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- from __future__ import annotations
- from dataclasses import dataclass
- from .typing import Union
- from .Provider import BaseProvider, RetryProvider
- from .Provider import (
- Chatgpt4Online,
- ChatgptDemoAi,
- ChatAnywhere,
- ChatgptNext,
- HuggingChat,
- GptForLove,
- ChatgptAi,
- DeepInfra,
- OnlineGpt,
- ChatBase,
- Liaobots,
- GeekGpt,
- FakeGpt,
- FreeGpt,
- Berlin,
- Llama2,
- Vercel,
- Phind,
- Koala,
- GptGo,
- Bard,
- Bing,
- You,
- H2o,
- Pi,
- VoiGpt,
- )
- @dataclass(unsafe_hash=True)
- class Model:
- name: str
- base_provider: str
- best_provider: Union[type[BaseProvider], RetryProvider] = None
-
- @staticmethod
- def __all__() -> list[str]:
- return _all_models
- default = Model(
- name = "",
- base_provider = "",
- best_provider = RetryProvider([
- Bing,
- ChatgptAi, GptGo, GeekGpt,
- You,
- Chatgpt4Online,
- ChatAnywhere,
- VoiGpt
- ])
- )
- # 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,
- Berlin, Koala,
- Chatgpt4Online,
- ChatAnywhere,
- ChatgptDemoAi,
- OnlineGpt,
- ChatgptNext,
- VoiGpt
- ])
- )
- # 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,
- ChatAnywhere,
- VoiGpt,
- ])
- )
- gpt_4 = Model(
- name = 'gpt-4',
- base_provider = 'openai',
- best_provider = RetryProvider([
- Bing, Phind, Liaobots
- ])
- )
- 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]))
- # Mistal
- mixtral_8x7b = Model(
- name = "mistralai/Mixtral-8x7B-Instruct-v0.1",
- base_provider = "huggingface",
- best_provider = HuggingChat)
- mistral_7b = Model(
- name = "mistralai/Mistral-7B-Instruct-v0.1",
- base_provider = "huggingface",
- best_provider = HuggingChat)
- # Bard
- palm = Model(
- 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)
- falcon_40b = Model(
- 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)
- # Vercel
- claude_instant_v1 = Model(
- name = 'claude-instant-v1',
- base_provider = 'anthropic',
- best_provider = Vercel)
- claude_v1 = Model(
- name = 'claude-v1',
- base_provider = 'anthropic',
- best_provider = Vercel)
- claude_v2 = Model(
- name = 'claude-v2',
- base_provider = 'anthropic',
- best_provider = Vercel)
- command_light_nightly = Model(
- name = 'command-light-nightly',
- base_provider = 'cohere',
- best_provider = Vercel)
- command_nightly = Model(
- name = 'command-nightly',
- base_provider = 'cohere',
- best_provider = Vercel)
- gpt_neox_20b = Model(
- 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)
- oasst_sft_4_pythia_12b_epoch_35 = Model(
- 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)
- bloom = Model(
- name = 'bigscience/bloom',
- base_provider = 'huggingface',
- best_provider = Vercel)
- flan_t5_xxl = Model(
- 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)
- 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
- )
- text_ada_001 = Model(
- name = 'text-ada-001',
- base_provider = 'openai',
- best_provider = Vercel)
- text_babbage_001 = Model(
- name = 'text-babbage-001',
- base_provider = 'openai',
- best_provider = Vercel)
- text_curie_001 = Model(
- name = 'text-curie-001',
- base_provider = 'openai',
- best_provider = Vercel)
- text_davinci_002 = Model(
- name = 'text-davinci-002',
- base_provider = 'openai',
- best_provider = Vercel)
- text_davinci_003 = Model(
- 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)
- llama7b_v2_chat = Model(
- name = 'replicate:a16z-infra/llama7b-v2-chat',
- base_provider = 'replicate',
- best_provider = Vercel)
- llama70b_v2_chat = Model(
- name = 'replicate/llama70b-v2-chat',
- base_provider = 'replicate',
- best_provider = Vercel)
- pi = Model(
- name = 'pi',
- base_provider = 'inflection',
- best_provider=Pi
- )
- class ModelUtils:
- 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,
- # Llama 2
- 'llama2-7b' : llama2_7b,
- 'llama2-13b': llama2_13b,
- 'llama2-70b': llama2_70b,
-
- # Mistral
- 'mixtral-8x7b': mixtral_8x7b,
- 'mistral-7b': mistral_7b,
-
- # Bard
- '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,
-
- # 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,
- 'llama70b-v2-chat' : llama70b_v2_chat,
- '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,
- 'pi': pi
- }
- _all_models = list(ModelUtils.convert.keys())
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