Struct NewModel 

pub struct NewModel {

    pub name: String,
    pub file_path: PathBuf,
    pub param_count_b: f64,
    pub architecture: Option<String>,
    pub quantization: Option<String>,
    pub context_length: Option<u64>,
    pub expert_count: Option<u32>,
    pub expert_used_count: Option<u32>,
    pub expert_shared_count: Option<u32>,
    pub metadata: HashMap<String, String>,
    pub added_at: DateTime<Utc>,
    pub hf_repo_id: Option<String>,
    pub hf_commit_sha: Option<String>,
    pub hf_filename: Option<String>,
    pub download_date: Option<DateTime<Utc>>,
    pub last_update_check: Option<DateTime<Utc>>,
    pub tags: Vec<String>,
    pub file_paths: Option<Vec<PathBuf>>,
    pub capabilities: ModelCapabilities,
    pub inference_defaults: Option<InferenceConfig>,
    pub defaults_origin: Option<DefaultsOrigin>,
    pub server_defaults: Option<ServerConfig>,
}

A model to be inserted into the system (no ID yet).

This represents a model that hasn’t been persisted to the database. After insertion, the repository returns a Model with the assigned ID.

Fields

name: String

Human-readable name for the model.

file_path: PathBuf

Absolute path to the GGUF file on the filesystem.

param_count_b: f64

Number of parameters in the model (in billions).

architecture: Option<String>

Model architecture (e.g., “llama”, “mistral”, “falcon”).

quantization: Option<String>

Quantization type (e.g., “Q4_0”, “Q8_0”, “F16”, “F32”).

context_length: Option<u64>

Maximum context length the model supports.

expert_count: Option<u32>

Number of experts (for MoE models).

expert_used_count: Option<u32>

Number of experts used during inference (for MoE models).

expert_shared_count: Option<u32>

Number of shared experts (for MoE models).

metadata: HashMap<String, String>

Additional metadata key-value pairs from the GGUF file.

added_at: DateTime<Utc>

UTC timestamp of when the model was added to the database.

hf_repo_id: Option<String>

HuggingFace repository ID (e.g., “TheBloke/Llama-2-7B-GGUF”).

hf_commit_sha: Option<String>

Git commit SHA from HuggingFace Hub.

hf_filename: Option<String>

Original filename on HuggingFace Hub.

download_date: Option<DateTime<Utc>>

Timestamp of when this model was downloaded from HuggingFace.

last_update_check: Option<DateTime<Utc>>

Last time we checked for updates on HuggingFace.

tags: Vec<String>

User-defined tags for organizing models.

file_paths: Option<Vec<PathBuf>>

Ordered list of all file paths for sharded models (None for single-file models).

capabilities: ModelCapabilities

Model capabilities inferred from chat template analysis.

inference_defaults: Option<InferenceConfig>

Per-model inference parameter defaults.

These are preferred over global settings when making inference requests. If not set, falls back to global settings or hardcoded defaults.

defaults_origin: Option<DefaultsOrigin>

See Model::defaults_origin.

server_defaults: Option<ServerConfig>

Per-model server startup defaults.

Implementations

impl NewModel

pub fn new( name: String, file_path: PathBuf, param_count_b: f64, added_at: DateTime<Utc>, ) -> Self

Create a new model with minimal required fields.

Other fields are set to None or empty defaults.

Trait Implementations

impl Clone for NewModel

fn clone(&self) -> NewModel

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NewModel

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for NewModel

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for NewModel

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

where __S: Serializer,

Serialize this value into the given Serde serializer.