Struct AiAgentInputTransforms 

pub struct AiAgentInputTransforms {

    pub provider: Option<Box<ProviderTransform>>,
    pub output_type: Option<Box<InputTransform>>,
    pub user_message: Option<Box<InputTransform>>,
    pub system_prompt: Option<Box<InputTransform>>,
    pub streaming: Option<Box<InputTransform>>,
    pub memory: Option<Box<MemoryTransform>>,
    pub memory_id: Option<Box<InputTransform>>,
    pub previous_messages: Option<Box<InputTransform>>,
    pub output_schema: Option<Box<InputTransform>>,
    pub user_attachments: Option<Box<InputTransform>>,
    pub enabled_tools: Option<Box<InputTransform>>,
    pub max_completion_tokens: Option<Box<InputTransform>>,
    pub temperature: Option<Box<InputTransform>>,
    pub max_iterations: Option<Box<InputTransform>>,
}

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

Fields

provider: Option<Box<ProviderTransform>>

output_type: Option<Box<InputTransform>>

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

user_message: Option<Box<InputTransform>>

The user’s prompt/message to the AI agent. Supports variable interpolation with flow.input syntax. Required unless memory is off and previous_messages supplies the prompt; image output always needs it.

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, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result

memory: Option<Box<MemoryTransform>>

memory_id: Option<Box<InputTransform>>

String. Names the memory this step reads and writes, overriding the memory id the run was started with (the chat conversation, an app chat session or the memory_id run parameter). Leave unset to use the run’s memory id. A fixed value shares one memory across every run; an expression such as flow_input.customer_id keeps one memory per key. When it evaluates to an empty value the agent runs without memory. Read only while memory is window: it is ignored when memory is off, and an older auto or manual memory reads neither history input.

previous_messages: Option<Box<InputTransform>>

Array of MemoryMessage. History supplied by the flow, sent between the system prompt and the user message. Read only while memory is off or absent: managed memory ignores it, and an older auto or manual memory reads neither history input.

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_attachments: Option<Box<InputTransform>>

Array of file references (images or PDFs) for the AI agent. Format: Array<{ bucket: string, key: string }> - S3 object references Example: [{ bucket: ‘my-bucket’, key: ‘documents/report.pdf’ }]

enabled_tools: Option<Box<InputTransform>>

Array of strings naming which of the tools configured in tools the agent may call this run. Leaving it unset carries every one of them; an empty array carries none. A tool is named as the model is shown it. An entry the model is shown nothing of is named by what identifies it instead: an MCP server by its resource path, carrying every tool it exposes (which of them stays that entry’s include_tools/exclude_tools), and a websearch entry by the reserved name ‘__wm_web_search’, whatever summary it carries (no tool may take that name). Example: [‘get_user’, ‘u/admin/github_mcp’, ‘__wm_web_search’]

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

max_iterations: Option<Box<InputTransform>>

Number. Limits how many times the agent can loop through reasoning and tool use. Range: 1-1000.

Implementations

impl AiAgentInputTransforms

pub fn new() -> AiAgentInputTransforms

Input parameters for the AI agent mapped to their values

Trait Implementations

impl Clone for AiAgentInputTransforms

fn clone(&self) -> Self

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() -> Self

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: &Self) -> bool

Equality operator ==.

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

Inequality operator !=.

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