litellm-rs 0.4.16

A high-performance AI Gateway written in Rust, providing OpenAI-compatible APIs with intelligent routing, load balancing, and enterprise features
Documentation
//! Helper functions for embeddings
//!
//! Provides convenient functions for common embedding operations.

/// Calculate cosine similarity between two embedding vectors
///
/// # Arguments
/// * `a` - First embedding vector
/// * `b` - Second embedding vector
///
/// # Returns
/// Cosine similarity value between -1.0 and 1.0
/// Returns 0.0 if either vector has zero magnitude
///
/// # Example
/// ```rust
/// use litellm_rs::core::embedding::cosine_similarity;
///
/// let a = vec![1.0, 0.0, 0.0];
/// let b = vec![0.0, 1.0, 0.0];
/// let similarity = cosine_similarity(&a, &b);
/// assert!((similarity - 0.0).abs() < 1e-6); // Orthogonal vectors
/// ```
pub fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 {
    if a.len() != b.len() {
        return 0.0;
    }

    let dot_product: f32 = a.iter().zip(b.iter()).map(|(x, y)| x * y).sum();
    let magnitude_a: f32 = a.iter().map(|x| x * x).sum::<f32>().sqrt();
    let magnitude_b: f32 = b.iter().map(|x| x * x).sum::<f32>().sqrt();

    if magnitude_a == 0.0 || magnitude_b == 0.0 {
        return 0.0;
    }

    dot_product / (magnitude_a * magnitude_b)
}

/// Calculate Euclidean distance between two embedding vectors
///
/// # Arguments
/// * `a` - First embedding vector
/// * `b` - Second embedding vector
///
/// # Returns
/// Euclidean distance (L2 norm of the difference)
/// Returns f32::INFINITY if vectors have different lengths
///
/// # Example
/// ```rust
/// use litellm_rs::core::embedding::euclidean_distance;
///
/// let a = vec![0.0, 0.0];
/// let b = vec![3.0, 4.0];
/// let distance = euclidean_distance(&a, &b);
/// assert!((distance - 5.0).abs() < 1e-6);
/// ```
pub fn euclidean_distance(a: &[f32], b: &[f32]) -> f32 {
    if a.len() != b.len() {
        return f32::INFINITY;
    }

    a.iter()
        .zip(b.iter())
        .map(|(x, y)| (x - y).powi(2))
        .sum::<f32>()
        .sqrt()
}

/// Calculate dot product between two embedding vectors
///
/// # Arguments
/// * `a` - First embedding vector
/// * `b` - Second embedding vector
///
/// # Returns
/// Dot product value
/// Returns 0.0 if vectors have different lengths
pub fn dot_product(a: &[f32], b: &[f32]) -> f32 {
    if a.len() != b.len() {
        return 0.0;
    }

    a.iter().zip(b.iter()).map(|(x, y)| x * y).sum()
}

/// Normalize an embedding vector to unit length
///
/// # Arguments
/// * `v` - Embedding vector to normalize
///
/// # Returns
/// Normalized vector with magnitude 1.0
/// Returns zero vector if input has zero magnitude
pub fn normalize(v: &[f32]) -> Vec<f32> {
    let magnitude: f32 = v.iter().map(|x| x * x).sum::<f32>().sqrt();

    if magnitude == 0.0 {
        return v.to_vec();
    }

    v.iter().map(|x| x / magnitude).collect()
}

#[cfg(test)]
mod tests {
    use super::*;

    // ==================== Cosine Similarity Tests ====================

    #[test]
    fn test_cosine_similarity_identical() {
        let a = vec![1.0, 2.0, 3.0];
        let b = vec![1.0, 2.0, 3.0];
        let sim = cosine_similarity(&a, &b);
        assert!((sim - 1.0).abs() < 1e-6);
    }

    #[test]
    fn test_cosine_similarity_orthogonal() {
        let a = vec![1.0, 0.0, 0.0];
        let b = vec![0.0, 1.0, 0.0];
        let sim = cosine_similarity(&a, &b);
        assert!((sim - 0.0).abs() < 1e-6);
    }

    #[test]
    fn test_cosine_similarity_opposite() {
        let a = vec![1.0, 0.0];
        let b = vec![-1.0, 0.0];
        let sim = cosine_similarity(&a, &b);
        assert!((sim - (-1.0)).abs() < 1e-6);
    }

    #[test]
    fn test_cosine_similarity_different_lengths() {
        let a = vec![1.0, 2.0, 3.0];
        let b = vec![1.0, 2.0];
        let sim = cosine_similarity(&a, &b);
        assert_eq!(sim, 0.0);
    }

    #[test]
    fn test_cosine_similarity_zero_vector() {
        let a = vec![1.0, 2.0, 3.0];
        let b = vec![0.0, 0.0, 0.0];
        let sim = cosine_similarity(&a, &b);
        assert_eq!(sim, 0.0);
    }

    #[test]
    fn test_cosine_similarity_normalized() {
        let a = normalize(&[1.0, 1.0]);
        let b = normalize(&[1.0, 1.0]);
        let sim = cosine_similarity(&a, &b);
        assert!((sim - 1.0).abs() < 1e-6);
    }

    // ==================== Euclidean Distance Tests ====================

    #[test]
    fn test_euclidean_distance_identical() {
        let a = vec![1.0, 2.0, 3.0];
        let b = vec![1.0, 2.0, 3.0];
        let dist = euclidean_distance(&a, &b);
        assert!((dist - 0.0).abs() < 1e-6);
    }

    #[test]
    fn test_euclidean_distance_3_4_5() {
        let a = vec![0.0, 0.0];
        let b = vec![3.0, 4.0];
        let dist = euclidean_distance(&a, &b);
        assert!((dist - 5.0).abs() < 1e-6);
    }

    #[test]
    fn test_euclidean_distance_different_lengths() {
        let a = vec![1.0, 2.0, 3.0];
        let b = vec![1.0, 2.0];
        let dist = euclidean_distance(&a, &b);
        assert!(dist.is_infinite());
    }

    #[test]
    fn test_euclidean_distance_unit() {
        let a = vec![0.0];
        let b = vec![1.0];
        let dist = euclidean_distance(&a, &b);
        assert!((dist - 1.0).abs() < 1e-6);
    }

    // ==================== Dot Product Tests ====================

    #[test]
    fn test_dot_product_basic() {
        let a = vec![1.0, 2.0, 3.0];
        let b = vec![4.0, 5.0, 6.0];
        let result = dot_product(&a, &b);
        assert!((result - 32.0).abs() < 1e-6); // 1*4 + 2*5 + 3*6 = 32
    }

    #[test]
    fn test_dot_product_orthogonal() {
        let a = vec![1.0, 0.0];
        let b = vec![0.0, 1.0];
        let result = dot_product(&a, &b);
        assert!((result - 0.0).abs() < 1e-6);
    }

    #[test]
    fn test_dot_product_different_lengths() {
        let a = vec![1.0, 2.0, 3.0];
        let b = vec![1.0, 2.0];
        let result = dot_product(&a, &b);
        assert_eq!(result, 0.0);
    }

    // ==================== Normalize Tests ====================

    #[test]
    fn test_normalize_unit() {
        let v = vec![3.0, 4.0];
        let normalized = normalize(&v);
        assert!((normalized[0] - 0.6).abs() < 1e-6);
        assert!((normalized[1] - 0.8).abs() < 1e-6);

        // Verify magnitude is 1
        let mag: f32 = normalized.iter().map(|x| x * x).sum::<f32>().sqrt();
        assert!((mag - 1.0).abs() < 1e-6);
    }

    #[test]
    fn test_normalize_already_unit() {
        let v = vec![1.0, 0.0, 0.0];
        let normalized = normalize(&v);
        assert!((normalized[0] - 1.0).abs() < 1e-6);
        assert!((normalized[1] - 0.0).abs() < 1e-6);
    }

    #[test]
    fn test_normalize_zero_vector() {
        let v = vec![0.0, 0.0, 0.0];
        let normalized = normalize(&v);
        assert_eq!(normalized, vec![0.0, 0.0, 0.0]);
    }

    #[test]
    fn test_normalize_preserves_direction() {
        let v = vec![2.0, 2.0];
        let normalized = normalize(&v);
        let ratio = normalized[0] / normalized[1];
        assert!((ratio - 1.0).abs() < 1e-6);
    }
}