Struct AiAgentInputTransforms 

pub struct AiAgentInputTransforms {
    pub provider: Box<ProviderTransform>,
    pub output_type: Box<InputTransform>,
    pub user_message: Box<InputTransform>,
    pub system_prompt: Option<Box<InputTransform>>,
    pub streaming: Option<Box<InputTransform>>,
    pub memory: Option<Box<MemoryTransform>>,
    pub output_schema: Option<Box<InputTransform>>,
    pub user_images: Option<Box<InputTransform>>,
    pub max_completion_tokens: Option<Box<InputTransform>>,
    pub temperature: Option<Box<InputTransform>>,
}

AiAgentInputTransforms : Input parameters for the AI agent mapped to their values

Fields

provider: Box<ProviderTransform>

output_type: Box<InputTransform>

Output format type. Valid values: ‘text’ (default) - plain text response, ‘image’ - image generation

user_message: Box<InputTransform>

The user’s prompt/message to the AI agent. Supports variable interpolation with flow.input syntax.

system_prompt: Option<Box<InputTransform>>

System instructions that guide the AI’s behavior, persona, and response style. Optional.

streaming: Option<Box<InputTransform>>

Boolean. If true, stream the AI response incrementally. Streaming events include: token_delta, tool_call, tool_call_arguments, tool_execution, tool_result

memory: Option<Box<MemoryTransform>>

output_schema: Option<Box<InputTransform>>

JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape. Supports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc. Example: { type: ‘object’, properties: { name: { type: ‘string’ }, age: { type: ‘integer’ } }, required: [‘name’] }

user_images: Option<Box<InputTransform>>

Array of image references for vision-capable models. Format: Array<{ bucket: string, key: string }> - S3 object references Example: [{ bucket: ‘my-bucket’, key: ‘images/photo.jpg’ }]

max_completion_tokens: Option<Box<InputTransform>>

Integer. Maximum number of tokens the AI will generate in its response. Range: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.

temperature: Option<Box<InputTransform>>

Float. Controls randomness/creativity of responses. Range: 0.0 to 2.0 (provider-dependent) - 0.0 = deterministic, focused responses - 0.7 = balanced (common default) - 1.0+ = more creative/random

Implementations

impl AiAgentInputTransforms

pub fn new( provider: ProviderTransform, output_type: InputTransform, user_message: InputTransform, ) -> AiAgentInputTransforms

Input parameters for the AI agent mapped to their values

Trait Implementations

impl Clone for AiAgentInputTransforms

fn clone(&self) -> AiAgentInputTransforms

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for AiAgentInputTransforms

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

Formats the value using the given formatter.

impl Default for AiAgentInputTransforms

fn default() -> AiAgentInputTransforms

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for AiAgentInputTransforms

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for AiAgentInputTransforms

fn eq(&self, other: &AiAgentInputTransforms) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for AiAgentInputTransforms

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for AiAgentInputTransforms