|
|
|
|
# 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 = IterListProvider([
|
|
FreeGpt,
|
|
You,
|
|
OpenaiChat,
|
|
Koala,
|
|
ChatgptFree,
|
|
FreeChatgpt,
|
|
DDG,
|
|
AI365VIP,
|
|
Pizzagpt,
|
|
])
|
|
)
|
|
|
|
############
|
|
### Text ###
|
|
############
|
|
|
|
### OpenAI ###
|
|
### GPT-3.5 / GPT-4 ###
|
|
# gpt-3.5
|
|
gpt_35_turbo = Model(
|
|
name = 'gpt-3.5-turbo',
|
|
base_provider = 'openai',
|
|
best_provider = IterListProvider([
|
|
FreeGpt,
|
|
You,
|
|
Koala,
|
|
OpenaiChat,
|
|
ChatgptFree,
|
|
FreeChatgpt,
|
|
DDG,
|
|
AI365VIP,
|
|
Pizzagpt,
|
|
])
|
|
)
|
|
|
|
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
|
|
gpt_4 = Model(
|
|
name = 'gpt-4',
|
|
base_provider = 'openai',
|
|
best_provider = IterListProvider([
|
|
Bing, Liaobots,
|
|
])
|
|
)
|
|
|
|
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
|
|
)
|
|
|
|
gpt_4_turbo = Model(
|
|
name = 'gpt-4-turbo',
|
|
base_provider = 'openai',
|
|
best_provider = Bing
|
|
)
|
|
|
|
gpt_4o = Model(
|
|
name = 'gpt-4o',
|
|
base_provider = 'openai',
|
|
best_provider = IterListProvider([
|
|
You, Liaobots, Chatgpt4o, AI365VIP
|
|
])
|
|
)
|
|
|
|
|
|
### GigaChat ###
|
|
gigachat = Model(
|
|
name = 'GigaChat:latest',
|
|
base_provider = 'gigachat',
|
|
best_provider = GigaChat
|
|
)
|
|
|
|
|
|
### Meta ###
|
|
meta = Model(
|
|
name = "meta",
|
|
base_provider = "meta",
|
|
best_provider = MetaAI
|
|
)
|
|
|
|
llama_2_70b_chat = Model(
|
|
name = "meta/llama-2-70b-chat",
|
|
base_provider = "meta",
|
|
best_provider = IterListProvider([ReplicateHome])
|
|
)
|
|
|
|
llama3_8b_instruct = Model(
|
|
name = "meta-llama/Meta-Llama-3-8B-Instruct",
|
|
base_provider = "meta",
|
|
best_provider = IterListProvider([DeepInfra, PerplexityLabs, Replicate])
|
|
)
|
|
|
|
llama3_70b_instruct = Model(
|
|
name = "meta-llama/Meta-Llama-3-70B-Instruct",
|
|
base_provider = "meta",
|
|
best_provider = IterListProvider([DeepInfra, PerplexityLabs, Replicate, HuggingChat, DDG])
|
|
)
|
|
|
|
codellama_34b_instruct = Model(
|
|
name = "codellama/CodeLlama-34b-Instruct-hf",
|
|
base_provider = "meta",
|
|
best_provider = HuggingChat
|
|
)
|
|
|
|
codellama_70b_instruct = Model(
|
|
name = "codellama/CodeLlama-70b-Instruct-hf",
|
|
base_provider = "meta",
|
|
best_provider = IterListProvider([DeepInfra])
|
|
)
|
|
|
|
|
|
### Mistral ###
|
|
mixtral_8x7b = Model(
|
|
name = "mistralai/Mixtral-8x7B-Instruct-v0.1",
|
|
base_provider = "huggingface",
|
|
best_provider = IterListProvider([DeepInfra, HuggingFace, PerplexityLabs, HuggingChat, DDG])
|
|
)
|
|
|
|
mistral_7b_v02 = Model(
|
|
name = "mistralai/Mistral-7B-Instruct-v0.2",
|
|
base_provider = "huggingface",
|
|
best_provider = IterListProvider([DeepInfra, HuggingFace, HuggingChat, ReplicateHome])
|
|
)
|
|
|
|
|
|
### NousResearch ###
|
|
Nous_Hermes_2_Mixtral_8x7B_DPO = Model(
|
|
name = "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
|
|
base_provider = "NousResearch",
|
|
best_provider = IterListProvider([HuggingFace, HuggingChat])
|
|
)
|
|
|
|
|
|
### 01-ai ###
|
|
Yi_1_5_34B_Chat = Model(
|
|
name = "01-ai/Yi-1.5-34B-Chat",
|
|
base_provider = "01-ai",
|
|
best_provider = IterListProvider([HuggingFace, HuggingChat])
|
|
)
|
|
|
|
|
|
### Microsoft ###
|
|
Phi_3_mini_4k_instruct = Model(
|
|
name = "microsoft/Phi-3-mini-4k-instruct",
|
|
base_provider = "Microsoft",
|
|
best_provider = IterListProvider([HuggingFace, HuggingChat])
|
|
)
|
|
|
|
|
|
### Google ###
|
|
# gemini
|
|
gemini = Model(
|
|
name = 'gemini',
|
|
base_provider = 'Google',
|
|
best_provider = Gemini
|
|
)
|
|
|
|
gemini_pro = Model(
|
|
name = 'gemini-pro',
|
|
base_provider = 'Google',
|
|
best_provider = IterListProvider([GeminiPro, You, GeminiProChat])
|
|
)
|
|
|
|
# gemma
|
|
gemma_2_9b_it = Model(
|
|
name = 'gemma-2-9b-it',
|
|
base_provider = 'Google',
|
|
best_provider = IterListProvider([PerplexityLabs])
|
|
)
|
|
|
|
gemma_2_27b_it = Model(
|
|
name = 'gemma-2-27b-it',
|
|
base_provider = 'Google',
|
|
best_provider = IterListProvider([PerplexityLabs])
|
|
)
|
|
|
|
|
|
### Anthropic ###
|
|
claude_v2 = Model(
|
|
name = 'claude-v2',
|
|
base_provider = 'anthropic',
|
|
best_provider = IterListProvider([Vercel])
|
|
)
|
|
|
|
claude_3_opus = Model(
|
|
name = 'claude-3-opus',
|
|
base_provider = 'anthropic',
|
|
best_provider = You
|
|
)
|
|
|
|
claude_3_sonnet = Model(
|
|
name = 'claude-3-sonnet',
|
|
base_provider = 'anthropic',
|
|
best_provider = You
|
|
)
|
|
|
|
claude_3_haiku = Model(
|
|
name = 'claude-3-haiku',
|
|
base_provider = 'anthropic',
|
|
best_provider = IterListProvider([DDG, AI365VIP])
|
|
)
|
|
|
|
|
|
### Reka AI ###
|
|
reka_core = Model(
|
|
name = 'reka-core',
|
|
base_provider = 'Reka AI',
|
|
best_provider = Reka
|
|
)
|
|
|
|
|
|
### NVIDIA ###
|
|
nemotron_4_340b_instruct = Model(
|
|
name = 'nemotron-4-340b-instruct',
|
|
base_provider = 'NVIDIA',
|
|
best_provider = IterListProvider([PerplexityLabs])
|
|
)
|
|
|
|
|
|
### Blackbox ###
|
|
blackbox = Model(
|
|
name = 'blackbox',
|
|
base_provider = 'Blackbox',
|
|
best_provider = Blackbox
|
|
)
|
|
|
|
|
|
### Databricks ###
|
|
dbrx_instruct = Model(
|
|
name = 'databricks/dbrx-instruct',
|
|
base_provider = 'Databricks',
|
|
best_provider = IterListProvider([DeepInfra])
|
|
)
|
|
|
|
|
|
### CohereForAI ###
|
|
command_r_plus = Model(
|
|
name = 'CohereForAI/c4ai-command-r-plus',
|
|
base_provider = 'CohereForAI',
|
|
best_provider = IterListProvider([HuggingChat])
|
|
)
|
|
|
|
|
|
### Other ###
|
|
pi = Model(
|
|
name = 'pi',
|
|
base_provider = 'inflection',
|
|
best_provider = Pi
|
|
)
|
|
|
|
|
|
#############
|
|
### Image ###
|
|
#############
|
|
|
|
### Stability AI ###
|
|
sdxl = Model(
|
|
name = 'stability-ai/sdxl',
|
|
base_provider = 'Stability AI',
|
|
best_provider = IterListProvider([ReplicateHome, DeepInfraImage])
|
|
|
|
)
|
|
|
|
### AI Forever ###
|
|
kandinsky_2_2 = Model(
|
|
name = 'ai-forever/kandinsky-2.2',
|
|
base_provider = 'AI Forever',
|
|
best_provider = IterListProvider([ReplicateHome])
|
|
|
|
)
|
|
|
|
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-3.5 / GPT-4 ###
|
|
# 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-4o' : gpt_4o,
|
|
'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,
|
|
|
|
|
|
### Meta ###
|
|
"meta-ai": meta,
|
|
|
|
'llama-2-70b-chat': llama_2_70b_chat,
|
|
'llama3-8b': llama3_8b_instruct, # alias
|
|
'llama3-70b': llama3_70b_instruct, # alias
|
|
'llama3-8b-instruct' : llama3_8b_instruct,
|
|
'llama3-70b-instruct': llama3_70b_instruct,
|
|
|
|
'codellama-34b-instruct': codellama_34b_instruct,
|
|
'codellama-70b-instruct': codellama_70b_instruct,
|
|
|
|
|
|
### Mistral (Opensource) ###
|
|
'mixtral-8x7b': mixtral_8x7b,
|
|
'mistral-7b-v02': mistral_7b_v02,
|
|
|
|
|
|
### NousResearch ###
|
|
'Nous-Hermes-2-Mixtral-8x7B-DPO': Nous_Hermes_2_Mixtral_8x7B_DPO,
|
|
|
|
|
|
### 01-ai ###
|
|
'Yi-1.5-34B-Chat': Yi_1_5_34B_Chat,
|
|
|
|
|
|
### Microsoft ###
|
|
'Phi-3-mini-4k-instruct': Phi_3_mini_4k_instruct,
|
|
|
|
|
|
### Google ###
|
|
# gemini
|
|
'gemini': gemini,
|
|
'gemini-pro': gemini_pro,
|
|
|
|
# gemma
|
|
'gemma-2-9b-it': gemma_2_9b_it,
|
|
'gemma-2-27b-it': gemma_2_27b_it,
|
|
|
|
|
|
### Anthropic ###
|
|
'claude-v2': claude_v2,
|
|
'claude-3-opus': claude_3_opus,
|
|
'claude-3-sonnet': claude_3_sonnet,
|
|
'claude-3-haiku': claude_3_haiku,
|
|
|
|
|
|
### Reka AI ###
|
|
'reka': reka_core,
|
|
|
|
|
|
### NVIDIA ###
|
|
'nemotron-4-340b-instruct': nemotron_4_340b_instruct,
|
|
|
|
|
|
### Blackbox ###
|
|
'blackbox': blackbox,
|
|
|
|
|
|
### CohereForAI ###
|
|
'command-r+': command_r_plus,
|
|
|
|
|
|
### Databricks ###
|
|
'dbrx-instruct': dbrx_instruct,
|
|
|
|
|
|
### GigaChat ###
|
|
'gigachat': gigachat,
|
|
|
|
|
|
# Other
|
|
'pi': pi,
|
|
|
|
|
|
|
|
#############
|
|
### Image ###
|
|
#############
|
|
|
|
### Stability AI ###
|
|
'sdxl': sdxl,
|
|
|
|
### AI Forever ###
|
|
'kandinsky-2.2': kandinsky_2_2,
|
|
}
|
|
|
|
_all_models = list(ModelUtils.convert.keys())
|