Struct PaladinData 

pub struct PaladinData {

    pub system_prompt: String,
    pub name: String,
    pub user_name: String,
    pub model: String,
    pub temperature: f32,
    pub max_loops: MaxLoops,
    pub stop_words: Vec<String>,
    pub status: PaladinStatus,
    pub vision_enabled: bool,
    pub autonomous_planning: bool,
    pub autonomous_prompts: bool,
    pub agent_description: String,
    pub dynamic_temperature: bool,
}

Core data payload for a Paladin entity

Contains all configuration and state information for an autonomous AI agent. This struct is wrapped in a Node<T> to provide UUID, timestamps, and versioning.

Fields

system_prompt: String

System prompt defining the Paladin’s behavior and personality

name: String

Display name for the Paladin

user_name: String

Name to use for the user in conversations

model: String

LLM model identifier (e.g., “gpt-4”, “claude-3”)

temperature: f32

Response randomness (0.0 = deterministic, 1.0 = maximum randomness)

max_loops: MaxLoops

Maximum iteration control (Fixed or Auto planning mode)

stop_words: Vec<String>

Tokens that signal the Paladin should stop processing

status: PaladinStatus

Current execution status

vision_enabled: bool

Whether vision capabilities are enabled for this Paladin

autonomous_planning: bool

Whether autonomous planning mode is enabled (Layer 1)

When true, the Paladin will use PlanningService to decompose complex tasks into subtasks before execution. Requires planning service to be configured in PaladinExecutionService.

autonomous_prompts: bool

Whether auto-generate system prompt is enabled (Layer 1)

When true, the Paladin will use PromptGenerationService to generate a contextual system prompt based on agent_description. Requires prompt generation service to be configured in PaladinExecutionService.

agent_description: String

Agent description used for autonomous prompt generation

Provides context for generating system prompts when autonomous_prompts is enabled. Should describe the agent’s role and capabilities.

dynamic_temperature: bool

Whether dynamic temperature adjustment is enabled (Layer 2)

When true, temperature increases linearly from the configured base value to 1.0 over the course of max_loops iterations. This encourages exploration in later loops when the agent might be stuck.

Trait Implementations

impl Clone for PaladinData

fn clone(&self) -> PaladinData

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for PaladinData

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl Default for PaladinData

fn default() -> PaladinData

Creates a PaladinData instance with sensible defaults.

Default Values

• system_prompt: Empty string (must be set before use)
• name: “Paladin”
• user_name: “User”
• model: “gpt-4”
• temperature: 0.7
• max_loops: MaxLoops::Fixed(3)
• stop_words: Empty vector
• status: Idle
• vision_enabled: false
• autonomous_planning: false
• autonomous_prompts: false
• agent_description: Empty string
• dynamic_temperature: false

impl<'de> Deserialize<'de> for PaladinData

fn deserialize<__D>( __deserializer: __D, ) -> Result<PaladinData, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for PaladinData

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.