Struct Settings 

pub struct Settings {

    pub default_download_path: Option<String>,
    pub default_context_size: Option<u64>,
    pub proxy_port: Option<u16>,
    pub llama_base_port: Option<u16>,
    pub max_download_queue_size: Option<u32>,
    pub show_memory_fit_indicators: Option<bool>,
    pub max_tool_iterations: Option<u32>,
    pub max_stagnation_steps: Option<u32>,
    pub default_model_id: Option<i64>,
    pub inference_defaults: Option<InferenceConfig>,
    pub inference_profiles: Option<Vec<InferenceProfile>>,
    pub setup_completed: Option<bool>,
    pub title_generation_prompt: Option<String>,
    pub bind_host: Option<String>,
    pub share_lan: Option<bool>,
    pub trust_client_sampling: Option<bool>,
}

Application settings structure.

All fields are optional to support partial updates and graceful defaults.

Fields

default_download_path: Option<String>

Default directory for downloading models.

default_context_size: Option<u64>

Default context size for models (e.g., 4096, 8192).

proxy_port: Option<u16>

Port for the OpenAI-compatible proxy server.

llama_base_port: Option<u16>

Base port for llama-server instance allocation (first port in range). Note: The OpenAI-compatible proxy listens on proxy_port.

max_download_queue_size: Option<u32>

Maximum number of downloads that can be queued (1-50).

show_memory_fit_indicators: Option<bool>

Whether to show memory fit indicators in HuggingFace browser.

max_tool_iterations: Option<u32>

Maximum iterations for tool calling agentic loop.

max_stagnation_steps: Option<u32>

Maximum stagnation steps before stopping agent loop.

default_model_id: Option<i64>

Default model ID for commands that support a default model.

inference_defaults: Option<InferenceConfig>

Global inference parameter defaults.

Applied when neither request nor per-model defaults are specified. If not set, hardcoded defaults are used as final fallback.

inference_profiles: Option<Vec<InferenceProfile>>

Named sampling profiles, selectable per request as {model}:{profile}.

Global rather than per-model: one coding profile applies to every model, and its sparse fields fall through to that model’s own inference_defaults for anything it does not set. See crate::domain::inference_profile.

setup_completed: Option<bool>

Whether the first-run setup wizard has been completed.

title_generation_prompt: Option<String>

Custom prompt template for generating chat titles.

bind_host: Option<String>

Override the bind host for gglib web.

None → use the compiled-in default (127.0.0.1). The --host flag takes precedence for a single run without changing this value.

share_lan: Option<bool>

Whether gglib web binds all LAN interfaces and broadcasts over mDNS.

None/Some(false) → localhost-only. The --share-lan flag can turn this on for a single run, but cannot turn it off — clear it here.

trust_client_sampling: Option<bool>

Whether a client’s own sampling parameters (temperature, top_p, top_k, presence_penalty, repeat_penalty, min_p) are honoured by the proxy at all.

None/Some(false) → the client’s sampling opinions are dropped from the resolution hierarchy entirely; the request falls straight through to the profile / per-model / global / floor layers as if the client had sent none of them. max_tokens is unaffected either way — it is a budget, not a taste, and a client that names one still gets it honoured; ignoring it would silently truncate that client’s own turns.

Defaults to distrust because most clients that talk to this proxy send fixed sampling values with no user-facing control behind them — boilerplate the client always sends, not a deliberate choice by whoever is using it (VS Code Copilot’s LLM Gateway hardcodes temperature: 0 on every request, for one). Letting that boilerplate silently outrank a model’s own tuned defaults and this server’s global settings defeats the point of configuring either. Set true for a client that does expose real sampling controls to its user (OpenWebUI’s sliders, for instance).

Implementations

impl Settings

pub const fn with_defaults() -> Self

Create settings with sensible defaults.

pub const fn effective_proxy_port(&self) -> u16

Get the effective proxy port (with default fallback).

pub const fn effective_llama_base_port(&self) -> u16

Get the effective llama-server base port (with default fallback).

pub fn merge(&mut self, other: &SettingsUpdate)

Merge another settings into this one, only updating fields that are Some.

Trait Implementations

impl Clone for Settings

fn clone(&self) -> Settings

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Settings

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

Formats the value using the given formatter.

impl Default for Settings

fn default() -> Settings

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Settings

where Settings: Default,

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for Settings

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

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 Settings