Struct ModelCard 

pub struct ModelCard {

    pub id: String,
    pub display_name: Option<String>,
    pub aliases: Vec<String>,
    pub model_type: ModelType,
    pub hf_model_type: Option<String>,
    pub architectures: Vec<String>,
    pub provider: Option<ProviderType>,
    pub context_length: Option<u32>,
    pub tokenizer_path: Option<String>,
    pub chat_template: Option<String>,
    pub reasoning_parser: Option<String>,
    pub tool_parser: Option<String>,
    pub metadata: Option<Value>,
    pub id2label: HashMap<u32, String>,
    pub num_labels: u32,
}

Model card containing model configuration and capabilities.

Example

use openai_protocol::{model_type::ModelType, model_card::ModelCard, worker::ProviderType};

let card = ModelCard::new("meta-llama/Llama-3.1-8B-Instruct")
    .with_display_name("Llama 3.1 8B Instruct")
    .with_alias("llama-3.1-8b")
    .with_model_type(ModelType::VISION_LLM)
    .with_context_length(128_000)
    .with_tokenizer_path("meta-llama/Llama-3.1-8B-Instruct");

assert!(card.matches("llama-3.1-8b"));
assert!(card.model_type.supports_vision());
assert!(card.provider.is_none()); // Local model, no external provider

Fields

id: String

Primary model ID (e.g., “meta-llama/Llama-3.1-8B-Instruct”)

display_name: Option<String>

Optional display name (e.g., “Llama 3.1 8B Instruct”)

aliases: Vec<String>

Alternative names/aliases for this model

model_type: ModelType

Supported endpoint types (bitflags)

hf_model_type: Option<String>

HuggingFace model type string (e.g., “llama”, “qwen2”, “gpt-oss”)

architectures: Vec<String>

Model architectures from HuggingFace config (e.g., [“LlamaForCausalLM”])

provider: Option<ProviderType>

Provider hint for API transformations. None means native/passthrough (no transformation needed).

context_length: Option<u32>

Maximum context length in tokens

tokenizer_path: Option<String>

Path to tokenizer (e.g., HuggingFace model ID or local path)

chat_template: Option<String>

Chat template (Jinja2 template string or path)

reasoning_parser: Option<String>

Reasoning parser type (e.g., “deepseek”, “qwen”)

tool_parser: Option<String>

Tool/function calling parser type (e.g., “llama”, “mistral”)

metadata: Option<Value>

User-defined metadata (for fields not covered above)

id2label: HashMap<u32, String>

Classification label mapping (class index -> label name). Empty if not a classification model.

num_labels: u32

Number of classification labels (0 if not a classifier).

Implementations

impl ModelCard

pub fn new(id: impl Into<String>) -> Self

Create a new model card with minimal configuration.

Defaults to ModelType::LLM and no provider (native/passthrough).

pub fn with_display_name(self, name: impl Into<String>) -> Self

Set the display name

pub fn with_alias(self, alias: impl Into<String>) -> Self

Add a single alias

pub fn with_aliases( self, aliases: impl IntoIterator<Item = impl Into<String>>, ) -> Self

Add multiple aliases

pub fn with_model_type(self, model_type: ModelType) -> Self

Set the model type (capabilities)

pub fn with_hf_model_type(self, hf_model_type: impl Into<String>) -> Self

Set the HuggingFace model type string

pub fn with_architectures(self, architectures: Vec<String>) -> Self

Set the model architectures

pub fn with_provider(self, provider: ProviderType) -> Self

Set the provider type (for external API transformations)

pub fn with_context_length(self, length: u32) -> Self

Set the context length

pub fn with_tokenizer_path(self, path: impl Into<String>) -> Self

Set the tokenizer path

pub fn with_chat_template(self, template: impl Into<String>) -> Self

Set the chat template

pub fn with_reasoning_parser(self, parser: impl Into<String>) -> Self

Set the reasoning parser type

pub fn with_tool_parser(self, parser: impl Into<String>) -> Self

Set the tool parser type

pub fn with_metadata(self, metadata: Value) -> Self

Set custom metadata

pub fn with_id2label(self, id2label: HashMap<u32, String>) -> Self

Set the id2label mapping for classification models

pub fn with_num_labels(self, num_labels: u32) -> Self

Set num_labels directly (alternative to with_id2label)

pub fn matches(&self, model_id: &str) -> bool

Check if this model matches the given ID (including aliases)

pub fn supports_endpoint(&self, endpoint: Endpoint) -> bool

Check if this model supports a given endpoint

pub fn name(&self) -> &str

Get the display name or fall back to ID

pub fn is_native(&self) -> bool

Check if this is a native/local model (no external provider)

pub fn has_external_provider(&self) -> bool

Check if this model uses an external provider

pub fn is_llm(&self) -> bool

Check if this is an LLM (supports chat)

pub fn is_embedding_model(&self) -> bool

Check if this is an embedding model

pub fn supports_vision(&self) -> bool

Check if this model supports vision/multimodal

pub fn supports_tools(&self) -> bool

Check if this model supports tools/function calling

pub fn supports_reasoning(&self) -> bool

Check if this model supports reasoning

pub fn is_classifier(&self) -> bool

Check if this is a classification model

pub fn get_label(&self, class_idx: u32) -> String

Get label for a class index, with fallback to generic label (LABEL_N)

Trait Implementations

impl Clone for ModelCard

fn clone(&self) -> ModelCard

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ModelCard

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

Formats the value using the given formatter.

impl Default for ModelCard

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for ModelCard

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for ModelCard

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

Formats the value using the given formatter.

impl Serialize for ModelCard

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

where __S: Serializer,

Serialize this value into the given Serde serializer.