simplify code

atoma-inference/src/model_thread.rs

@@ -108,7 +108,6 @@ where
     U: Response,
 {
     pub(crate) fn start<M, F>(
-        api: F,
         config: ModelConfig,
         public_key: PublicKey,
     ) -> Result<(Self, Vec<ModelThreadHandle<T, U>>), ModelThreadError>
@@ -119,6 +118,10 @@ where
             + 'static,
     {
         let model_ids = config.model_ids();
+        let api_key = config.api_key();
+        let storage_path = config.storage_path();
+        let api = F::create(api_key, storage_path)?;
+
         let mut handles = Vec::with_capacity(model_ids.len());
         let mut model_senders = HashMap::with_capacity(model_ids.len());
 

atoma-inference/src/models/config.rs

@@ -9,21 +9,21 @@ use crate::models::ModelId;
 pub struct ModelConfig {
     api_key: String,
     models: Vec<ModelId>,
-    storage_folder: PathBuf,
+    storage_path: PathBuf,
     tracing: bool,
 }
 
 impl ModelConfig {
     pub fn new(
         api_key: String,
         models: Vec<ModelId>,
-        storage_folder: PathBuf,
+        storage_path: PathBuf,
         tracing: bool,
     ) -> Self {
         Self {
             api_key,
             models,
-            storage_folder,
+            storage_path,
             tracing,
         }
     }
@@ -36,8 +36,8 @@ impl ModelConfig {
         self.models.clone()
     }
 
-    pub fn storage_folder(&self) -> PathBuf {
-        self.storage_folder.clone()
+    pub fn storage_path(&self) -> PathBuf {
+        self.storage_path.clone()
     }
 
     pub fn tracing(&self) -> bool {
@@ -66,12 +66,12 @@ pub mod tests {
         let config = ModelConfig::new(
             String::from("my_key"),
             vec!["Llama2_7b".to_string()],
-            "storage_folder".parse().unwrap(),
+            "storage_path".parse().unwrap(),
             true,
         );
 
         let toml_str = toml::to_string(&config).unwrap();
-        let should_be_toml_str = "api_key = \"my_key\"\nmodels = [\"Llama2_7b\"]\nstorage_folder = \"storage_folder\"\ntracing = true\n";
+        let should_be_toml_str = "api_key = \"my_key\"\nmodels = [\"Llama2_7b\"]\nstorage_path = \"storage_path\"\ntracing = true\n";
         assert_eq!(toml_str, should_be_toml_str);
     }
 }

atoma-inference/src/service.rs

@@ -49,13 +49,9 @@ where
         let private_key = PrivateKey::from(private_key_bytes);
         let public_key = private_key.verification_key();
         let model_config = ModelConfig::from_file_path(config_file_path);
-        let api_key = model_config.api_key();
-        let storage_folder = model_config.storage_folder();
-
-        let api = F::create(api_key, storage_folder)?;
 
         let (dispatcher, model_thread_handle) =
-            ModelThreadDispatcher::start::<M, F>(api, model_config, public_key)
+            ModelThreadDispatcher::start::<M, F>(model_config, public_key)
                 .map_err(ModelServiceError::ModelThreadError)?;
         let start_time = Instant::now();
 
@@ -236,7 +232,7 @@ mod tests {
         let config_data = Value::Table(toml! {
             api_key = "your_api_key"
             models = ["Mamba3b"]
-            storage_folder = "./storage_folder/"
+            storage_path = "./storage_path/"
             tokenizer_file_path = "./tokenizer_file_path/"
             tracing = true
         });