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			438 lines
		
	
	
		
			14 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			438 lines
		
	
	
		
			14 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
import base64
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import enum
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from collections.abc import Mapping
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from enum import Enum
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from typing import Any, Optional, Union
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from pydantic import BaseModel, ConfigDict, Field, ValidationInfo, field_serializer, field_validator, model_validator
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from core.entities.provider_entities import ProviderConfig
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from core.plugin.entities.parameters import (
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    PluginParameter,
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    PluginParameterOption,
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    PluginParameterType,
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    as_normal_type,
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    cast_parameter_value,
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    init_frontend_parameter,
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)
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from core.tools.entities.common_entities import I18nObject
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from core.tools.entities.constants import TOOL_SELECTOR_MODEL_IDENTITY
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class ToolLabelEnum(Enum):
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    SEARCH = "search"
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    IMAGE = "image"
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    VIDEOS = "videos"
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    WEATHER = "weather"
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    FINANCE = "finance"
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    DESIGN = "design"
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    TRAVEL = "travel"
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    SOCIAL = "social"
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    NEWS = "news"
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    MEDICAL = "medical"
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    PRODUCTIVITY = "productivity"
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    EDUCATION = "education"
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    BUSINESS = "business"
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    ENTERTAINMENT = "entertainment"
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    UTILITIES = "utilities"
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    OTHER = "other"
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class ToolProviderType(enum.StrEnum):
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    """
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    Enum class for tool provider
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    """
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    PLUGIN = "plugin"
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    BUILT_IN = "builtin"
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    WORKFLOW = "workflow"
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    API = "api"
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    APP = "app"
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    DATASET_RETRIEVAL = "dataset-retrieval"
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    @classmethod
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    def value_of(cls, value: str) -> "ToolProviderType":
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        """
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        Get value of given mode.
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        :param value: mode value
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        :return: mode
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        """
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        for mode in cls:
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            if mode.value == value:
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                return mode
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        raise ValueError(f"invalid mode value {value}")
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class ApiProviderSchemaType(Enum):
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    """
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    Enum class for api provider schema type.
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    """
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    OPENAPI = "openapi"
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    SWAGGER = "swagger"
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    OPENAI_PLUGIN = "openai_plugin"
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    OPENAI_ACTIONS = "openai_actions"
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    @classmethod
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    def value_of(cls, value: str) -> "ApiProviderSchemaType":
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        """
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        Get value of given mode.
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        :param value: mode value
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        :return: mode
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        """
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        for mode in cls:
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            if mode.value == value:
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                return mode
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        raise ValueError(f"invalid mode value {value}")
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class ApiProviderAuthType(Enum):
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    """
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    Enum class for api provider auth type.
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    """
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    NONE = "none"
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    API_KEY = "api_key"
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    @classmethod
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    def value_of(cls, value: str) -> "ApiProviderAuthType":
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        """
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        Get value of given mode.
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        :param value: mode value
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        :return: mode
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        """
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        for mode in cls:
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            if mode.value == value:
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                return mode
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        raise ValueError(f"invalid mode value {value}")
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class ToolInvokeMessage(BaseModel):
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    class TextMessage(BaseModel):
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        text: str
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    class JsonMessage(BaseModel):
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        json_object: dict
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    class BlobMessage(BaseModel):
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        blob: bytes
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    class BlobChunkMessage(BaseModel):
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        id: str = Field(..., description="The id of the blob")
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        sequence: int = Field(..., description="The sequence of the chunk")
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        total_length: int = Field(..., description="The total length of the blob")
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        blob: bytes = Field(..., description="The blob data of the chunk")
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        end: bool = Field(..., description="Whether the chunk is the last chunk")
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    class FileMessage(BaseModel):
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        pass
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    class VariableMessage(BaseModel):
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        variable_name: str = Field(..., description="The name of the variable")
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        variable_value: Any = Field(..., description="The value of the variable")
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        stream: bool = Field(default=False, description="Whether the variable is streamed")
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        @model_validator(mode="before")
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        @classmethod
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        def transform_variable_value(cls, values) -> Any:
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            """
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            Only basic types and lists are allowed.
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            """
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            value = values.get("variable_value")
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            if not isinstance(value, dict | list | str | int | float | bool):
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                raise ValueError("Only basic types and lists are allowed.")
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            # if stream is true, the value must be a string
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            if values.get("stream"):
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                if not isinstance(value, str):
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                    raise ValueError("When 'stream' is True, 'variable_value' must be a string.")
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            return values
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        @field_validator("variable_name", mode="before")
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        @classmethod
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        def transform_variable_name(cls, value: str) -> str:
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            """
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            The variable name must be a string.
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            """
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            if value in {"json", "text", "files"}:
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                raise ValueError(f"The variable name '{value}' is reserved.")
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            return value
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    class LogMessage(BaseModel):
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        class LogStatus(Enum):
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            START = "start"
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            ERROR = "error"
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            SUCCESS = "success"
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        id: str
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        label: str = Field(..., description="The label of the log")
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        parent_id: Optional[str] = Field(default=None, description="Leave empty for root log")
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        error: Optional[str] = Field(default=None, description="The error message")
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        status: LogStatus = Field(..., description="The status of the log")
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        data: Mapping[str, Any] = Field(..., description="Detailed log data")
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        metadata: Optional[Mapping[str, Any]] = Field(default=None, description="The metadata of the log")
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    class MessageType(Enum):
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        TEXT = "text"
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        IMAGE = "image"
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        LINK = "link"
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        BLOB = "blob"
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        JSON = "json"
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        IMAGE_LINK = "image_link"
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        BINARY_LINK = "binary_link"
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        VARIABLE = "variable"
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        FILE = "file"
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        LOG = "log"
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        BLOB_CHUNK = "blob_chunk"
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    type: MessageType = MessageType.TEXT
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    """
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        plain text, image url or link url
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    """
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    message: (
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        JsonMessage | TextMessage | BlobChunkMessage | BlobMessage | LogMessage | FileMessage | None | VariableMessage
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    )
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    meta: dict[str, Any] | None = None
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    @field_validator("message", mode="before")
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    @classmethod
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    def decode_blob_message(cls, v):
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        if isinstance(v, dict) and "blob" in v:
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            try:
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                v["blob"] = base64.b64decode(v["blob"])
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            except Exception:
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                pass
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        return v
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    @field_serializer("message")
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    def serialize_message(self, v):
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        if isinstance(v, self.BlobMessage):
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            return {"blob": base64.b64encode(v.blob).decode("utf-8")}
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        return v
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class ToolInvokeMessageBinary(BaseModel):
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    mimetype: str = Field(..., description="The mimetype of the binary")
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    url: str = Field(..., description="The url of the binary")
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    file_var: Optional[dict[str, Any]] = None
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class ToolParameter(PluginParameter):
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    """
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    Overrides type
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    """
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    class ToolParameterType(enum.StrEnum):
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        """
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        removes TOOLS_SELECTOR from PluginParameterType
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        """
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        STRING = PluginParameterType.STRING.value
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        NUMBER = PluginParameterType.NUMBER.value
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        BOOLEAN = PluginParameterType.BOOLEAN.value
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        SELECT = PluginParameterType.SELECT.value
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        SECRET_INPUT = PluginParameterType.SECRET_INPUT.value
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        FILE = PluginParameterType.FILE.value
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        FILES = PluginParameterType.FILES.value
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        APP_SELECTOR = PluginParameterType.APP_SELECTOR.value
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        MODEL_SELECTOR = PluginParameterType.MODEL_SELECTOR.value
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        # deprecated, should not use.
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        SYSTEM_FILES = PluginParameterType.SYSTEM_FILES.value
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        def as_normal_type(self):
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            return as_normal_type(self)
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        def cast_value(self, value: Any):
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            return cast_parameter_value(self, value)
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    class ToolParameterForm(Enum):
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        SCHEMA = "schema"  # should be set while adding tool
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        FORM = "form"  # should be set before invoking tool
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        LLM = "llm"  # will be set by LLM
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    type: ToolParameterType = Field(..., description="The type of the parameter")
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    human_description: Optional[I18nObject] = Field(default=None, description="The description presented to the user")
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    form: ToolParameterForm = Field(..., description="The form of the parameter, schema/form/llm")
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    llm_description: Optional[str] = None
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    @classmethod
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    def get_simple_instance(
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        cls,
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        name: str,
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        llm_description: str,
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        typ: ToolParameterType,
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        required: bool,
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        options: Optional[list[str]] = None,
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    ) -> "ToolParameter":
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        """
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        get a simple tool parameter
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        :param name: the name of the parameter
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        :param llm_description: the description presented to the LLM
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        :param typ: the type of the parameter
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        :param required: if the parameter is required
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        :param options: the options of the parameter
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        """
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        # convert options to ToolParameterOption
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        # FIXME fix the type error
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        if options:
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            option_objs = [
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                PluginParameterOption(value=option, label=I18nObject(en_US=option, zh_Hans=option))
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                for option in options
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            ]
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        else:
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            option_objs = []
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        return cls(
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            name=name,
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            label=I18nObject(en_US="", zh_Hans=""),
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            placeholder=None,
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            human_description=I18nObject(en_US="", zh_Hans=""),
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            type=typ,
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            form=cls.ToolParameterForm.LLM,
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            llm_description=llm_description,
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            required=required,
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            options=option_objs,
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        )
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    def init_frontend_parameter(self, value: Any):
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        return init_frontend_parameter(self, self.type, value)
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class ToolProviderIdentity(BaseModel):
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    author: str = Field(..., description="The author of the tool")
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    name: str = Field(..., description="The name of the tool")
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    description: I18nObject = Field(..., description="The description of the tool")
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    icon: str = Field(..., description="The icon of the tool")
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    label: I18nObject = Field(..., description="The label of the tool")
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    tags: Optional[list[ToolLabelEnum]] = Field(
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        default=[],
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        description="The tags of the tool",
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    )
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class ToolIdentity(BaseModel):
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    author: str = Field(..., description="The author of the tool")
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    name: str = Field(..., description="The name of the tool")
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    label: I18nObject = Field(..., description="The label of the tool")
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    provider: str = Field(..., description="The provider of the tool")
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    icon: Optional[str] = None
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class ToolDescription(BaseModel):
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    human: I18nObject = Field(..., description="The description presented to the user")
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    llm: str = Field(..., description="The description presented to the LLM")
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class ToolEntity(BaseModel):
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    identity: ToolIdentity
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    parameters: list[ToolParameter] = Field(default_factory=list)
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    description: Optional[ToolDescription] = None
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    output_schema: Optional[dict] = None
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    has_runtime_parameters: bool = Field(default=False, description="Whether the tool has runtime parameters")
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    # pydantic configs
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    model_config = ConfigDict(protected_namespaces=())
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    @field_validator("parameters", mode="before")
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    @classmethod
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    def set_parameters(cls, v, validation_info: ValidationInfo) -> list[ToolParameter]:
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        return v or []
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class ToolProviderEntity(BaseModel):
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    identity: ToolProviderIdentity
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    plugin_id: Optional[str] = None
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    credentials_schema: list[ProviderConfig] = Field(default_factory=list)
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class ToolProviderEntityWithPlugin(ToolProviderEntity):
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    tools: list[ToolEntity] = Field(default_factory=list)
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class WorkflowToolParameterConfiguration(BaseModel):
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    """
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    Workflow tool configuration
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    """
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    name: str = Field(..., description="The name of the parameter")
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    description: str = Field(..., description="The description of the parameter")
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    form: ToolParameter.ToolParameterForm = Field(..., description="The form of the parameter")
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class ToolInvokeMeta(BaseModel):
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    """
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    Tool invoke meta
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    """
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    time_cost: float = Field(..., description="The time cost of the tool invoke")
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    error: Optional[str] = None
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    tool_config: Optional[dict] = None
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    @classmethod
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    def empty(cls) -> "ToolInvokeMeta":
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        """
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        Get an empty instance of ToolInvokeMeta
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        """
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        return cls(time_cost=0.0, error=None, tool_config={})
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    @classmethod
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    def error_instance(cls, error: str) -> "ToolInvokeMeta":
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        """
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        Get an instance of ToolInvokeMeta with error
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        """
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        return cls(time_cost=0.0, error=error, tool_config={})
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    def to_dict(self) -> dict:
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        return {
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            "time_cost": self.time_cost,
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            "error": self.error,
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            "tool_config": self.tool_config,
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        }
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class ToolLabel(BaseModel):
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    """
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    Tool label
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    """
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    name: str = Field(..., description="The name of the tool")
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    label: I18nObject = Field(..., description="The label of the tool")
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    icon: str = Field(..., description="The icon of the tool")
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class ToolInvokeFrom(Enum):
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    """
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    Enum class for tool invoke
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    """
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    WORKFLOW = "workflow"
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    AGENT = "agent"
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    PLUGIN = "plugin"
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class ToolSelector(BaseModel):
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    dify_model_identity: str = TOOL_SELECTOR_MODEL_IDENTITY
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    class Parameter(BaseModel):
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        name: str = Field(..., description="The name of the parameter")
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        type: ToolParameter.ToolParameterType = Field(..., description="The type of the parameter")
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        required: bool = Field(..., description="Whether the parameter is required")
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        description: str = Field(..., description="The description of the parameter")
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        default: Optional[Union[int, float, str]] = None
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        options: Optional[list[PluginParameterOption]] = None
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    provider_id: str = Field(..., description="The id of the provider")
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    tool_name: str = Field(..., description="The name of the tool")
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    tool_description: str = Field(..., description="The description of the tool")
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    tool_configuration: Mapping[str, Any] = Field(..., description="Configuration, type form")
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    tool_parameters: Mapping[str, Parameter] = Field(..., description="Parameters, type llm")
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    def to_plugin_parameter(self) -> dict[str, Any]:
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        return self.model_dump()
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