# Service with grpc-python We can send streaming audio data to server in real-time with grpc client every 10 ms e.g., and get transcribed text when stop speaking. The audio data is in streaming, the asr inference process is in offline. ## For the Server ### Prepare server environment Install the modelscope and funasr ```shell pip install -U modelscope funasr # For the users in China, you could install with the command: # pip install -U modelscope funasr -i https://mirror.sjtu.edu.cn/pypi/web/simple git clone https://github.com/alibaba/FunASR.git && cd FunASR ``` Install the requirements ```shell cd funasr/runtime/python/grpc pip install -r requirements_server.txt ``` ### Generate protobuf file Run on server, the two generated pb files are both used for server and client ```shell # paraformer_pb2.py and paraformer_pb2_grpc.py are already generated, # regenerate it only when you make changes to ./proto/paraformer.proto file. python -m grpc_tools.protoc --proto_path=./proto -I ./proto --python_out=. --grpc_python_out=./ ./proto/paraformer.proto ``` ### Start grpc server ``` # Start server. python grpc_main_server.py --port 10095 --backend pipeline ``` ## For the client ### Install the requirements ```shell git clone https://github.com/alibaba/FunASR.git && cd FunASR cd funasr/runtime/python/grpc pip install -r requirements_client.txt ``` ### Generate protobuf file Run on server, the two generated pb files are both used for server and client ```shell # paraformer_pb2.py and paraformer_pb2_grpc.py are already generated, # regenerate it only when you make changes to ./proto/paraformer.proto file. python -m grpc_tools.protoc --proto_path=./proto -I ./proto --python_out=. --grpc_python_out=./ ./proto/paraformer.proto ``` ### Start grpc client ``` # Start client. python grpc_main_client_mic.py --host 127.0.0.1 --port 10095 ``` ## Workflow in desgin
## Acknowledge
1. This project is maintained by [FunASR community](https://github.com/alibaba-damo-academy/FunASR).