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95 lines
3.0 KiB
Markdown
95 lines
3.0 KiB
Markdown
# Service with grpc-python
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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.
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The audio data is in streaming, the asr inference process is in offline.
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## For the Server
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### Prepare server environment
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#### Backend is modelscope pipeline (default)
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Install the modelscope and funasr
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```shell
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pip install -U modelscope funasr
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# For the users in China, you could install with the command:
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# pip install -U modelscope funasr -i https://mirror.sjtu.edu.cn/pypi/web/simple
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git clone https://github.com/alibaba/FunASR.git && cd FunASR
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```
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Install the requirements
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```shell
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cd funasr/runtime/python/grpc
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pip install -r requirements_server.txt
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```
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#### Backend is funasr_onnx (optional)
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Install [`funasr_onnx`](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime).
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```
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pip install funasr_onnx -i https://pypi.Python.org/simple
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```
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Export the model, more details ref to [export docs](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/onnxruntime).
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```shell
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python -m funasr.export.export_model --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type onnx --quantize True
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```
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### Generate protobuf file
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Run on server, the two generated pb files are both used for server and client
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```shell
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# paraformer_pb2.py and paraformer_pb2_grpc.py are already generated,
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# regenerate it only when you make changes to ./proto/paraformer.proto file.
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python -m grpc_tools.protoc --proto_path=./proto -I ./proto --python_out=. --grpc_python_out=./ ./proto/paraformer.proto
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```
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### Start grpc server
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```
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# Start server.
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python grpc_main_server.py --port 10095 --backend pipeline
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```
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If you want run server with onnxruntime, please set `backend` and `onnx_dir`.
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```
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# Start server.
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python grpc_main_server.py --port 10095 --backend onnxruntime --onnx_dir /models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch
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```
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## For the client
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### Install the requirements
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```shell
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git clone https://github.com/alibaba/FunASR.git && cd FunASR
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cd funasr/runtime/python/grpc
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pip install -r requirements_client.txt
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```
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### Generate protobuf file
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Run on server, the two generated pb files are both used for server and client
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```shell
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# paraformer_pb2.py and paraformer_pb2_grpc.py are already generated,
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# regenerate it only when you make changes to ./proto/paraformer.proto file.
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python -m grpc_tools.protoc --proto_path=./proto -I ./proto --python_out=. --grpc_python_out=./ ./proto/paraformer.proto
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```
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### Start grpc client
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```
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# Start client.
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python grpc_main_client_mic.py --host 127.0.0.1 --port 10095
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```
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## Workflow in desgin
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<div align="left"><img src="proto/workflow.png" width="400"/>
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## Reference
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We borrow from or refer to some code as:
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1)https://github.com/wenet-e2e/wenet/tree/main/runtime/core/grpc
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2)https://github.com/Open-Speech-EkStep/inference_service/blob/main/realtime_inference_service.py |