先跑 ASR

docker build -f packages/WhisperLive/docker/Dockerfile.gpu -t whisperlive-gpu .

docker run -it --gpus all -p 9090:9090 --name whisperlive --restart=always whisperlive-gpu

conda update --all -y conda create -n tcm-agent python=3.11 -y conda activate tcm-agent conda install -c conda-forge jupyter -y

pip install torch==2.1.0+cu121 -f https://download.pytorch.org/whl/cu121/torch_stable.html pip install torchaudio==2.1.0+cu121 -f https://download.pytorch.org/whl/cu121/torch_stable.html pip install torchvision==0.16.0+cu121 -f https://download.pytorch.org/whl/cu121/torch_stable.html

pip install --no-cache-dir --requirement=config/requirements.txt

C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\Common7\IDE\CommonExtensions\Microsoft\CMake\CMake\bin C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.36.32532\bin\Hostx64\x64

pip install pyopenjtalk -i https://pypi.tuna.tsinghua.edu.cn/simple --no-build-isolation

conda activate tcm-agent && python ./services/redis_service.py

conda activate tcm-agent && python ./services/asr_service.py

conda activate tcm-agent && python ./services/aikenshe_service.py

conda activate tcm-agent && python ./services/new_asr_service.py

https://github.com/ollama/ollama ollama serve ollama run llama3.1:8b

git clone https://github.com/infiniflow/ragflow.git cd ragflow/docker cd src\packages\ragflow\docker && docker-compose up -d

docker run -it --gpus all -p 9090:9090 ghcr.io/collabora/whisperlive-gpu:latest

docker run -d -p 51201:6379 --name 51201-redis -d --restart=always redis

端口占用列表 服务名称 端口 Redis 51201 AI Kan She 52045 ASR Client 9091 Whisper Live Server 9090 Ragflow Server 443, 80, 9380 Ragflow ES 1200 Ragflow Minio 9000, 9001 Ragflow Redis (未指定)