neomemx 0.1.2

A high-performance memory library for AI agents with semantic search
Documentation 
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//! HuggingFace Inference API embedder configuration

use serde::{Deserialize, Serialize};

/// Configuration for HuggingFace embeddings
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct HuggingFaceEmbedderConfig {
    /// Model to use for embeddings
    #[serde(default = "default_model")]
    pub model: String,

    /// HuggingFace API token
    pub api_key: Option<String>,

    /// Embedding dimensions (depends on model)
    #[serde(default = "default_embedding_dims")]
    pub embedding_dims: usize,

    /// HuggingFace Inference API base URL
    #[serde(default = "default_base_url")]
    pub base_url: String,
}

fn default_model() -> String {
    "BAAI/bge-small-en-v1.5".to_string()
}

fn default_embedding_dims() -> usize {
    384
}

fn default_base_url() -> String {
    "https://api-inference.huggingface.co/models".to_string()
}

impl Default for HuggingFaceEmbedderConfig {
    fn default() -> Self {
        Self {
            model: default_model(),
            api_key: None,
            embedding_dims: default_embedding_dims(),
            base_url: default_base_url(),
        }
    }
}

impl HuggingFaceEmbedderConfig {
    /// Get the API key from config or environment
    pub fn get_api_key(&self) -> Option<String> {
        self.api_key
            .clone()
            .or_else(|| std::env::var("HUGGINGFACE_API_KEY").ok())
    }
}