Struct DocumentIndex 

pub struct DocumentIndex {
    pub doc_id: String,
    pub term_frequencies: HashMap<String, f64>,
    pub doc_length: usize,
    pub embedding: Option<Vec<f64>>,
}

A document representation stored inside the ranker index.

Fields

doc_id: String

Unique document identifier.

term_frequencies: HashMap<String, f64>

Pre-computed term frequency map: term → raw count (normalised to f64).

doc_length: usize

Total number of tokens in the document.

embedding: Option<Vec<f64>>

Optional dense embedding used for semantic scoring.

Implementations

impl DocumentIndex

pub fn from_tokens( doc_id: impl Into<String>, tokens: &[&str], embedding: Option<Vec<f64>>, ) -> Self

Constructs a DocumentIndex from a plain token list.

Term frequencies are computed as raw counts; the caller may pass a pre-embedded vector if semantic ranking is desired.

Trait Implementations

impl Clone for DocumentIndex

fn clone(&self) -> DocumentIndex

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for DocumentIndex

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

Formats the value using the given formatter.