Struct AgentBase 

pub struct AgentBase {

    pub upstream: Upstream,
    pub model: String,
    pub output_mode: OutputMode,
    pub synthetic_reasoning: Option<bool>,
    pub top_logprobs: Option<u64>,
    pub prefix_messages: Option<Vec<Message>>,
    pub post_system_prefix_messages: Option<Vec<Message>>,
    pub suffix_messages: Option<Vec<Message>>,
    pub mcp_servers: Option<McpServers>,
    pub frequency_penalty: Option<f64>,
    pub logit_bias: Option<IndexMap<String, i64>>,
    pub max_completion_tokens: Option<u64>,
    pub presence_penalty: Option<f64>,
    pub stop: Option<Stop>,
    pub temperature: Option<f64>,
    pub top_p: Option<f64>,
    pub max_tokens: Option<u64>,
    pub min_p: Option<f64>,
    pub provider: Option<Provider>,
    pub reasoning: Option<Reasoning>,
    pub repetition_penalty: Option<f64>,
    pub top_a: Option<f64>,
    pub top_k: Option<u64>,
    pub verbosity: Option<Verbosity>,
}

The base configuration for an OpenRouter Agent (without computed ID).

Fields

upstream: Upstream

The upstream provider marker.

model: String

The upstream language model identifier (e.g., "gpt-4", "claude-3-opus").

output_mode: OutputMode

The output mode for vector completions. Ignored for agent completions.

synthetic_reasoning: Option<bool>

Enable synthetic reasoning for non-reasoning LLMs.

Vector completions only. Ignored for agent completions.

top_logprobs: Option<u64>

Number of top log probabilities to return (2-20).

Vector completions only. Ignored for agent completions.

prefix_messages: Option<Vec<Message>>

Messages prepended to the user’s prompt.

post_system_prefix_messages: Option<Vec<Message>>

Messages inserted after the leading chain of system/developer messages.

suffix_messages: Option<Vec<Message>>

Messages appended after the user’s prompt.

mcp_servers: Option<McpServers>

MCP servers the agent can connect to.

frequency_penalty: Option<f64>

Penalizes tokens based on their frequency in the output so far (-2.0 to 2.0).

logit_bias: Option<IndexMap<String, i64>>

Token ID to bias mapping (-100 to 100). Positive values increase likelihood.

max_completion_tokens: Option<u64>

Maximum tokens in the completion.

presence_penalty: Option<f64>

Penalizes tokens based on their presence in the output so far (-2.0 to 2.0).

stop: Option<Stop>

Stop sequences that halt generation.

temperature: Option<f64>

Sampling temperature (0.0 to 2.0). Higher = more random.

top_p: Option<f64>

Nucleus sampling probability (0.0 to 1.0).

max_tokens: Option<u64>

Maximum tokens (OpenRouter variant of max_completion_tokens).

min_p: Option<f64>

Minimum probability threshold for sampling (0.0 to 1.0).

provider: Option<Provider>

Provider routing preferences.

reasoning: Option<Reasoning>

Reasoning/thinking configuration for supported models.

repetition_penalty: Option<f64>

Repetition penalty (0.0 to 2.0). Values > 1.0 penalize repetition.

top_a: Option<f64>

Top-a sampling parameter (0.0 to 1.0).

top_k: Option<u64>

Top-k sampling: only consider the k most likely tokens.

verbosity: Option<Verbosity>

Output verbosity hint for supported models.

Implementations

impl AgentBase

pub fn prepare(&mut self)

Normalizes the configuration for deterministic ID computation.

pub fn validate(&self) -> Result<(), String>

Validates the configuration.

pub fn merged_messages(&self, messages: Vec<Message>) -> Vec<Message>

Returns prefix messages, then the provided messages, then suffix messages.

pub fn id(&self) -> String

Computes the deterministic content-addressed ID.

Trait Implementations

impl<'arbitrary> Arbitrary<'arbitrary> for AgentBase

fn arbitrary(u: &mut Unstructured<'arbitrary>) -> Result<Self>

Generate an arbitrary value of Self from the given unstructured data.

fn arbitrary_take_rest(u: Unstructured<'arbitrary>) -> Result<Self>

Generate an arbitrary value of Self from the entirety of the given unstructured data.

fn size_hint(depth: usize) -> (usize, Option<usize>)

Get a size hint for how many bytes out of an Unstructured this type needs to construct itself.

fn try_size_hint( depth: usize, ) -> Result<(usize, Option<usize>), MaxRecursionReached>

Get a size hint for how many bytes out of an Unstructured this type needs to construct itself.

impl Clone for AgentBase

fn clone(&self) -> AgentBase

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for AgentBase

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

Formats the value using the given formatter.

impl Default for AgentBase

fn default() -> AgentBase

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for AgentBase

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl JsonSchema for AgentBase

fn schema_name() -> Cow<'static, str>

The name of the generated JSON Schema.

fn schema_id() -> Cow<'static, str>

Returns a string that uniquely identifies the schema produced by this type.

fn json_schema(generator: &mut SchemaGenerator) -> Schema

Generates a JSON Schema for this type.

fn inline_schema() -> bool

Whether JSON Schemas generated for this type should be included directly in parent schemas, rather than being re-used where possible using the $ref keyword.

impl PartialEq for AgentBase

fn eq(&self, other: &AgentBase) -> 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 AgentBase

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl TryFrom<AgentBase> for Agent

type Error = String

The type returned in the event of a conversion error.

fn try_from(base: AgentBase) -> Result<Self, Self::Error>

Performs the conversion.

impl StructuralPartialEq for AgentBase