add ffmpeg feature

Cargo.toml

@@ -14,7 +14,7 @@ candle-flash-attn = { git = "https://github.com/huggingface/candle.git", version
 serde = "1.0.226"
 serde_json = "1.0.145"
 anyhow = "1.0.100"
-ffmpeg-next = "8.0.0"
+ffmpeg-next = { version = "8.0.0", optional = true }
 image = "0.25.8"
 reqwest = { version = "0.12.23", features = ["blocking"] }
 base64 = "0.22.1"
@@ -34,6 +34,7 @@ dirs = "6.0.0"
 [features]
 flash-attn=["candle-flash-attn"]
 cuda=["candle-nn/cuda", "candle-core/cuda", "candle-transformers/cuda"]
+ffmpeg=["ffmpeg-next"]
 
 [lints.clippy]
 needless_range_loop = "allow"

README.md

@@ -26,7 +26,7 @@
 ⭐ 如果这个项目对你有帮助，请给我们一个 Star！
 
 ## 环境依赖
-1. ffmpeg: 
+* 启用ffmpeg的feature时：
     * ubuntu/WSL
     ```bash
     sudo apt-get update
@@ -34,6 +34,32 @@ sudo apt-get install -y clang pkg-config ffmpeg libavutil-dev libavcodec-dev lib
     ```
     * windows参考： https://github.com/zmwangx/rust-ffmpeg/wiki/Notes-on-building
 
+## 功能特性
+项目提供了几个可选的功能特性，您可以根据需要启用它们：
+* flash-attn: 启用 Flash Attention 支持以提升模型推理性能：
+```bash
+cargo build --features flash-attn
+```
+
+* cuda: 为 candle 核心组件启用 CUDA 支持，实现 GPU 加速计算：
+```bash
+cargo build --features cuda
+```
+
+* ffmpeg: 启用 FFmpeg 支持，提供多媒体处理功能：
+```bash
+cargo build --features ffmpeg
+```
+* 组合使用功能特性
+
+```bash
+# 同时启用 CUDA 和 Flash Attention 以获得最佳性能
+cargo build --features "cuda,flash-attn"
+
+# 启用所有功能特性
+cargo build --features "cuda,flash-attn,ffmpeg"
+```
+
 ## 安装及使用
 
 ### 从源码构建部署

src/models/qwen2_5vl/processor.rs

@@ -5,6 +5,7 @@ use aha_openai_dive::v1::resources::chat::{
 };
 use anyhow::{Result, anyhow};
 use candle_core::{DType, Device, IndexOp, Shape, Tensor};
+#[cfg(feature = "ffmpeg")]
 use ffmpeg_next as ffmpeg;
 use image::DynamicImage;
 use num::integer::lcm;
@@ -33,6 +34,7 @@ pub struct GeneralInput {
     pub second_per_grid_ts: Option<Vec<f32>>,
 }
 
+#[allow(unused)]
 pub struct Qwen2_5VLProcessor {
     vision_setting: VisionSetting,
     device: Device,
@@ -213,6 +215,7 @@ impl Qwen2_5VLProcessor {
         })
     }
 
+    #[allow(unused_mut)]
     pub fn process_info(
         &self,
         messages: &ChatCompletionParameters,
@@ -221,7 +224,7 @@ impl Qwen2_5VLProcessor {
         let mut pixel_values = None;
         let mut image_grid_thw = None;
         let mut pixel_values_video = None;
-        let mut video_grid_thw = None;
+        let mut video_grid_thw: Option<Tensor> = None;
         let mut second_per_grid_ts = None;
         let vision_map = self.extract_vision_info(messages)?;
         let img_mean =
@@ -251,6 +254,7 @@ impl Qwen2_5VLProcessor {
                     };
                 }
             }
+            #[cfg(feature = "ffmpeg")]
             if key.eq("video") {
                 let mut file_vec = Vec::new();
                 for file in &vec {
@@ -294,6 +298,7 @@ impl Qwen2_5VLProcessor {
             }
             text = text.replace("<|placeholder|>", &self.image_token);
         }
+        #[cfg(feature = "ffmpeg")]
         if let Some(ref video_grid_thw) = video_grid_thw {
             let mut index = 0;
             while text.contains(&self.video_token) {
@@ -359,6 +364,7 @@ pub fn smart_resize(
     Ok((h_bar, w_bar))
 }
 
+#[cfg(feature = "ffmpeg")]
 pub fn get_video_data(
     file: &String,
     vision_setting: &VisionSetting,

src/models/qwen3vl/processor.rs

@@ -5,6 +5,7 @@ use aha_openai_dive::v1::resources::chat::{
 };
 use anyhow::{Result, anyhow};
 use candle_core::{DType, Device, IndexOp, Shape, Tensor};
+#[cfg(feature = "ffmpeg")]
 use ffmpeg_next as ffmpeg;
 use image::DynamicImage;
 use num::integer::lcm;
@@ -44,6 +45,7 @@ pub struct VideoMetadata {
     frame_indices: Vec<u32>,
 }
 
+#[allow(unused)]
 pub struct Qwen3VLProcessor {
     img_process_cfg: PreprocessorConfig,
     video_process_cfg: PreprocessorConfig,
@@ -256,6 +258,7 @@ impl Qwen3VLProcessor {
         })
     }
 
+    #[allow(unused)]
     fn calculate_timestamps(
         &self,
         frames_indices: Vec<u32>,
@@ -282,6 +285,7 @@ impl Qwen3VLProcessor {
         Ok(stamps)
     }
 
+    #[allow(unused)]
     pub fn process_info(
         &self,
         messages: &ChatCompletionParameters,
@@ -291,7 +295,7 @@ impl Qwen3VLProcessor {
         let mut image_grid_thw = None;
         let mut pixel_values_video = None;
         let mut video_grid_thw: Option<Tensor> = None;
-        let mut video_metadata = None;
+        let mut video_metadata: Option<Vec<VideoMetadata>> = None;
         let vision_map = self.extract_vision_info(messages)?;
         let img_mean =
             Tensor::from_slice(&self.img_process_cfg.image_mean, (3, 1, 1), &self.device)?
@@ -320,6 +324,7 @@ impl Qwen3VLProcessor {
                     };
                 }
             }
+            #[cfg(feature = "ffmpeg")]
             if key.eq("video") {
                 let mut file_vec = Vec::new();
                 let mut video_infos = Vec::new();
@@ -371,6 +376,7 @@ impl Qwen3VLProcessor {
             }
             text = text.replace("<|placeholder|>", &self.image_token);
         }
+        #[cfg(feature = "ffmpeg")]
         if let Some(ref video_grid_thw) = video_grid_thw {
             let mut index = 0;
             while text.contains(&self.video_token) {
@@ -471,6 +477,7 @@ pub fn video_smart_resize(
     Ok((h_bar, w_bar))
 }
 
+#[cfg(feature = "ffmpeg")]
 pub fn get_video_data(
     file: &String,
     patch_size: u32,

src/utils/video_utils.rs

@@ -1,14 +1,14 @@
-use std::{fs::File, io::Write};
+// use std::{fs::File, io::Write};
 
-use ffmpeg_next as ffmpeg;
+// use ffmpeg_next as ffmpeg;
 
-#[allow(unused)]
+// #[allow(unused)]
-fn save_file(
+// fn save_file(
-    frame: &ffmpeg::frame::Video,
+//     frame: &ffmpeg::frame::Video,
-    index: usize,
+//     index: usize,
-) -> std::result::Result<(), std::io::Error> {
+// ) -> std::result::Result<(), std::io::Error> {
-    let mut file = File::create(format!("frame{}.ppm", index))?;
+//     let mut file = File::create(format!("frame{}.ppm", index))?;
-    file.write_all(format!("P6\n{} {}\n255\n", frame.width(), frame.height()).as_bytes())?;
+//     file.write_all(format!("P6\n{} {}\n255\n", frame.width(), frame.height()).as_bytes())?;
-    file.write_all(frame.data(0))?;
+//     file.write_all(frame.data(0))?;
-    Ok(())
+//     Ok(())
-}
+// }

tests/test_gelab_zero.rs

@@ -0,0 +1,41 @@
+use std::time::Instant;
+
+use aha::models::{GenerateModel, qwen3vl::generate::Qwen3VLGenerateModel};
+use aha_openai_dive::v1::resources::chat::ChatCompletionParameters;
+use anyhow::Result;
+
+#[test]
+fn gelab_zero_generate() -> Result<()> {
+    // test with cuda: RUST_BACKTRACE=1 cargo test -F cuda gelab_zero_generate -r -- --nocapture
+
+    let model_path = "/home/jhq/huggingface_model/stepfun-ai/GELab-Zero-4B-preview";
+
+    let message = r#"
+    {
+        "model": "gelab-zero",
+        "messages": [
+            {
+                "role": "user",
+                "content": [    
+                    {
+                        "type": "text", 
+                        "text": "Hello, GELab-Zero!"
+                    }
+                ]
+            }
+        ]
+    }
+    "#;
+    let mes: ChatCompletionParameters = serde_json::from_str(message)?;
+    let i_start = Instant::now();
+    let mut qwen3vl = Qwen3VLGenerateModel::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 res = qwen3vl.generate(mes)?;
+    let i_duration = i_start.elapsed();
+    println!("generate: \n {:?}", res);
+    println!("Time elapsed in generate is: {:?}", i_duration);
+    Ok(())
+}

tests/test_qwen3vl.rs

@@ -19,23 +19,21 @@ fn qwen3vl_generate() -> Result<()> {
                 "role": "user",
                 "content": [
                     {
-                        "type": "image",
+                        "type": "video",
-                        "image_url": 
+                        "video_url": 
                         {
-                            "url": "file://./assets/img/ocr_test1.png"
+                            "url": "./assets/video/video_test.mp4"
                         }
                     },             
                     {
                         "type": "text", 
-                        "text": "请分析图片并提取所有可见文本内容，按从左到右、从上到下的布局，返回纯文本"
+                        "text": "视频里发生了什么"
                     }
                 ]
             }
         ]
     }
     "#;
-    // ./assets/video/video_test.mp4
-
     let mes: ChatCompletionParameters = serde_json::from_str(message)?;
     let i_start = Instant::now();
     let mut qwen3vl = Qwen3VLGenerateModel::init(model_path, None, None)?;