wehub-resource-sync
329 lines
8.7 KiB
Python
329 lines
8.7 KiB
Python
from dataclasses import dataclass
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from typing import Literal, TypedDict
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from openai.types import AudioModel
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STTModels = AudioModel
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TTSModels = Literal["tts-1", "tts-1-hd", "gpt-4o-mini-tts"]
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TTSVoices = Literal[
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"alloy",
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"ash",
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"ballad",
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"coral",
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"echo",
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"fable",
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"onyx",
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"nova",
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"sage",
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"shimmer",
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]
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DalleModels = Literal["dall-e-2", "dall-e-3"]
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ChatModels = Literal[
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"gpt-5.4",
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"gpt-5.4-mini",
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"gpt-5.3-chat-latest",
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"gpt-5.2",
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"gpt-5.2-chat-latest",
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"gpt-5.1",
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"gpt-5.1-chat-latest",
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"gpt-5",
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"gpt-5-chat-latest",
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"gpt-5-mini",
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"gpt-5-nano",
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"gpt-4.1",
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"gpt-4.1-mini",
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"gpt-4.1-nano",
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"gpt-4o",
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"gpt-4o-2024-05-13",
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"gpt-4o-mini",
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"gpt-4o-mini-2024-07-18",
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"gpt-4-turbo",
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"gpt-4-turbo-2024-04-09",
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"gpt-4-turbo-preview",
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"gpt-4-0125-preview",
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"gpt-4-1106-preview",
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"gpt-4-vision-preview",
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"gpt-4-1106-vision-preview",
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"gpt-4",
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"gpt-4-0314",
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"gpt-4-0613",
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"gpt-4-32k",
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"gpt-4-32k-0314",
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"gpt-4-32k-0613",
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"gpt-3.5-turbo",
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"gpt-3.5-turbo-16k",
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"gpt-3.5-turbo-0301",
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"gpt-3.5-turbo-0613",
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"gpt-3.5-turbo-1106",
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"gpt-3.5-turbo-16k-0613",
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]
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RealtimeModels = Literal[
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"gpt-realtime",
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"gpt-realtime-1.5",
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"gpt-realtime-2",
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"gpt-realtime-2025-08-28",
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"gpt-4o-realtime-preview",
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]
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EmbeddingModels = Literal[
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"text-embedding-ada-002", "text-embedding-3-small", "text-embedding-3-large"
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]
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AssistantTools = Literal["code_interpreter", "file_search", "function"]
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# adapters for OpenAI-compatible LLMs
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TelnyxChatModels = Literal[
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"meta-llama/Meta-Llama-3.1-8B-Instruct",
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"meta-llama/Meta-Llama-3.1-70B-Instruct",
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]
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NebiusChatModels = Literal[
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"meta-llama/Meta-Llama-3.1-70B-Instruct",
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"meta-llama/Llama-3.3-70B-Instruct",
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"meta-llama/Llama-3.3-8B-Instruct",
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"meta-llama/Meta-Llama-3.1-405B-Instruct",
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"openai/gpt-oss-120b",
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"openai/gpt-oss-20b",
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"moonshotai/Kimi-K2-Instruct",
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"Qwen/Qwen3-Coder-480B-A35B-Instruct",
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"NousResearch/Hermes-4-405B",
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"NousResearch/Hermes-4-70B",
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"zai-org/GLM-4.5",
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"zai-org/GLM-4.5-Air",
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"deepseek-ai/DeepSeek-R1-0528",
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"deepseek-ai/DeepSeek-R1",
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"deepseek-ai/DeepSeek-V3",
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"deepseek-ai/DeepSeek-V3-0324",
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"Qwen/Qwen3-235B-A22B-Instruct-2507",
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"Qwen/Qwen3-235B-A22B",
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"Qwen/Qwen3-32B",
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"Qwen/Qwen3-30B-A3B",
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"Qwen/Qwen3-4B-fast",
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"Qwen/Qwen3-14B",
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"Qwen/Qwen2.5-Coder-7B",
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"Qwen/Qwen2.5-Coder-32B-Instruct",
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"nvidia/Llama-3_1-Nemotron-Ultra-253B-v1",
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"mistralai/Mistral-Nemo-Instruct-2407",
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"google/gemma-2-2b-it",
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]
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CerebrasChatModels = Literal[
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"llama3.1-8b",
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"llama-3.3-70b",
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"llama-4-scout-17b-16e-instruct",
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"llama-4-maverick-17b-128e-instruct",
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"qwen-3-32b",
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"qwen-3-235b-a22b-instruct-2507",
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"qwen-3-235b-a22b-thinking-2507",
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"qwen-3-coder-480b",
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"gpt-oss-120b",
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]
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PerplexityChatModels = Literal[
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"llama-3.1-sonar-small-128k-online",
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"llama-3.1-sonar-small-128k-chat",
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"llama-3.1-sonar-large-128k-online",
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"llama-3.1-sonar-large-128k-chat",
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"llama-3.1-8b-instruct",
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"llama-3.1-70b-instruct",
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]
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DeepSeekChatModels = Literal[
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"deepseek-coder",
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"deepseek-chat",
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]
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CometAPIChatModels = Literal[
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# GPT series
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"gpt-5-chat-latest",
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"gpt-5",
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"gpt-5-pro",
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"gpt-5-nano",
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"gpt-4.1",
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"gpt-4o-mini",
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"o4-mini-2025-04-16",
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"o3-pro-2025-06-10",
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"chatgpt-4o-latest",
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# Claude series
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"claude-sonnet-4-5-20250929",
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"claude-opus-4-1-20250805",
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"claude-opus-4-1-20250805-thinking",
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"claude-sonnet-4-20250514",
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"claude-sonnet-4-20250514-thinking",
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"claude-3-7-sonnet-latest",
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"claude-3-5-haiku-latest",
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# Gemini series
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"gemini-2.5-pro",
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"gemini-2.5-flash",
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"gemini-2.5-flash-lite",
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"gemini-2.0-flash",
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# Grok series
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"grok-4-0709",
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"grok-4-fast-non-reasoning",
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"grok-4-fast-reasoning",
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# DeepSeek series
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"deepseek-v3.1",
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"deepseek-v3",
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"deepseek-r1-0528",
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"deepseek-chat",
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"deepseek-reasoner",
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# Qwen series
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"qwen3-30b-a3b",
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"qwen3-coder-plus-2025-07-22",
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]
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VertexModels = Literal[
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"google/gemini-2.0-flash-exp",
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"google/gemini-1.5-flash",
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"google/gemini-1.5-pro",
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"google/gemini-1.0-pro-vision",
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"google/gemini-1.0-pro-vision-001",
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"google/gemini-1.0-pro-002",
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"google/gemini-1.0-pro-001",
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"google/gemini-1.0-pro",
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]
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TogetherChatModels = Literal[
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"Austism/chronos-hermes-13b",
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"Gryphe/MythoMax-L2-13b",
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"NousResearch/Nous-Capybara-7B-V1p9",
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"NousResearch/Nous-Hermes-2-Mistral-7B-DPO",
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"NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
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"NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT",
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"NousResearch/Nous-Hermes-2-Yi-34B",
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"NousResearch/Nous-Hermes-Llama2-13b",
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"NousResearch/Nous-Hermes-llama-2-7b",
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"Open-Orca/Mistral-7B-OpenOrca",
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"Qwen/Qwen1.5-0.5B-Chat",
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"Qwen/Qwen1.5-1.8B-Chat",
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"Qwen/Qwen1.5-110B-Chat",
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"Qwen/Qwen1.5-14B-Chat",
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"Qwen/Qwen1.5-32B-Chat",
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"Qwen/Qwen1.5-4B-Chat",
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"Qwen/Qwen1.5-72B-Chat",
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"Qwen/Qwen1.5-7B-Chat",
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"Qwen/Qwen2-72B-Instruct",
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"Snowflake/snowflake-arctic-instruct",
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"Undi95/ReMM-SLERP-L2-13B",
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"Undi95/Toppy-M-7B",
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"WizardLM/WizardLM-13B-V1.2",
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"allenai/OLMo-7B",
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"allenai/OLMo-7B-Instruct",
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"allenai/OLMo-7B-Twin-2T",
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"codellama/CodeLlama-13b-Instruct-hf",
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"codellama/CodeLlama-34b-Instruct-hf",
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"codellama/CodeLlama-70b-Instruct-hf",
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"codellama/CodeLlama-7b-Instruct-hf",
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"cognitivecomputations/dolphin-2.5-mixtral-8x7b",
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"databricks/dbrx-instruct",
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"deepseek-ai/deepseek-coder-33b-instruct",
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"deepseek-ai/deepseek-llm-67b-chat",
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"garage-bAInd/Platypus2-70B-instruct",
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"google/gemma-2-27b-it",
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"google/gemma-2-9b-it",
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"google/gemma-2b-it",
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"google/gemma-7b-it",
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"lmsys/vicuna-13b-v1.5",
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"lmsys/vicuna-7b-v1.5",
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"meta-llama/Llama-2-13b-chat-hf",
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"meta-llama/Llama-2-70b-chat-hf",
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"meta-llama/Llama-2-7b-chat-hf",
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"meta-llama/Llama-3-70b-chat-hf",
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"meta-llama/Llama-3-8b-chat-hf",
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"meta-llama/Meta-Llama-3-70B-Instruct-Lite",
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"meta-llama/Meta-Llama-3-70B-Instruct-Turbo",
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"meta-llama/Meta-Llama-3-8B-Instruct-Lite",
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"meta-llama/Meta-Llama-3-8B-Instruct-Turbo",
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"meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
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"meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
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"meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
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"meta-llama/Llama-3.3-70B-Instruct-Turbo",
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"mistralai/Mistral-7B-Instruct-v0.1",
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"mistralai/Mistral-7B-Instruct-v0.2",
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"mistralai/Mistral-7B-Instruct-v0.3",
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"mistralai/Mixtral-8x22B-Instruct-v0.1",
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"mistralai/Mixtral-8x7B-Instruct-v0.1",
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"openchat/openchat-3.5-1210",
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"snorkelai/Snorkel-Mistral-PairRM-DPO",
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"teknium/OpenHermes-2-Mistral-7B",
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"teknium/OpenHermes-2p5-Mistral-7B",
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"togethercomputer/Llama-2-7B-32K-Instruct",
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"togethercomputer/RedPajama-INCITE-7B-Chat",
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"togethercomputer/RedPajama-INCITE-Chat-3B-v1",
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"togethercomputer/StripedHyena-Nous-7B",
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"togethercomputer/alpaca-7b",
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"upstage/SOLAR-10.7B-Instruct-v1.0",
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"zero-one-ai/Yi-34B-Chat",
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]
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OctoChatModels = Literal[
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"meta-llama-3-70b-instruct",
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"meta-llama-3.1-405b-instruct",
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"meta-llama-3.1-70b-instruct",
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"meta-llama-3.1-8b-instruct",
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"mistral-7b-instruct",
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"mixtral-8x7b-instruct",
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"wizardlm-2-8x22bllamaguard-2-7b",
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]
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XAIChatModels = Literal[
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"grok-3",
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"grok-3-fast",
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"grok-3-mini",
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"grok-3-mini-fast",
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"grok-2-vision-1212",
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"grok-2-image-1212",
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"grok-2-1212",
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]
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SambaNovaChatModels = Literal[
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"DeepSeek-R1-0528",
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"DeepSeek-V3-0324",
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"DeepSeek-V3.1",
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"DeepSeek-R1-Distill-Llama-70B",
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"Meta-Llama-3.3-70B-Instruct",
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"Meta-Llama-3.1-8B-Instruct",
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"Llama-4-Maverick-17B-128E-Instruct",
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"gpt-oss-120b",
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"Qwen3-235B-A22B-Instruct-2507",
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"Qwen3-32B",
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"Llama-3.3-Swallow-70B-Instruct-v0.4",
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"E5-Mistral-7B-Instruct",
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]
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def _supports_reasoning_effort(model: ChatModels | str) -> bool:
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return model in [
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"gpt-5.4",
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"gpt-5.4-mini",
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"gpt-5.2",
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"gpt-5.1",
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"gpt-5",
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"gpt-5-mini",
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"gpt-5-nano",
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]
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@dataclass
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class OpenRouterWebPlugin:
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"""OpenRouter web search plugin configuration"""
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max_results: int = 5
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search_prompt: str | None = None
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id: str = "web"
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class OpenRouterProviderPreferences(TypedDict, total=False):
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"""OpenRouter provider routing preferences."""
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order: list[str]
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allow_fallbacks: bool
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require_parameters: bool
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data_collection: Literal["allow", "deny"]
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only: list[str]
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ignore: list[str]
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quantizations: list[str]
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sort: Literal["price", "throughput", "latency"]
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max_price: dict[str, float]
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