feat:解决了notebook启动uvicorn显示不正常的问题

Dockerfile

-FROM image.sourcefind.cn:5000/gpu/admin/base/jupyterlab-pytorch:2.2.0-py3.10-cuda12.1-ubuntu22.04-devel
+FROM image.sourcefind.cn:5000/gpu/admin/base/jupyterlab-pytorch:2.2.0-py3.10-cuda12.1-ubuntu22.04-devel as base
 ARG IMAGE=voicechat2
 ARG IMAGE_UPPER=voicechat2
 ARG BRANCH=gpu
 RUN cd /root && git clone -b $BRANCH http://developer.hpccube.com/codes/chenpangpang/$IMAGE.git
 WORKDIR /root/$IMAGE/$IMAGE_UPPER
-RUN apt-get update && apt-get install -y build-essential  byobu curl wget espeak-ng ffmpeg libopus0 libopus-dev
 RUN pip install -r requirements.txt
-RUN cd llama.cpp && make GGML_CUDA=1 -j
-COPY chenyh/$IMAGE/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf /root/$IMAGE/$IMAGE_UPPER/llama.cpp/
-COPY chenyh/$IMAGE/tts_models--en--vctk--vits /root/.local/share/tts/
-#COPY chenyh/$IMAGE/distil-whisper/large-v2 /root/$IMAGE/$IMAGE_UPPER/
+
+#########
+# Prod  #
+#########
+FROM image.sourcefind.cn:5000/gpu/admin/base/jupyterlab-pytorch:2.2.0-py3.10-cuda12.1-ubuntu22.04-devel
+COPY chenyh/$IMAGE/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf /root/$IMAGE/$IMAGE_UPPER/llama.cpp/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf
+COPY chenyh/$IMAGE/tts_models--en--vctk--vits /root/.local/share/tts/tts_models--en--vctk--vits
+COPY chenyh/$IMAGE/distil-whisper/large-v2 /root/$IMAGE/$IMAGE_UPPER/distil-whisper/large-v2
+RUN apt-get update && apt-get install -y build-essential  byobu curl wget espeak-ng ffmpeg libopus0 libopus-dev
+COPY --from=base /opt/conda/lib/python3.10/site-packages /opt/conda/lib/python3.10/site-packages
+COPY --from=base /root/$IMAGE/$IMAGE_UPPER /root/$IMAGE_UPPER
+COPY --from=base /root/$IMAGE/启动器.ipynb /root/$IMAGE/start.sh /root/
+# 需要在同种型号gpu上编译
+# RUN cd llama.cpp && make GGML_CUDA=1 -j

export-hf-model.py

+import os
+import shutil
+
+MODEL_NAME = "distil-whisper/large-v2"
+HF_CACHE_DIR = "/root/.cache/huggingface/hub/"
+hash_code = None
+# models--distil-whisper--large-v2/snapshots/66bb165856c86b9eae9dba7830c0cd7d859f4ef4/"
+for cache_model_name in os.listdir(HF_CACHE_DIR):
+    flag = False
+    for model_name_str_split in MODEL_NAME.split("/"):
+        if model_name_str_split in cache_model_name:
+            flag = True
+        else:
+            flag = False
+            break
+    if flag:
+        if hash_code is None:
+            full_path = os.path.join(HF_CACHE_DIR, cache_model_name, "snapshots",
+                                     os.listdir(os.path.join(HF_CACHE_DIR, cache_model_name, "snapshots"))[0])
+        else:
+            full_path = os.path.join(HF_CACHE_DIR, cache_model_name, "snapshots", hash_code)
+        os.makedirs(MODEL_NAME, exist_ok=True)
+        for filename in os.listdir(full_path):
+            shutil.copy(os.path.join(full_path, filename), os.path.join(MODEL_NAME, filename))
+            print("copy: ", os.path.join(full_path, filename), " to ", os.path.join(MODEL_NAME, filename))

start.sh

 #!/bin/bash
-export PATH=/opt/conda/lib/python3.10/site-packages/ninja/data/bin:$PATH
 cd /root/voicechat2
-python app.py
+python run.py
\ No newline at end of file

voicechat2/run.py

+import os
+from multiprocessing import Pool
+
+cmd_list = ["uvicorn voicechat2:app --host 0.0.0.0 --port 8000 --reload",
+            "uvicorn srt-server:app --host 0.0.0.0 --port 8001 --reload",
+            "llama.cpp/llama-server --host 127.0.0.1 --port 8002 -m llama.cpp/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf \
+            -ngl 99 -c 8192",
+            "uvicorn tts-server:app --host 0.0.0.0 --port 8003"]
+
+
+def run(cmd):
+    os.system(cmd)
+
+
+if __name__ == "__main__":
+    pool = Pool(4)  # 创建拥有3个进程数量的进程池
+    pool.map(run, cmd_list)
+    pool.close()  # 关闭进程池，不再接受新的进程
+    pool.join()  # 主进程阻塞等待子进程的退出

启动器.ipynb

@@ -8,17 +8,15 @@
    },
    "source": [
     "## 说明\n",
-    "- 启动需要加载模型，需要2分钟左右的时间\n",
-    "- 启动和重启 Notebook 点上方工具栏中的「重启并运行所有单元格」。出现如下内容就算成功了：\n",
-    "    - `Running on local URL:  http://0.0.0.0:7860`\n",
-    "    - `Running on public URL: https://xxxxxxxxxxxxxxx.gradio.live`\n",
+    "- 启动需要加载模型，需要1分钟左右的时间\n",
+    "- 启动和重启 Notebook 点上方工具栏中的「重启并运行所有单元格」\n",
     "- 通过以下方式开启页面：\n",
-    "    - 控制台打开「自定义服务」了，访问自定义服务端口号设置为7860\n",
-    "    - 直接打开显示的公开链接`public URL`\n",
+    "    - 控制台打开「自定义服务」了，访问自定义服务端口号设置为8000\n",
     "\n",
     "## 功能介绍\n",
     "- 原项目地址：https://github.com/lhl/voicechat2\n",
-    "- voicechat2：2D图片到3D模型转化工具，单张图片仅需10秒即可生成高质量3D模型"
+    "- voicechat2：一款可交互的AI语音聊天器\n",
+    "![demo](./assets/示例.png)"
    ]
   },
   {
@@ -26,8 +24,8 @@
    "execution_count": null,
    "id": "53a96614-e2d2-4710-a82b-0d5ca9cb9872",
    "metadata": {
-    "tags": [],
-    "is_executing": true
+    "is_executing": true,
+    "tags": []
    },
    "outputs": [],
    "source": [