mirror of
https://github.com/blakeblackshear/frigate.git
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63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
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from enum import Enum
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from typing import Optional, Union
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from pydantic import BaseModel, Field, field_validator
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from ..base import FrigateBaseModel
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from ..env import EnvString
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__all__ = ["GenAIConfig", "GenAICameraConfig", "GenAIProviderEnum"]
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class GenAIProviderEnum(str, Enum):
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openai = "openai"
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gemini = "gemini"
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ollama = "ollama"
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# uses BaseModel because some global attributes are not available at the camera level
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class GenAICameraConfig(BaseModel):
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enabled: bool = Field(default=False, title="Enable GenAI for camera.")
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prompt: str = Field(
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default="Describe the {label} in the sequence of images with as much detail as possible. Do not describe the background.",
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title="Default caption prompt.",
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)
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object_prompts: dict[str, str] = Field(
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default_factory=dict, title="Object specific prompts."
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)
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objects: Union[str, list[str]] = Field(
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default_factory=list,
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title="List of objects to run generative AI for.",
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)
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required_zones: Union[str, list[str]] = Field(
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default_factory=list,
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title="List of required zones to be entered in order to run generative AI.",
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)
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@field_validator("required_zones", mode="before")
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@classmethod
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def validate_required_zones(cls, v):
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if isinstance(v, str) and "," not in v:
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return [v]
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return v
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class GenAIConfig(FrigateBaseModel):
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enabled: bool = Field(default=False, title="Enable GenAI.")
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prompt: str = Field(
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default="Describe the {label} in the sequence of images with as much detail as possible. Do not describe the background.",
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title="Default caption prompt.",
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)
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object_prompts: dict[str, str] = Field(
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default_factory=dict, title="Object specific prompts."
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)
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api_key: Optional[EnvString] = Field(default=None, title="Provider API key.")
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base_url: Optional[str] = Field(default=None, title="Provider base url.")
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model: str = Field(default="gpt-4o", title="GenAI model.")
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provider: GenAIProviderEnum = Field(
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default=GenAIProviderEnum.openai, title="GenAI provider."
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)
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