fix: ModelConfig import error for aarch64 Linux builds (#2536)

Author: kensave

crates/semantic-search-client/src/client/hosted_model_client.rs

@@ -329,6 +329,7 @@ mod tests {
             repo_path: "test/repo".to_string(),
             model_file: "model.safetensors".to_string(),
             tokenizer_file: "tokenizer.json".to_string(),
+            #[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
             config: Default::default(),
             normalize_embeddings: true,
             batch_size: 32,
@@ -359,6 +360,7 @@ mod tests {
             repo_path: "test/repo".to_string(),
             model_file: "model.safetensors".to_string(),
             tokenizer_file: "tokenizer.json".to_string(),
+            #[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
             config: Default::default(),
             normalize_embeddings: true,
             batch_size: 32,

crates/semantic-search-client/src/embedding/candle_models.rs

@@ -1,5 +1,6 @@
 use std::path::PathBuf;
 
+#[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
 use candle_transformers::models::bert::Config as BertConfig;
 
 /// Type of model to use for text embedding
@@ -29,6 +30,7 @@ pub struct ModelConfig {
     /// Name of the tokenizer file
     pub tokenizer_file: String,
     /// BERT configuration
+    #[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
     pub config: BertConfig,
     /// Whether to normalize embeddings
     pub normalize_embeddings: bool,
@@ -45,6 +47,7 @@ impl ModelType {
                 repo_path: "sentence-transformers/all-MiniLM-L6-v2".to_string(),
                 model_file: "model.safetensors".to_string(),
                 tokenizer_file: "tokenizer.json".to_string(),
+                #[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
                 config: BertConfig {
                     vocab_size: 30522,
                     hidden_size: 384,
@@ -71,6 +74,7 @@ impl ModelType {
                 repo_path: "sentence-transformers/all-MiniLM-L12-v2".to_string(),
                 model_file: "model.safetensors".to_string(),
                 tokenizer_file: "tokenizer.json".to_string(),
+                #[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
                 config: BertConfig {
                     vocab_size: 30522,
                     hidden_size: 384,

crates/semantic-search-client/src/embedding/mod.rs

@@ -4,7 +4,6 @@ mod benchmark_utils;
 mod bm25;
 #[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
 mod candle;
-#[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
 mod candle_models;
 /// Mock embedder for testing
 #[cfg(test)]
@@ -20,7 +19,6 @@ pub use benchmark_utils::{
 pub use bm25::BM25TextEmbedder;
 #[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
 pub use candle::CandleTextEmbedder;
-#[cfg(not(all(target_os = "linux", target_arch = "aarch64")))]
 pub use candle_models::{
     ModelConfig,
     ModelType,