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2df2d6b0cf
Add "Custom Provider": Set API Url in the settings Remove Discord link from result, add them to attr: Jmuz Fix Bug: File content are added to the prompt Changed response from /v1/models API Disable Pizzagpt Provider
914 lines
20 KiB
Python
914 lines
20 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass
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from .Provider import IterListProvider, ProviderType
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from .Provider import (
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Airforce,
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AutonomousAI,
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Blackbox,
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BlackboxCreateAgent,
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BingCreateImages,
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CablyAI,
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ChatGLM,
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ChatGpt,
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ChatGptEs,
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ChatGptt,
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ClaudeSon,
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Cloudflare,
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Copilot,
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CopilotAccount,
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DarkAI,
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DDG,
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DeepInfraChat,
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GigaChat,
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Gemini,
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GeminiPro,
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HuggingChat,
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HuggingFace,
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HuggingSpace,
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Jmuz,
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Liaobots,
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Mhystical,
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MetaAI,
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MicrosoftDesigner,
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OpenaiChat,
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OpenaiAccount,
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PerplexityLabs,
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Pi,
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PollinationsAI,
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Reka,
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ReplicateHome,
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RubiksAI,
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TeachAnything,
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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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class ImageModel(Model):
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pass
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### Default ###
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default = Model(
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name = "",
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base_provider = "",
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best_provider = IterListProvider([
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DDG,
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Blackbox,
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Copilot,
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ChatGptEs,
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ChatGptt,
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PollinationsAI,
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Jmuz,
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CablyAI,
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OpenaiChat,
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DarkAI,
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ClaudeSon,
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DeepInfraChat,
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Airforce,
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Cloudflare,
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])
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)
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############
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### Text ###
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############
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### OpenAI ###
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# gpt-3.5
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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 = IterListProvider([DarkAI, ChatGpt])
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)
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# gpt-4
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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 = IterListProvider([DDG, Blackbox, Jmuz, ChatGptEs, ChatGptt, PollinationsAI, Copilot, OpenaiChat, Liaobots, Mhystical])
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)
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# gpt-4o
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gpt_4o = Model(
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name = 'gpt-4o',
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base_provider = 'OpenAI',
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best_provider = IterListProvider([Blackbox, ChatGptt, Jmuz, ChatGptEs, PollinationsAI, DarkAI, ChatGpt, Liaobots, OpenaiChat])
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)
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gpt_4o_mini = Model(
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name = 'gpt-4o-mini',
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base_provider = 'OpenAI',
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best_provider = IterListProvider([DDG, ChatGptEs, ChatGptt, Jmuz, ChatGpt, RubiksAI, Liaobots, OpenaiChat])
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)
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# o1
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o1 = Model(
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name = 'o1',
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base_provider = 'OpenAI',
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best_provider = OpenaiAccount
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)
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o1_preview = Model(
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name = 'o1-preview',
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base_provider = 'OpenAI',
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best_provider = Liaobots
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)
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o1_mini = Model(
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name = 'o1-mini',
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base_provider = 'OpenAI',
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best_provider = Liaobots
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)
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### GigaChat ###
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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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### Meta ###
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meta = Model(
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name = "meta-ai",
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base_provider = "Meta",
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best_provider = MetaAI
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)
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# llama 2
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llama_2_7b = Model(
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name = "llama-2-7b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([Cloudflare, Airforce])
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)
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# llama 3
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llama_3_8b = Model(
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name = "llama-3-8b",
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base_provider = "Meta Llama",
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best_provider = Cloudflare
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)
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# llama 3.1
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llama_3_1_8b = Model(
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name = "llama-3.1-8b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([Blackbox, Jmuz, DeepInfraChat, Cloudflare, Airforce, PerplexityLabs])
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)
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llama_3_1_70b = Model(
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name = "llama-3.1-70b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([DDG, Jmuz, Blackbox, DeepInfraChat, BlackboxCreateAgent, TeachAnything, DarkAI, Airforce, RubiksAI, PerplexityLabs])
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)
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llama_3_1_405b = Model(
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name = "llama-3.1-405b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([Blackbox, Jmuz])
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)
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# llama 3.2
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llama_3_2_1b = Model(
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name = "llama-3.2-1b",
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base_provider = "Meta Llama",
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best_provider = Cloudflare
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)
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llama_3_2_3b = Model(
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name = "llama-3.2-3b",
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base_provider = "Meta Llama",
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best_provider = PollinationsAI
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)
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llama_3_2_11b = Model(
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name = "llama-3.2-11b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([Jmuz, HuggingChat, HuggingFace])
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)
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llama_3_2_90b = Model(
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name = "llama-3.2-90b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([AutonomousAI, Jmuz])
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)
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# llama 3.3
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llama_3_3_70b = Model(
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name = "llama-3.3-70b",
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base_provider = "Meta Llama",
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best_provider = IterListProvider([Blackbox, PollinationsAI, AutonomousAI, Jmuz, HuggingChat, HuggingFace, PerplexityLabs])
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)
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### Mistral ###
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mixtral_7b = Model(
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name = "mixtral-7b",
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base_provider = "Mistral",
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best_provider = Blackbox
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)
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mixtral_8x7b = Model(
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name = "mixtral-8x7b",
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base_provider = "Mistral",
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best_provider = IterListProvider([DDG, Jmuz])
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)
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mistral_nemo = Model(
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name = "mistral-nemo",
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base_provider = "Mistral",
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best_provider = IterListProvider([PollinationsAI, HuggingChat, HuggingFace])
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)
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mistral_large = Model(
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name = "mistral-large",
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base_provider = "Mistral",
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best_provider = PollinationsAI
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)
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### NousResearch ###
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hermes_2_dpo = Model(
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name = "hermes-2-dpo",
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base_provider = "NousResearch",
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best_provider = IterListProvider([Blackbox, Airforce])
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)
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hermes_2_pro = Model(
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name = "hermes-2-pro",
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base_provider = "NousResearch",
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best_provider = Airforce
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)
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hermes_3 = Model(
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name = "hermes-3",
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base_provider = "NousResearch",
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best_provider = IterListProvider([AutonomousAI, HuggingChat, HuggingFace])
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)
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### Microsoft ###
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phi_2 = Model(
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name = "phi-2",
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base_provider = "Microsoft",
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best_provider = Airforce
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)
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phi_3_5_mini = Model(
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name = "phi-3.5-mini",
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base_provider = "Microsoft",
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best_provider = IterListProvider([HuggingChat, HuggingFace])
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)
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### Google DeepMind ###
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# gemini
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gemini = Model(
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name = 'gemini',
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base_provider = 'Google',
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best_provider = IterListProvider([Jmuz, Gemini])
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)
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# gemini-1.5
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gemini_1_5_pro = Model(
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name = 'gemini-1.5-pro',
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base_provider = 'Google DeepMind',
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best_provider = IterListProvider([Blackbox, Jmuz, Gemini, GeminiPro, Liaobots])
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)
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gemini_1_5_flash = Model(
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name = 'gemini-1.5-flash',
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base_provider = 'Google DeepMind',
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best_provider = IterListProvider([Blackbox, Jmuz, Gemini, GeminiPro, Liaobots])
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)
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# gemini-2.0
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gemini_2_0_flash = Model(
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name = 'gemini-2.0-flash',
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base_provider = 'Google DeepMind',
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best_provider = IterListProvider([GeminiPro, Liaobots])
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)
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gemini_2_0_flash_thinking = Model(
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name = 'gemini-2.0-flash-thinking',
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base_provider = 'Google DeepMind',
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best_provider = Liaobots
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)
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# gemma
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gemma_2b = Model(
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name = 'gemma-2b',
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base_provider = 'Google',
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best_provider = ReplicateHome
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)
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### Anthropic ###
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# claude 3
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claude_3_haiku = Model(
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name = 'claude-3-haiku',
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base_provider = 'Anthropic',
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best_provider = IterListProvider([DDG, Jmuz])
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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 = Liaobots
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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 = IterListProvider([Jmuz, Liaobots])
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)
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# claude 3.5
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claude_3_5_sonnet = Model(
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name = 'claude-3.5-sonnet',
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base_provider = 'Anthropic',
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best_provider = IterListProvider([Blackbox, PollinationsAI, Jmuz, ClaudeSon, Liaobots])
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)
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### Reka AI ###
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reka_core = Model(
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name = 'reka-core',
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base_provider = 'Reka AI',
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best_provider = Reka
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)
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### Blackbox AI ###
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blackboxai = Model(
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name = 'blackboxai',
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base_provider = 'Blackbox AI',
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best_provider = Blackbox
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)
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blackboxai_pro = Model(
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name = 'blackboxai-pro',
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base_provider = 'Blackbox AI',
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best_provider = Blackbox
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)
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### CohereForAI ###
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command_r_plus = Model(
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name = 'command-r-plus',
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base_provider = 'CohereForAI',
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best_provider = HuggingChat
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)
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command_r = Model(
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name = 'command-r',
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base_provider = 'CohereForAI',
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best_provider = PollinationsAI
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)
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### Qwen ###
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# qwen 1_5
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qwen_1_5_7b = Model(
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name = 'qwen-1.5-7b',
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base_provider = 'Qwen',
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best_provider = Cloudflare
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)
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# qwen 2
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qwen_2_72b = Model(
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name = 'qwen-2-72b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([PollinationsAI, DeepInfraChat])
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)
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# qwen 2.5
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qwen_2_5_72b = Model(
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name = 'qwen-2.5-72b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([Jmuz, HuggingSpace])
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)
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qwen_2_5_coder_32b = Model(
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name = 'qwen-2.5-coder-32b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([Jmuz, PollinationsAI, AutonomousAI, DeepInfraChat, HuggingChat])
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)
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qwq_32b = Model(
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name = 'qwq-32b',
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base_provider = 'Qwen',
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best_provider = IterListProvider([Blackbox, Jmuz, HuggingSpace, DeepInfraChat, HuggingChat])
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)
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### Inflection ###
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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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### DeepSeek ###
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deepseek_chat = Model(
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name = 'deepseek-chat',
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base_provider = 'DeepSeek',
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best_provider = IterListProvider([Blackbox, Jmuz, PollinationsAI])
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)
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deepseek_coder = Model(
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name = 'deepseek-coder',
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base_provider = 'DeepSeek',
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best_provider = Airforce
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)
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### WizardLM ###
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wizardlm_2_8x22b = Model(
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name = 'wizardlm-2-8x22b',
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base_provider = 'WizardLM',
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best_provider = IterListProvider([Jmuz, DeepInfraChat])
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)
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### OpenChat ###
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openchat_3_5 = Model(
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name = 'openchat-3.5',
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base_provider = 'OpenChat',
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best_provider = Airforce
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)
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### x.ai ###
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grok_2 = Model(
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name = 'grok-2',
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base_provider = 'x.ai',
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best_provider = Liaobots
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)
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### Perplexity AI ###
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sonar_online = Model(
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name = 'sonar-online',
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base_provider = 'Perplexity AI',
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best_provider = PerplexityLabs
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)
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sonar_chat = Model(
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name = 'sonar-chat',
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base_provider = 'Perplexity AI',
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best_provider = PerplexityLabs
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)
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### Nvidia ###
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nemotron_70b = Model(
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name = 'nemotron-70b',
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base_provider = 'Nvidia',
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best_provider = IterListProvider([DeepInfraChat, HuggingChat, HuggingFace])
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)
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### Teknium ###
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openhermes_2_5 = Model(
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name = 'openhermes-2.5',
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base_provider = 'Teknium',
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best_provider = Airforce
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)
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### Liquid ###
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lfm_40b = Model(
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name = 'lfm-40b',
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base_provider = 'Liquid',
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best_provider = IterListProvider([Airforce, PerplexityLabs])
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)
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### DiscoResearch ###
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german_7b = Model(
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name = 'german-7b',
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base_provider = 'DiscoResearch',
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best_provider = Airforce
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)
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### HuggingFaceH4 ###
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zephyr_7b = Model(
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name = 'zephyr-7b',
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base_provider = 'HuggingFaceH4',
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best_provider = Airforce
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)
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### Inferless ###
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neural_7b = Model(
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name = 'neural-7b',
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base_provider = 'Inferless',
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best_provider = Airforce
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)
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### Databricks ###
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dbrx_instruct = Model(
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name = 'dbrx-instruct',
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base_provider = 'Databricks',
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best_provider = Blackbox
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)
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### PollinationsAI ###
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p1 = Model(
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name = 'p1',
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base_provider = 'PollinationsAI',
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best_provider = PollinationsAI
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)
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### CablyAI ###
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cably_80b = Model(
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name = 'cably-80b',
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base_provider = 'CablyAI',
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best_provider = CablyAI
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)
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### THUDM ###
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glm_4 = Model(
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name = 'glm-4',
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base_provider = 'THUDM',
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best_provider = ChatGLM
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)
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### Uncensored AI ###
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evil = Model(
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name = 'evil',
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base_provider = 'Evil Mode - Experimental',
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best_provider = IterListProvider([PollinationsAI, Airforce])
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)
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### Other ###
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midijourney = Model(
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name = 'midijourney',
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base_provider = 'Other',
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best_provider = PollinationsAI
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)
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turbo = Model(
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name = 'turbo',
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base_provider = 'Other',
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best_provider = PollinationsAI
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)
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unity = Model(
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name = 'unity',
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base_provider = 'Other',
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best_provider = PollinationsAI
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)
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rtist = Model(
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name = 'rtist',
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base_provider = 'Other',
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best_provider = PollinationsAI
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)
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|
#############
|
|
### Image ###
|
|
#############
|
|
|
|
### Stability AI ###
|
|
sdxl = ImageModel(
|
|
name = 'sdxl',
|
|
base_provider = 'Stability AI',
|
|
best_provider = IterListProvider([ReplicateHome, Airforce])
|
|
|
|
)
|
|
|
|
sd_3 = ImageModel(
|
|
name = 'sd-3',
|
|
base_provider = 'Stability AI',
|
|
best_provider = ReplicateHome
|
|
)
|
|
|
|
sd_3_5 = ImageModel(
|
|
name = 'sd-3.5',
|
|
base_provider = 'Stability AI',
|
|
best_provider = HuggingSpace
|
|
)
|
|
|
|
### Playground ###
|
|
playground_v2_5 = ImageModel(
|
|
name = 'playground-v2.5',
|
|
base_provider = 'Playground AI',
|
|
best_provider = ReplicateHome
|
|
)
|
|
|
|
### Flux AI ###
|
|
flux = ImageModel(
|
|
name = 'flux',
|
|
base_provider = 'Flux AI',
|
|
best_provider = IterListProvider([Blackbox, BlackboxCreateAgent, PollinationsAI, Airforce])
|
|
)
|
|
|
|
flux_pro = ImageModel(
|
|
name = 'flux-pro',
|
|
base_provider = 'Flux AI',
|
|
best_provider = IterListProvider([PollinationsAI, Airforce])
|
|
)
|
|
|
|
flux_dev = ImageModel(
|
|
name = 'flux-dev',
|
|
base_provider = 'Flux AI',
|
|
best_provider = IterListProvider([HuggingSpace, HuggingChat, HuggingFace])
|
|
)
|
|
|
|
flux_schnell = ImageModel(
|
|
name = 'flux-schnell',
|
|
base_provider = 'Flux AI',
|
|
best_provider = IterListProvider([HuggingSpace, HuggingFace])
|
|
)
|
|
|
|
flux_realism = ImageModel(
|
|
name = 'flux-realism',
|
|
base_provider = 'Flux AI',
|
|
best_provider = IterListProvider([PollinationsAI, Airforce])
|
|
)
|
|
|
|
flux_cablyai = ImageModel(
|
|
name = 'flux-cablyai',
|
|
base_provider = 'Flux AI',
|
|
best_provider = PollinationsAI
|
|
)
|
|
|
|
flux_anime = ImageModel(
|
|
name = 'flux-anime',
|
|
base_provider = 'Flux AI',
|
|
best_provider = IterListProvider([PollinationsAI, Airforce])
|
|
)
|
|
|
|
flux_3d = ImageModel(
|
|
name = 'flux-3d',
|
|
base_provider = 'Flux AI',
|
|
best_provider = IterListProvider([PollinationsAI, Airforce])
|
|
)
|
|
|
|
flux_disney = ImageModel(
|
|
name = 'flux-disney',
|
|
base_provider = 'Flux AI',
|
|
best_provider = Airforce
|
|
)
|
|
|
|
flux_pixel = ImageModel(
|
|
name = 'flux-pixel',
|
|
base_provider = 'Flux AI',
|
|
best_provider = Airforce
|
|
)
|
|
|
|
flux_4o = ImageModel(
|
|
name = 'flux-4o',
|
|
base_provider = 'Flux AI',
|
|
best_provider = Airforce
|
|
)
|
|
|
|
### OpenAI ###
|
|
dall_e_3 = ImageModel(
|
|
name = 'dall-e-3',
|
|
base_provider = 'OpenAI',
|
|
best_provider = IterListProvider([Airforce, PollinationsAI, CopilotAccount, OpenaiAccount, MicrosoftDesigner, BingCreateImages])
|
|
)
|
|
|
|
### Midjourney ###
|
|
midjourney = ImageModel(
|
|
name = 'midjourney',
|
|
base_provider = 'Midjourney',
|
|
best_provider = IterListProvider([PollinationsAI, Airforce])
|
|
)
|
|
|
|
### Other ###
|
|
any_dark = ImageModel(
|
|
name = 'any-dark',
|
|
base_provider = 'Other',
|
|
best_provider = IterListProvider([PollinationsAI, Airforce])
|
|
)
|
|
|
|
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
|
|
'gpt-3': gpt_35_turbo,
|
|
|
|
# gpt-3.5
|
|
gpt_35_turbo.name: gpt_35_turbo,
|
|
|
|
# gpt-4
|
|
gpt_4.name: gpt_4,
|
|
|
|
# gpt-4o
|
|
gpt_4o.name: gpt_4o,
|
|
gpt_4o_mini.name: gpt_4o_mini,
|
|
|
|
# o1
|
|
o1.name: o1,
|
|
o1_preview.name: o1_preview,
|
|
o1_mini.name: o1_mini,
|
|
|
|
### Meta ###
|
|
meta.name: meta,
|
|
|
|
# llama-2
|
|
llama_2_7b.name: llama_2_7b,
|
|
|
|
# llama-3
|
|
llama_3_8b.name: llama_3_8b,
|
|
|
|
# llama-3.1
|
|
llama_3_1_8b.name: llama_3_1_8b,
|
|
llama_3_1_70b.name: llama_3_1_70b,
|
|
llama_3_1_405b.name: llama_3_1_405b,
|
|
|
|
# llama-3.2
|
|
llama_3_2_1b.name: llama_3_2_1b,
|
|
llama_3_2_3b.name: llama_3_2_3b,
|
|
llama_3_2_11b.name: llama_3_2_11b,
|
|
llama_3_2_90b.name: llama_3_2_90b,
|
|
|
|
# llama-3.3
|
|
llama_3_3_70b.name: llama_3_3_70b,
|
|
|
|
### Mistral ###
|
|
mixtral_7b.name: mixtral_7b,
|
|
mixtral_8x7b.name: mixtral_8x7b,
|
|
mistral_nemo.name: mistral_nemo,
|
|
mistral_large.name: mistral_large,
|
|
|
|
### NousResearch ###
|
|
hermes_2_dpo.name: hermes_2_dpo,
|
|
hermes_2_pro.name: hermes_2_pro,
|
|
hermes_3.name: hermes_3,
|
|
|
|
### Microsoft ###
|
|
phi_2.name: phi_2,
|
|
phi_3_5_mini.name: phi_3_5_mini,
|
|
|
|
### Google ###
|
|
# gemini
|
|
gemini.name: gemini,
|
|
|
|
# gemini-1.5
|
|
gemini_1_5_pro.name: gemini_1_5_pro,
|
|
gemini_1_5_flash.name: gemini_1_5_flash,
|
|
|
|
# gemini-2.0
|
|
gemini_2_0_flash.name: gemini_2_0_flash,
|
|
gemini_2_0_flash_thinking.name: gemini_2_0_flash_thinking,
|
|
|
|
# gemma
|
|
gemma_2b.name: gemma_2b,
|
|
|
|
### Anthropic ###
|
|
# claude 3
|
|
claude_3_opus.name: claude_3_opus,
|
|
claude_3_sonnet.name: claude_3_sonnet,
|
|
claude_3_haiku.name: claude_3_haiku,
|
|
|
|
# claude 3.5
|
|
claude_3_5_sonnet.name: claude_3_5_sonnet,
|
|
|
|
### Reka AI ###
|
|
reka_core.name: reka_core,
|
|
|
|
### Blackbox AI ###
|
|
blackboxai.name: blackboxai,
|
|
blackboxai_pro.name: blackboxai_pro,
|
|
|
|
### CohereForAI ###
|
|
command_r_plus.name: command_r_plus,
|
|
command_r.name: command_r,
|
|
|
|
### GigaChat ###
|
|
gigachat.name: gigachat,
|
|
|
|
### Qwen ###
|
|
# qwen 1_5
|
|
qwen_1_5_7b.name: qwen_1_5_7b,
|
|
|
|
# qwen 2
|
|
qwen_2_72b.name: qwen_2_72b,
|
|
|
|
# qwen 2.5
|
|
qwen_2_5_72b.name: qwen_2_5_72b,
|
|
qwen_2_5_coder_32b.name: qwen_2_5_coder_32b,
|
|
qwq_32b.name: qwq_32b,
|
|
|
|
### Inflection ###
|
|
pi.name: pi,
|
|
|
|
### WizardLM ###
|
|
wizardlm_2_8x22b.name: wizardlm_2_8x22b,
|
|
|
|
### OpenChat ###
|
|
openchat_3_5.name: openchat_3_5,
|
|
|
|
### x.ai ###
|
|
grok_2.name: grok_2,
|
|
|
|
### Perplexity AI ###
|
|
sonar_online.name: sonar_online,
|
|
sonar_chat.name: sonar_chat,
|
|
|
|
### DeepSeek ###
|
|
deepseek_chat.name: deepseek_chat,
|
|
deepseek_coder.name: deepseek_coder,
|
|
|
|
### TheBloke ###
|
|
german_7b.name: german_7b,
|
|
|
|
### Nvidia ###
|
|
nemotron_70b.name: nemotron_70b,
|
|
|
|
### Teknium ###
|
|
openhermes_2_5.name: openhermes_2_5,
|
|
|
|
### Liquid ###
|
|
lfm_40b.name: lfm_40b,
|
|
|
|
### HuggingFaceH4 ###
|
|
zephyr_7b.name: zephyr_7b,
|
|
|
|
### Inferless ###
|
|
neural_7b.name: neural_7b,
|
|
|
|
### Databricks ###
|
|
dbrx_instruct.name: dbrx_instruct,
|
|
|
|
### PollinationsAI ###
|
|
p1.name: p1,
|
|
|
|
### CablyAI ###
|
|
cably_80b.name: cably_80b,
|
|
|
|
### THUDM ###
|
|
glm_4.name: glm_4,
|
|
|
|
### Uncensored AI ###
|
|
evil.name: evil,
|
|
|
|
### Other ###
|
|
midijourney.name: midijourney,
|
|
turbo.name: turbo,
|
|
unity.name: unity,
|
|
rtist.name: rtist,
|
|
|
|
#############
|
|
### Image ###
|
|
#############
|
|
|
|
### Stability AI ###
|
|
sdxl.name: sdxl,
|
|
sd_3.name: sd_3,
|
|
sd_3_5.name: sd_3_5,
|
|
|
|
### Playground ###
|
|
playground_v2_5.name: playground_v2_5,
|
|
|
|
### Flux AI ###
|
|
flux.name: flux,
|
|
flux_pro.name: flux_pro,
|
|
flux_dev.name: flux_dev,
|
|
flux_schnell.name: flux_schnell,
|
|
flux_realism.name: flux_realism,
|
|
flux_cablyai.name: flux_cablyai,
|
|
flux_anime.name: flux_anime,
|
|
flux_3d.name: flux_3d,
|
|
flux_disney.name: flux_disney,
|
|
flux_pixel.name: flux_pixel,
|
|
flux_4o.name: flux_4o,
|
|
|
|
### OpenAI ###
|
|
dall_e_3.name: dall_e_3,
|
|
|
|
### Midjourney ###
|
|
midjourney.name: midjourney,
|
|
|
|
### Other ###
|
|
any_dark.name: any_dark,
|
|
}
|
|
|
|
# Create a list of all models and his providers
|
|
__models__ = {
|
|
model.name: (model, providers)
|
|
for model, providers in [
|
|
(model, [provider for provider in model.best_provider.providers if provider.working]
|
|
if isinstance(model.best_provider, IterListProvider)
|
|
else [model.best_provider]
|
|
if model.best_provider is not None and model.best_provider.working
|
|
else [])
|
|
for model in ModelUtils.convert.values()]
|
|
if providers
|
|
}
|
|
_all_models = list(__models__.keys())
|