update server env

funasr/runtime/python/grpc/Readme.md

@@ -5,25 +5,25 @@ The audio data is in streaming, the asr inference process is in offline.
 
 ## Steps
 
-Step 1) Optional, prepare server environment (on server).  Install modelscope and funasr with pip or with cuda-docker image.
+Step 1) **Optional**, prepare server environment (on server).  Install modelscope and funasr with pip or with cuda-docker image.
 
-Option 1: Install modelscope and funasr with [pip](https://github.com/alibaba-damo-academy/FunASR#installation)
+         Option 1: Install modelscope and funasr with [pip](https://github.com/alibaba-damo-academy/FunASR#installation)
 
-Option 2: or install with cuda-docker image as: 
+         Option 2: or install with cuda-docker image as: 
 
 ```
 CID=`docker run --network host -d -it --gpus '"device=0"' registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.3.0-py37-torch1.11.0-tf1.15.5-1.2.0`
 echo $CID
 docker exec -it $CID /bin/bash
 ```
-Get funasr source code and get into grpc directory.
+         Get funasr source code and get into grpc directory.
 ```
 git clone https://github.com/alibaba-damo-academy/FunASR
 cd FunASR/funasr/runtime/python/grpc/
 ```
 
 
-Step 2) Optional, generate protobuf file (run on server, the two generated pb file are both used for server and client).
+Step 2) **Optional**, generate protobuf file (run on server, the two generated pb file are both used for server and client).
 ```
 # paraformer_pb2.py and paraformer_pb2_grpc.py are already generated.
 python -m grpc_tools.protoc  --proto_path=./proto -I ./proto    --python_out=. --grpc_python_out=./ ./proto/paraformer.proto
@@ -35,8 +35,9 @@ python grpc_main_server.py --port 10095
 ```
 
 Step 4) Start grpc client (on client with microphone).
+
+         **Optional**, Install dependency.
 ```
-# Optional, Install dependency.
 python -m pip install pyaudio webrtcvad
 ```
 ```