Struct Embedding 

pub struct Embedding {
    pub document: String,
    pub vec: Vec<f64>,
}

A single document and its vector representation.

The document field preserves the original text so embeddings can be matched back to their source after batching or storage.

Fields

document: String

The text that was embedded.

vec: Vec<f64>

The embedding vector returned by the model.

Trait Implementations

impl Clone for Embedding

fn clone(&self) -> Embedding

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Embedding

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

Formats the value using the given formatter.

impl Default for Embedding

fn default() -> Embedding

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Embedding

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Eq for Embedding

impl PartialEq for Embedding

fn eq(&self, other: &Self) -> bool

Equality operator ==.

fn ne(&self, other: &Rhs) -> bool

Inequality operator !=.

impl Serialize for Embedding

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl VectorDistance for Embedding

fn dot_product(&self, other: &Self) -> f64

Dot product of two vectors.

fn cosine_similarity(&self, other: &Self, normalized: bool) -> f64

Cosine similarity in [-1, 1].

fn angular_distance(&self, other: &Self, normalized: bool) -> f64

Angular distance in [0, 1] (0 = identical direction).

fn euclidean_distance(&self, other: &Self) -> f64

Euclidean (L2) distance.

fn manhattan_distance(&self, other: &Self) -> f64

Manhattan (L1) distance.

fn chebyshev_distance(&self, other: &Self) -> f64

Chebyshev (L∞) distance — maximum absolute difference across dimensions.