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| | | ## Steps |
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| | | Step 1) Prepare server environment (on server). |
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| | | Step 1) Optional, prepare server environment (on server). Install modelscope and funasr with pip or with cuda-docker image. |
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| | | Option 1: Install modelscope and funasr with [pip](https://github.com/alibaba-damo-academy/FunASR#installation) |
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| | | Option 2: or install with cuda-docker image as: |
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| | | |
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| | | ``` |
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| | | # Optional, modelscope cuda docker is preferred. |
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| | | 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` |
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| | | echo $CID |
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| | | docker exec -it $CID /bin/bash |
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| | | cd /opt/conda/lib/python3.7/site-packages/funasr/runtime/python/grpc |
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| | | ``` |
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| | | Get funasr source code and get into grpc directory. |
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| | | ``` |
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| | | git clone https://github.com/alibaba-damo-academy/FunASR |
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| | | cd FunASR/funasr/runtime/python/grpc/ |
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| | | ``` |
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| | | Step 2) Generate protobuf file (for server and client). |
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| | | |
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| | | Step 2) Optional, generate protobuf file (run on server, the two generated pb file are both used for server and client). |
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| | | ``` |
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| | | # Optional, paraformer_pb2.py and paraformer_pb2_grpc.py are already generated. |
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| | | # paraformer_pb2.py and paraformer_pb2_grpc.py are already generated. |
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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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| | | ``` |
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| | | Step 4) Start grpc client (on client with microphone). |
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| | | |
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| | | ``` |
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| | | # Install dependency. Optional. |
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| | | # Optional, Install dependency. |
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| | | python -m pip install pyaudio webrtcvad |
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| | | ``` |
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| | | ``` |
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| | | ## Reference |
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| | | We borrow or refer to some code from: |
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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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