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 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>,
}

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.

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.

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.