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307 lines
7.3 KiB
Python
307 lines
7.3 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass
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from .Provider import RetryProvider, ProviderType
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from .Provider import (
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Chatgpt4Online,
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PerplexityLabs,
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GeminiProChat,
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ChatgptNext,
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HuggingChat,
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HuggingFace,
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OpenaiChat,
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ChatgptAi,
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DeepInfra,
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GigaChat,
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Liaobots,
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FreeGpt,
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Llama2,
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Vercel,
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Gemini,
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Bing,
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You,
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Pi,
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)
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@dataclass(unsafe_hash=True)
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class Model:
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"""
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Represents a machine learning model configuration.
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Attributes:
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name (str): Name of the model.
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base_provider (str): Default provider for the model.
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best_provider (ProviderType): The preferred provider for the model, typically with retry logic.
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"""
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name: str
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base_provider: str
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best_provider: ProviderType = None
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@staticmethod
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def __all__() -> list[str]:
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"""Returns a list of all model names."""
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return _all_models
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default = Model(
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name = "",
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base_provider = "",
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best_provider = RetryProvider([
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Bing,
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ChatgptAi,
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You,
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Chatgpt4Online,
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OpenaiChat
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])
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)
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# GPT-3.5 too, but all providers supports long requests and responses
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gpt_35_long = Model(
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name = 'gpt-3.5-turbo',
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base_provider = 'openai',
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best_provider = RetryProvider([
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FreeGpt,
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You,
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ChatgptNext,
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OpenaiChat,
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])
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)
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# GPT-3.5 / GPT-4
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gpt_35_turbo = Model(
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name = 'gpt-3.5-turbo',
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base_provider = 'openai',
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best_provider = OpenaiChat
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)
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gpt_4 = Model(
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name = 'gpt-4',
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base_provider = 'openai',
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best_provider = RetryProvider([
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Bing, Liaobots,
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])
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)
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gpt_4_turbo = Model(
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name = 'gpt-4-turbo',
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base_provider = 'openai',
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best_provider = Bing
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)
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gigachat = Model(
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name = 'GigaChat:latest',
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base_provider = 'gigachat',
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best_provider = GigaChat
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)
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gigachat_plus = Model(
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name = 'GigaChat-Plus',
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base_provider = 'gigachat',
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best_provider = GigaChat
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)
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gigachat_pro = Model(
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name = 'GigaChat-Pro',
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base_provider = 'gigachat',
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best_provider = GigaChat
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)
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llama2_7b = Model(
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name = "meta-llama/Llama-2-7b-chat-hf",
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base_provider = 'meta',
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best_provider = RetryProvider([Llama2, DeepInfra])
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)
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llama2_13b = Model(
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name = "meta-llama/Llama-2-13b-chat-hf",
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base_provider = 'meta',
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best_provider = RetryProvider([Llama2, DeepInfra])
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)
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llama2_70b = Model(
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name = "meta-llama/Llama-2-70b-chat-hf",
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base_provider = "meta",
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best_provider = RetryProvider([Llama2, DeepInfra, HuggingChat])
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)
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codellama_34b_instruct = Model(
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name = "codellama/CodeLlama-34b-Instruct-hf",
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base_provider = "meta",
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best_provider = RetryProvider([HuggingChat, DeepInfra])
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)
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codellama_70b_instruct = Model(
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name = "codellama/CodeLlama-70b-Instruct-hf",
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base_provider = "meta",
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best_provider = RetryProvider([DeepInfra, PerplexityLabs])
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)
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# Mistral
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mixtral_8x7b = Model(
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name = "mistralai/Mixtral-8x7B-Instruct-v0.1",
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base_provider = "huggingface",
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best_provider = RetryProvider([DeepInfra, HuggingChat, HuggingFace, PerplexityLabs])
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)
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mistral_7b = Model(
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name = "mistralai/Mistral-7B-Instruct-v0.1",
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base_provider = "huggingface",
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best_provider = RetryProvider([DeepInfra, HuggingChat, HuggingFace, PerplexityLabs])
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)
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# Misc models
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dolphin_mixtral_8x7b = Model(
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name = "cognitivecomputations/dolphin-2.6-mixtral-8x7b",
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base_provider = "huggingface",
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best_provider = DeepInfra
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)
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lzlv_70b = Model(
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name = "lizpreciatior/lzlv_70b_fp16_hf",
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base_provider = "huggingface",
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best_provider = DeepInfra
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)
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airoboros_70b = Model(
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name = "deepinfra/airoboros-70b",
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base_provider = "huggingface",
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best_provider = DeepInfra
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)
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airoboros_l2_70b = Model(
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name = "jondurbin/airoboros-l2-70b-gpt4-1.4.1",
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base_provider = "huggingface",
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best_provider = DeepInfra
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)
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openchat_35 = Model(
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name = "openchat/openchat_3.5",
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base_provider = "huggingface",
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best_provider = RetryProvider([DeepInfra, HuggingChat])
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)
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# Bard
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gemini = bard = palm = Model(
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name = 'gemini',
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base_provider = 'google',
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best_provider = Gemini
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)
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claude_v2 = Model(
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name = 'claude-v2',
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base_provider = 'anthropic',
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best_provider = RetryProvider([Vercel])
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)
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claude_3_opus = Model(
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name = 'claude-3-opus',
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base_provider = 'anthropic',
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best_provider = You
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)
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claude_3_sonnet = Model(
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name = 'claude-3-sonnet',
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base_provider = 'anthropic',
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best_provider = You
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)
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gpt_35_turbo_16k = Model(
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name = 'gpt-3.5-turbo-16k',
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base_provider = 'openai',
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best_provider = gpt_35_long.best_provider
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)
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gpt_35_turbo_16k_0613 = Model(
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name = 'gpt-3.5-turbo-16k-0613',
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base_provider = 'openai',
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best_provider = gpt_35_long.best_provider
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)
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gpt_35_turbo_0613 = Model(
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name = 'gpt-3.5-turbo-0613',
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base_provider = 'openai',
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best_provider = gpt_35_turbo.best_provider
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)
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gpt_4_0613 = Model(
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name = 'gpt-4-0613',
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base_provider = 'openai',
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best_provider = gpt_4.best_provider
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)
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gpt_4_32k = Model(
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name = 'gpt-4-32k',
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base_provider = 'openai',
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best_provider = gpt_4.best_provider
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)
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gpt_4_32k_0613 = Model(
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name = 'gpt-4-32k-0613',
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base_provider = 'openai',
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best_provider = gpt_4.best_provider
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)
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gemini_pro = Model(
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name = 'gemini-pro',
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base_provider = 'google',
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best_provider = RetryProvider([GeminiProChat, You])
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)
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pi = Model(
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name = 'pi',
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base_provider = 'inflection',
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best_provider = Pi
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)
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class ModelUtils:
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"""
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Utility class for mapping string identifiers to Model instances.
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Attributes:
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convert (dict[str, Model]): Dictionary mapping model string identifiers to Model instances.
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"""
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convert: dict[str, Model] = {
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# gpt-3.5
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'gpt-3.5-turbo' : gpt_35_turbo,
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'gpt-3.5-turbo-0613' : gpt_35_turbo_0613,
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'gpt-3.5-turbo-16k' : gpt_35_turbo_16k,
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'gpt-3.5-turbo-16k-0613' : gpt_35_turbo_16k_0613,
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'gpt-3.5-long': gpt_35_long,
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# gpt-4
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'gpt-4' : gpt_4,
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'gpt-4-0613' : gpt_4_0613,
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'gpt-4-32k' : gpt_4_32k,
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'gpt-4-32k-0613' : gpt_4_32k_0613,
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'gpt-4-turbo' : gpt_4_turbo,
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# Llama 2
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'llama2-7b' : llama2_7b,
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'llama2-13b': llama2_13b,
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'llama2-70b': llama2_70b,
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'codellama-34b-instruct': codellama_34b_instruct,
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'codellama-70b-instruct': codellama_70b_instruct,
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# GigaChat
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'gigachat' : gigachat,
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'gigachat_plus': gigachat_plus,
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'gigachat_pro' : gigachat_pro,
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'mixtral-8x7b': mixtral_8x7b,
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'mistral-7b': mistral_7b,
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'dolphin-mixtral-8x7b': dolphin_mixtral_8x7b,
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'lzlv-70b': lzlv_70b,
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'airoboros-70b': airoboros_70b,
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'airoboros-l2-70b': airoboros_l2_70b,
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'openchat_3.5': openchat_35,
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'gemini': gemini,
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'gemini-pro': gemini_pro,
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'claude-v2': claude_v2,
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'claude-3-opus': claude_3_opus,
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'claude-3-sonnet': claude_3_sonnet,
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'pi': pi
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}
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_all_models = list(ModelUtils.convert.keys())
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