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app.py

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+import subprocess
+import sys
+
+subprocess.check_call([sys.executable, "-m", "pip", "install", "pip==24.0"])
+subprocess.check_call([sys.executable, "-m", "pip", "install", "omegaconf==2.0.6"])
+subprocess.check_call([sys.executable, "-m", "pip", "install", "git+https://github.com/facebookresearch/[email protected]"])
+import gradio as gr
+import os
+import torch
+import librosa
+import soundfile as sf
+import tempfile
+import spaces  # ZeroGPU requirement
+
+# 导入你的模块
+import Echox_copy_stream as Echox
+
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+# 全局变量
+_MODEL_ON_CUDA = False
+inference_model = None
+
+def init_model():
+    """在CPU上初始化模型"""
+    global inference_model
+    if inference_model is None:
+        inference_model = Echox.EchoxAssistant()
+    return inference_model
+
+def process_audio_input(audio):
+    """处理音频输入"""
+    if audio is None:
+        return None
+    
+    try:
+        # 如果是文件路径，直接返回
+        if isinstance(audio, str):
+            return audio
+        
+        # 如果是numpy数组格式 (sr, data)
+        if isinstance(audio, tuple):
+            sr, y = audio
+            if y.ndim > 1:
+                y = y[:, 0]  # 只保留第一个声道
+        else:
+            # 如果直接是数组
+            y = audio
+            sr = 16000  # 默认采样率
+        
+        # 保存为临时文件
+        with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as tmp_file:
+            sf.write(tmp_file.name, y, sr)
+            return tmp_file.name
+            
+    except Exception as e:
+        print(f"Error processing audio: {e}")
+        return None
+
+@spaces.GPU(duration=180)  # 使用ZeroGPU，3分钟超时
+def process_audio_text(text, audio):
+    """主要处理函数"""
+    global _MODEL_ON_CUDA, inference_model
+    
+    # 初始化模型（如果还没初始化）
+    if inference_model is None:
+        init_model()
+    
+    # 首次使用GPU时移动模型
+    if not _MODEL_ON_CUDA:
+        try:
+            # 将模型移动到GPU
+            if hasattr(inference_model, 'model'):
+                inference_model.model = inference_model.model.to("cuda")
+            if hasattr(inference_model, 'unit_translator'):
+                inference_model.unit_translator = inference_model.unit_translator.to("cuda")
+            
+            inference_model.device = "cuda"
+            _MODEL_ON_CUDA = True
+            print("Model moved to GPU")
+        except Exception as e:
+            print(f"Error moving model to GPU: {e}")
+    
+    # 处理音频输入
+    audio_path = process_audio_input(audio)
+    
+    text = ""
+    
+    tmp = [{
+        "conversations": [
+            {
+                "from": "user",
+                "value": text,
+                "audio": audio_path
+            }
+        ]
+    }]
+    
+    accumulated_text = ""
+    
+    try:
+        for text_response, audio_data in inference_model._inference(tmp):
+            if text_response:
+                accumulated_text = text_response
+            
+            if audio_data is not None:
+                sr, audio_array = audio_data
+                yield accumulated_text, (sr, audio_array)
+            else:
+                yield accumulated_text, None
+    except Exception as e:
+        yield f"Error: {str(e)}", None
+    finally:
+        # 清理临时文件
+        if audio_path and audio_path != audio and os.path.exists(audio_path):
+            try:
+                os.unlink(audio_path)
+            except:
+                pass
+
+# 初始化模型（在CPU上）
+init_model()
+
+if __name__ == "__main__":
+    examples = [
+        ["", "./show_case/1.wav"],
+        ["", "./show_case/2.wav"],
+    ]  
+
+    iface = gr.Interface(
+        fn=process_audio_text,
+        inputs=[
+            gr.Textbox(label="Enter text instruction", value=""),
+            gr.Audio(type="filepath", label="Upload Audio")
+        ],
+        outputs=[
+            gr.Textbox(label="Model output"),
+            gr.Audio(label="Streamed Audio", streaming=True, autoplay=True)
+        ],
+        examples=examples,
+        title="🔊 EchoX Assistant",
+        description="A multimodal AI assistant that understands speech and responds with both text and audio",
+        live=False,
+        allow_flagging="never"
+    )
+
+    iface.launch(server_name="0.0.0.0", server_port=7860, share=True)

requirements.txt

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+gradio==5.44.1
+librosa==0.10.2.post1
+numpy==1.24.4
+peft==0.5.0
+sentencepiece==0.2.0
+soundfile==0.12.1
+torch==2.3.0
+tqdm==4.66.5
+transformers==4.49.0