update fmt

tests/messy_test.rs

@@ -1,17 +1,17 @@
 // use std::io::Cursor;
 
-use std::fs::File;
+// use std::fs::File;
 // use symphonia::core::io::MediaSourceStream;
-use std::io::{Read, Seek};
-use std::{io::Cursor, time::Instant};
+// use std::io::{Read, Seek};
+// use std::{io::Cursor, time::Instant};
 
-use aha::utils::{load_tensor_from_pt, tensor_utils::interpolate_nearest_1d};
-use aha_openai_dive::v1::resources::chat::ChatCompletionParameters;
-use anyhow::{Result, anyhow};
-use byteorder::{LittleEndian, ReadBytesExt};
-use candle_core::{Shape, Tensor};
-use sentencepiece::SentencePieceProcessor;
-use zip::ZipArchive;
+use aha::utils::load_tensor_from_pt;
+// use aha_openai_dive::v1::resources::chat::ChatCompletionParameters;
+use anyhow::Result;
+// use byteorder::{LittleEndian, ReadBytesExt};
+use candle_core::Shape;
+// use sentencepiece::SentencePieceProcessor;
+// use zip::ZipArchive;
 
 #[test]
 fn messy_test() -> Result<()> {

tests/test_health_models.rs

@@ -0,0 +1,76 @@
+use aha::models::WhichModel;
+
+// Import helper functions from api module - these will need to be made public
+// or tested through integration testing
+
+#[test]
+fn test_model_type_classification() {
+    // Since get_model_type and get_model_id are private to api.rs,
+    // we document the expected behavior here for reference:
+    //
+    // LLM models: MiniCPM4_0_5B, Qwen2_5vl3B, Qwen2_5vl7B, Qwen3_0_6B,
+    //             Qwen3vl2B, Qwen3vl4B, Qwen3vl8B, Qwen3vl32B
+    // OCR models: DeepSeekOCR, HunyuanOCR, PaddleOCRVL
+    // ASR models: Qwen3ASR0_6B, Qwen3ASR1_7B, GlmASRNano2512, FunASRNano2512
+    // Image models: RMBG2_0, VoxCPM, VoxCPM1_5
+
+    // This test documents the expected model type classification
+    let llm_models = vec![
+        WhichModel::MiniCPM4_0_5B,
+        WhichModel::Qwen2_5vl3B,
+        WhichModel::Qwen2_5vl7B,
+        WhichModel::Qwen3_0_6B,
+        WhichModel::Qwen3vl2B,
+        WhichModel::Qwen3vl4B,
+        WhichModel::Qwen3vl8B,
+        WhichModel::Qwen3vl32B,
+    ];
+
+    let ocr_models = vec![
+        WhichModel::DeepSeekOCR,
+        WhichModel::HunyuanOCR,
+        WhichModel::PaddleOCRVL,
+    ];
+
+    let asr_models = vec![
+        WhichModel::Qwen3ASR0_6B,
+        WhichModel::Qwen3ASR1_7B,
+        WhichModel::GlmASRNano2512,
+        WhichModel::FunASRNano2512,
+    ];
+
+    let image_models = vec![
+        WhichModel::RMBG2_0,
+        WhichModel::VoxCPM,
+        WhichModel::VoxCPM1_5,
+    ];
+
+    // Verify counts
+    assert_eq!(llm_models.len(), 8);
+    assert_eq!(ocr_models.len(), 3);
+    assert_eq!(asr_models.len(), 4);
+    assert_eq!(image_models.len(), 3);
+
+    // Total models
+    assert_eq!(
+        llm_models.len() + ocr_models.len() + asr_models.len() + image_models.len(),
+        18
+    );
+}
+
+// Note: Integration tests for the /health and /models endpoints
+// should be done with a running server. These would typically:
+//
+// 1. Start the server with a test model
+// 2. Make HTTP requests to /health and /models
+// 3. Verify the response format and status codes
+//
+// Example (pseudo-code):
+//
+// #[tokio::test]
+// async fn test_health_endpoint() {
+//     let resp = reqwest::get("http://localhost:10100/health").await.unwrap();
+//     assert_eq!(resp.status(), 200);
+//     let json: serde_json::Value = resp.json().await.unwrap();
+//     assert_eq!(json["status"], "ok");
+// }

tests/weight_test.rs

@@ -1,12 +1,8 @@
 use std::collections::HashMap;
 
-use aha::utils::{find_type_files, get_device, read_pth_tensor_info_cycle};
+use aha::utils::{find_type_files, get_device};
 use anyhow::Result;
-use candle_core::{
-    Device,
-    pickle::{read_all_with_key, read_pth_tensor_info},
-    safetensors,
-};
+use candle_core::{Device, pickle::read_all_with_key, safetensors};
 use candle_nn::VarBuilder;
 
 #[test]
@@ -207,7 +203,7 @@ fn index_tts2_weight() -> Result<()> {
     // RUST_BACKTRACE=1 cargo test -F cuda index_tts2_weight -r -- --nocapture
     let save_dir: String =
         aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
-    let model_path = format!("{}/IndexTeam/IndexTTS-2/", save_dir);
+    // let model_path = format!("{}/IndexTeam/IndexTTS-2/", save_dir);
     let bigvgan_path = format!(
         "{}/nv-community/bigvgan_v2_22khz_80band_256x/bigvgan_generator.pt",
         save_dir