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from __future__ import annotations
from __future__ import annotations
from dataclasses import dataclass
from .typing import Union
from .Provider import BaseProvider, RetryProvider
from .Provider import (
from .typing import Union
from .Provider import BaseProvider, RetryProvider
from .Provider import (
AItianhuSpace,
ChatgptLogin,
ChatgptAi,
ChatBase,
Vercel,
DeepAi,
Aivvm,
Bard,
H2o,
GptGo,
Bing,
PerplexityAi,
ChatgptDuo,
ChatgptAi,
ChatBase,
AItianhu,
Wewordle,
Yqcloud,
AItianhu,
AItianhuSpace,
Aichat,
Myshell,
Vercel,
DeepAi,
Aichat,
Aivvm,
GptGo,
Bard,
Aibn,
ChatgptDuo,
Bing,
H2o,
)
@dataclass(unsafe_hash=True)
class Model:
name: str
base_provider: str
best_provider: Union[type[BaseProvider], RetryProvider] = None
# Config for HuggingChat, OpenAssistant
# Works for Liaobots, H2o, OpenaiChat, Yqcloud, You
default = Model(
name="",
base_provider="",
best_provider=RetryProvider([
Bing, # Not fully GPT 3 or 4
PerplexityAi, # Adds references to sources
Wewordle, # Responds with markdown
Yqcloud, # Answers short questions in chinese
ChatBase, # Don't want to answer creatively
ChatgptDuo, # Include search results
name = "",
base_provider = "",
best_provider = RetryProvider([
Bing, # Not fully GPT 3 or 4
PerplexityAi, # Adds references to sources
Wewordle, # Responds with markdown
Yqcloud, # Answers short questions in chinese
ChatBase, # Don't want to answer creatively
ChatgptDuo, # Include search results
DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, AItianhuSpace, Aichat, Myshell, Aibn,
])
)
# GPT-3.5 / GPT-4
gpt_35_turbo = Model(
name='gpt-3.5-turbo',
base_provider='openai',
best_provider=RetryProvider([
name = 'gpt-3.5-turbo',
base_provider = 'openai',
best_provider = RetryProvider([
DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, Aichat, AItianhuSpace, Myshell, Aibn,
])
)
gpt_4 = Model(
name='gpt-4',
base_provider='openai',
best_provider=RetryProvider([
Myshell, AItianhuSpace, Aivvm
name = 'gpt-4',
base_provider = 'openai',
best_provider = RetryProvider([
Myshell, AItianhuSpace,
])
)
# Bard
palm = Model(
name='palm',
base_provider='google',
best_provider=Bard)
name = 'palm',
base_provider = 'google',
best_provider = Bard)
# H2o
falcon_7b = Model(
name='h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
base_provider='huggingface',
best_provider=H2o)
name = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
base_provider = 'huggingface',
best_provider = H2o)
falcon_40b = Model(
name='h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
base_provider='huggingface',
best_provider=H2o)
name = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
base_provider = 'huggingface',
best_provider = H2o)
llama_13b = Model(
name='h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b',
base_provider='huggingface',
best_provider=H2o)
name = 'h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b',
base_provider = 'huggingface',
best_provider = H2o)
# Vercel
claude_instant_v1 = Model(
name='claude-instant-v1',
base_provider='anthropic',
best_provider=Vercel)
name = 'claude-instant-v1',
base_provider = 'anthropic',
best_provider = Vercel)
claude_v1 = Model(
name='claude-v1',
base_provider='anthropic',
best_provider=Vercel)
name = 'claude-v1',
base_provider = 'anthropic',
best_provider = Vercel)
claude_v2 = Model(
name='claude-v2',
base_provider='anthropic',
best_provider=Vercel)
name = 'claude-v2',
base_provider = 'anthropic',
best_provider = Vercel)
command_light_nightly = Model(
name='command-light-nightly',
base_provider='cohere',
best_provider=Vercel)
name = 'command-light-nightly',
base_provider = 'cohere',
best_provider = Vercel)
command_nightly = Model(
name='command-nightly',
base_provider='cohere',
best_provider=Vercel)
name = 'command-nightly',
base_provider = 'cohere',
best_provider = Vercel)
gpt_neox_20b = Model(
name='EleutherAI/gpt-neox-20b',
base_provider='huggingface',
best_provider=Vercel)
name = 'EleutherAI/gpt-neox-20b',
base_provider = 'huggingface',
best_provider = Vercel)
oasst_sft_1_pythia_12b = Model(
name='OpenAssistant/oasst-sft-1-pythia-12b',
base_provider='huggingface',
best_provider=Vercel)
name = 'OpenAssistant/oasst-sft-1-pythia-12b',
base_provider = 'huggingface',
best_provider = Vercel)
oasst_sft_4_pythia_12b_epoch_35 = Model(
name='OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
base_provider='huggingface',
best_provider=Vercel)
name = 'OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
base_provider = 'huggingface',
best_provider = Vercel)
santacoder = Model(
name='bigcode/santacoder',
base_provider='huggingface',
best_provider=Vercel)
name = 'bigcode/santacoder',
base_provider = 'huggingface',
best_provider = Vercel)
bloom = Model(
name='bigscience/bloom',
base_provider='huggingface',
best_provider=Vercel)
name = 'bigscience/bloom',
base_provider = 'huggingface',
best_provider = Vercel)
flan_t5_xxl = Model(
name='google/flan-t5-xxl',
base_provider='huggingface',
best_provider=Vercel)
name = 'google/flan-t5-xxl',
base_provider = 'huggingface',
best_provider = Vercel)
code_davinci_002 = Model(
name='code-davinci-002',
base_provider='openai',
best_provider=Vercel)
name = 'code-davinci-002',
base_provider = 'openai',
best_provider = Vercel)
gpt_35_turbo_16k = Model(
name='gpt-3.5-turbo-16k',
base_provider='openai',
best_provider=Aivvm)
name = 'gpt-3.5-turbo-16k',
base_provider = 'openai',
best_provider = Vercel)
gpt_35_turbo_16k_0613 = Model(
name='gpt-3.5-turbo-16k-0613',
base_provider='openai')
name = 'gpt-3.5-turbo-16k-0613',
base_provider = 'openai')
gpt_35_turbo_0613 = Model(
name='gpt-3.5-turbo-0613',
base_provider='openai',
best_provider=RetryProvider([
name = 'gpt-3.5-turbo-0613',
base_provider = 'openai',
best_provider = RetryProvider([
Aivvm, ChatgptLogin
])
)
gpt_4_0613 = Model(
name='gpt-4-0613',
base_provider='openai',
best_provider=Aivvm)
name = 'gpt-4-0613',
base_provider = 'openai',
best_provider = Aivvm)
gpt_4_32k = Model(
name='gpt-4-32k',
base_provider='openai',
best_provider=Aivvm)
name = 'gpt-4-32k',
base_provider = 'openai',
best_provider = Aivvm)
gpt_4_32k_0613 = Model(
name='gpt-4-32k-0613',
base_provider='openai',
best_provider=Aivvm)
name = 'gpt-4-32k-0613',
base_provider = 'openai',
best_provider = Aivvm)
text_ada_001 = Model(
name='text-ada-001',
base_provider='openai',
best_provider=Vercel)
name = 'text-ada-001',
base_provider = 'openai',
best_provider = Vercel)
text_babbage_001 = Model(
name='text-babbage-001',
base_provider='openai',
best_provider=Vercel)
name = 'text-babbage-001',
base_provider = 'openai',
best_provider = Vercel)
text_curie_001 = Model(
name='text-curie-001',
base_provider='openai',
best_provider=Vercel)
name = 'text-curie-001',
base_provider = 'openai',
best_provider = Vercel)
text_davinci_002 = Model(
name='text-davinci-002',
base_provider='openai',
best_provider=Vercel)
name = 'text-davinci-002',
base_provider = 'openai',
best_provider = Vercel)
text_davinci_003 = Model(
name='text-davinci-003',
base_provider='openai',
best_provider=Vercel)
name = 'text-davinci-003',
base_provider = 'openai',
best_provider = Vercel)
llama13b_v2_chat = Model(
name='replicate:a16z-infra/llama13b-v2-chat',
base_provider='replicate',
best_provider=Vercel)
name = 'replicate:a16z-infra/llama13b-v2-chat',
base_provider = 'replicate',
best_provider = Vercel)
llama7b_v2_chat = Model(
name='replicate:a16z-infra/llama7b-v2-chat',
base_provider='replicate',
best_provider=Vercel)
name = 'replicate:a16z-infra/llama7b-v2-chat',
base_provider = 'replicate',
best_provider = Vercel)
class ModelUtils:
convert: dict[str, Model] = {
# gpt-3.5 / gpt-4
'gpt-3.5-turbo': gpt_35_turbo,
'gpt-3.5-turbo-16k': gpt_35_turbo_16k,
'gpt-3.5-turbo-16k-0613': gpt_35_turbo_16k_0613,
'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-3.5
'gpt-3.5-turbo' : gpt_35_turbo,
'gpt-3.5-turbo-16k' : gpt_35_turbo_16k,
'gpt-3.5-turbo-16k-0613' : gpt_35_turbo_16k_0613,
# 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,
# Bard
'palm2': palm,
'palm': palm,
'google': palm,
'google-bard': palm,
'google-palm': palm,
'bard': palm,
'palm2' : palm,
'palm' : palm,
'google' : palm,
'google-bard' : palm,
'google-palm' : palm,
'bard' : palm,
# H2o
'falcon-40b': falcon_40b,
'falcon-7b': falcon_7b,
'llama-13b': llama_13b,
'falcon-40b' : falcon_40b,
'falcon-7b' : falcon_7b,
'llama-13b' : llama_13b,
# Vercel
'claude-instant-v1': claude_instant_v1,
'claude-v1': claude_v1,
'claude-v2': claude_v2,
'command-nightly': command_nightly,
'gpt-neox-20b': gpt_neox_20b,
'santacoder': santacoder,
'bloom': bloom,
'flan-t5-xxl': flan_t5_xxl,
'code-davinci-002': code_davinci_002,
'text-ada-001': text_ada_001,
'text-babbage-001': text_babbage_001,
'text-curie-001': text_curie_001,
'text-davinci-002': text_davinci_002,
'text-davinci-003': text_davinci_003,
'llama13b-v2-chat': llama13b_v2_chat,
'llama7b-v2-chat': llama7b_v2_chat,
'oasst-sft-1-pythia-12b': oasst_sft_1_pythia_12b,
'oasst-sft-4-pythia-12b-epoch-3.5': oasst_sft_4_pythia_12b_epoch_35,
'command-light-nightly': command_light_nightly,
}
'claude-instant-v1' : claude_instant_v1,
'claude-v1' : claude_v1,
'claude-v2' : claude_v2,
'command-nightly' : command_nightly,
'gpt-neox-20b' : gpt_neox_20b,
'santacoder' : santacoder,
'bloom' : bloom,
'flan-t5-xxl' : flan_t5_xxl,
'code-davinci-002' : code_davinci_002,
'text-ada-001' : text_ada_001,
'text-babbage-001' : text_babbage_001,
'text-curie-001' : text_curie_001,
'text-davinci-002' : text_davinci_002,
'text-davinci-003' : text_davinci_003,
'llama13b-v2-chat' : llama13b_v2_chat,
'llama7b-v2-chat' : llama7b_v2_chat,
'oasst-sft-1-pythia-12b' : oasst_sft_1_pythia_12b,
'oasst-sft-4-pythia-12b-epoch-3.5' : oasst_sft_4_pythia_12b_epoch_35,
'command-light-nightly' : command_light_nightly,
}