mirror of
https://github.com/Skyvern-AI/skyvern.git
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59 lines
1.6 KiB
Python
59 lines
1.6 KiB
Python
from dataclasses import dataclass
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from typing import Any, Awaitable, Literal, Protocol
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from skyvern.forge.sdk.models import Step
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from skyvern.forge.sdk.settings_manager import SettingsManager
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@dataclass(frozen=True)
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class LLMConfig:
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model_name: str
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required_env_vars: list[str]
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supports_vision: bool
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def get_missing_env_vars(self) -> list[str]:
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missing_env_vars = []
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for env_var in self.required_env_vars:
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env_var_value = getattr(SettingsManager.get_settings(), env_var, None)
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if not env_var_value:
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missing_env_vars.append(env_var)
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return missing_env_vars
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@dataclass(frozen=True)
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class LLMRouterModelConfig:
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model_name: str
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# https://litellm.vercel.app/docs/routing
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litellm_params: dict[str, Any]
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tpm: int | None = None
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rpm: int | None = None
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@dataclass(frozen=True)
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class LLMRouterConfig(LLMConfig):
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model_list: list[LLMRouterModelConfig]
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redis_host: str
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redis_port: int
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main_model_group: str
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fallback_model_group: str | None = None
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routing_strategy: Literal[
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"simple-shuffle",
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"least-busy",
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"usage-based-routing",
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"latency-based-routing",
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] = "usage-based-routing"
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num_retries: int = 2
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retry_delay_seconds: int = 15
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set_verbose: bool = True
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class LLMAPIHandler(Protocol):
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def __call__(
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self,
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prompt: str,
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step: Step | None = None,
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screenshots: list[bytes] | None = None,
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parameters: dict[str, Any] | None = None,
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) -> Awaitable[dict[str, Any]]:
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...
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