update doc

tests/test_voxcpm2.rs

@@ -1,9 +1,12 @@
 use std::time::Instant;
 
 use aha::{
-    models::{GenerateModel, voxcpm::generate::VoxCPMGenerate},
+    models::{
+        GenerateModel, voxcpm::generate::VoxCPMGenerate,
+        voxcpm_refact::generate::VoxCPMGenerateRefact,
+    },
     params::chat::ChatCompletionParameters,
-    utils::audio_utils::extract_and_save_audio_from_response,
+    utils::audio_utils::{extract_and_save_audio_from_response, save_wav_mono},
 };
 use anyhow::Result;
 
@@ -30,26 +33,74 @@ fn voxcpm2_use_message_generate() -> Result<()> {
                     },  
                     {
                         "type": "text", 
-                        "text": "你好，这是aha在说话"
+                        "text": "aha是一个基于Rust和Candle框架的本地AI推理引擎，支持多模态模型（文本、视觉、语音、OCR）。"
                     }
                 ]
             }
-        ]
+        ],
+        "metadata": {"prompt_text": "天雷滚滚我好怕怕，劈得我浑身掉渣渣。突破天劫我笑哈哈，逆天改命我吹喇叭，滴答滴答滴滴答"}
     }
     "#;
     let mes: ChatCompletionParameters = serde_json::from_str(message)?;
+    let i_start = Instant::now();
+    let mut voxcpm_generate = VoxCPMGenerateRefact::init(&model_path, None, None)?;
+    let i_duration = i_start.elapsed();
+    println!("Time elapsed in load model is: {:?}", i_duration);
+    // for _ in 0..10 {
+    //     let _ = voxcpm_generate.generate(mes.clone())?;
+    // }
+    // let mut times = vec![];
+    // for _ in 0..100 {
+    //     let start = Instant::now();
+    //     let _ = voxcpm_generate.generate(mes.clone())?;
+    //     times.push(start.elapsed());
+    // }
+    // let mean = times.iter().sum::<Duration>() / 100;
+    // println!("mean: {:?}", mean);
+    // times.sort();
+    // println!("p99: {:?}", times[99]);
+    let i_start = Instant::now();
+    let generate = voxcpm_generate.generate(mes)?;
+    let i_duration = i_start.elapsed();
+    println!("Time elapsed in generate is: {:?}", i_duration);
+    let save_path = extract_and_save_audio_from_response(&generate, "./")?;
+    for path in save_path {
+        println!("save audio: {}", path);
+    }
+    Ok(())
+}
+
+#[test]
+fn voxcpm2_generate() -> Result<()> {
+    // RUST_BACKTRACE=1 cargo test -F cuda --test test_voxcpm2 voxcpm2_generate -r -- --nocapture
+    let save_dir =
+        aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
+    let model_path = format!("{}/OpenBMB/VoxCPM2/", save_dir);
+
     let i_start = Instant::now();
     let mut voxcpm_generate = VoxCPMGenerate::init(&model_path, None, None)?;
     let i_duration = i_start.elapsed();
     println!("Time elapsed in load model is: {:?}", i_duration);
 
     let i_start = Instant::now();
-    let generate = voxcpm_generate.generate(mes)?;
-    let save_path = extract_and_save_audio_from_response(&generate, "./")?;
-    for path in save_path {
-        println!("save audio: {}", path);
-    }
+    let generate = voxcpm_generate.inference(
+        "aha是一个基于Rust和Candle框架的本地AI推理引擎，支持多模态模型（文本、视觉、语音、OCR）。"
+            .to_string(),
+        None,
+        None,
+        2,
+        1000,
+        10,
+        2.0,
+        6.0,
+    )?;
     let i_duration = i_start.elapsed();
     println!("Time elapsed in generate is: {:?}", i_duration);
+
+    save_wav_mono(
+        &generate,
+        "voxcpm2.wav",
+        voxcpm_generate.sample_rate() as u32,
+    )?;
     Ok(())
 }