550 lines
12 KiB
Markdown
550 lines
12 KiB
Markdown
# 在GPU上跑的服务
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## clip.service
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多媒体embedding服务，提供文本，图像，视频和音频的embedding服务
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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WorkingDirectory=/share/run/clip
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ExecStart=/share/run/clip/start.sh
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ExecStop=/share/run/clip/stop.sh
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StandardOutput=append:/var/log/clip/clip.log
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StandardError=append:/var/log/clip/clip.log
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SyslogIdentifier=clip
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[Install]
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WantedBy=multi-user.target
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```
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## http服务
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https://embedding.opencomputing.net:1044/mme
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### 模型
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* 使用的模型名：laion/CLIP-ViT-B-32-laion2B-s34B-b79K
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* 模型路径
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### 运行脚本
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```
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#!/bin/bash
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CUDA_VISIBLE_DEVICES=4 /share/vllm-0.8.5/bin/python -m llmengine
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.mm_embedding -p 8882
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```
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## entities.service
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实体抽取服务
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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WorkingDirectory=/share/run/entities
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ExecStart=/share/run/entities/start.sh
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ExecStop=/share/run/entities/stop.sh
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StandardOutput=append:/var/log/entities/entities.log
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StandardError=append:/var/log/entities/entities.log
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SyslogIdentifier=entities
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://entities.opencomputing.net:10443
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### 模型
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路径：/share/models/LTP/small
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### 运行脚本
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```
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#!/bin/bash
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CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.entity -p 9990 /share/models/LTP/small
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```
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## f5tts.service
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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User=ymq
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Group=ymq
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WorkingDirectory=/share/ymq/run/f5tts
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Type=forking
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ExecStart=/share/ymq/run/f5tts/start.sh
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ExecStop=/share/ymq/run/f5tts/stop.sh
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StandardOutput=append:/var/log/f5tts/f5tts.log
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StandardError=append:/var/log/f5tts/f5tts.log
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SyslogIdentifier=f5tts
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://tts.opencomputing.net:10443
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### 模型
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* 模型路径
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/share/models/SWivid/F5-TTS/F5TTS_v1_Base/model_1250000.safetensors
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### 软件仓库
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https://git.opencomputing.cn/yumoqing/f5tts
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### 执行脚本
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```
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#!/usr/bin/bash
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echo start 3 instances for f5tts engine
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rundir=/share/ymq/run/f5tts
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CUDA_VISIBLE_DEVICES=6 ${rundir}/f5tts.env/bin/python ${rundir}/app/f5tts.py -w ${rundir} -p 9995 &
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CUDA_VISIBLE_DEVICES=6 ${rundir}/f5tts.env/bin/python ${rundir}/app/f5tts.py -w ${rundir} -p 9995 &
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CUDA_VISIBLE_DEVICES=6 ${rundir}/f5tts.env/bin/python ${rundir}/app/f5tts.py -w ${rundir} -p 9995 &
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CUDA_VISIBLE_DEVICES=6 ${rundir}/f5tts.env/bin/python ${rundir}/app/f5tts.py -w ${rundir} -p 9995 &
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```
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## fastwhisper.service
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ASR模型
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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User=ymq
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Group=ymq
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Type=forking
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WorkingDirectory=/d/ymq/run/fastwhisper
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ExecStart=/d/ymq/run/fastwhisper/start.sh
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ExecStop=/d/ymq/run/fastwhisper/stop.sh
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StandardOutput=append:/d/ymq/run/fastwhisper/logs/fastwhisper.log
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StandardError=append:/d/ymq/run/fastwhisper/logs/fastwhisper.log
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SyslogIdentifier=fastwhisper
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://asr.opencomputing.net:10443/fw
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### 模型
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* 路径
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/data/ymq/models/deepdml/faster-whisper-large-v3-turbo-ct2
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### 软件仓库
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https://git.opencomputing.cn/yumoqing/fastwhisper
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### 执行脚本
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```
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cd /d/ymq/run/fastwhisper
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/d/ymq/run/fastwhisper/py3/bin/python /d/ymq/run/fastwhisper/app/fastwhisper.py -w /d/ymq/run/fastwhisper &
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exit 0
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```
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## fvlm.service
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fast vlm 模型服务
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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User=ymq
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Group=ymq
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Type=forking
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WorkingDirectory=/share/ymq/run/fvlm
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# ExecStart=/share/ymq/run/fvlm/fvlm.env/bin/python app/fastvlm.py -p 9994
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ExecStart=/share/ymq/run/fvlm/start.sh
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ExecStop=/share/ymq/run/fvlm/stop.sh
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StandardOutput=append:/var/log/fvlm/fvlm.log
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StandardError=append:/var/log/fvlm/fvlm.log
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SyslogIdentifier=fvlm
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://fastvlm.opencomputing.net:10443
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### 模型
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* 路径
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/share/models/apple/llava-fastvithd_0.5b_stage3
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### 软件仓库
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https://git.kaiyuancloud.cn/yumoqing/fvlm
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### 脚本
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```
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#!/usr/bin/bash
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CUDA_VISIBLE_DEVICES=6 /share/ymq/run/fvlm/fvlm.env/bin/python app/fastvlm.py -p 9994 &
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```
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## m2m.service
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多语言翻译
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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WorkingDirectory=/share/run/m2m
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ExecStart=/share/run/m2m/start.sh
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ExecStop=/share/run/m2m/stop.sh
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StandardOutput=append:/var/log/m2m/m2m.log
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StandardError=append:/var/log/m2m/m2m.log
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SyslogIdentifier=m2m
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://t2t.opencomputing.net:10443/m2m
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### 模型
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* 路径
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/share/models/facebook/m2m100_1.2B
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### 运行脚本
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#!/bin/bash
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```
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/share/vllm-0.8.5/bin/python -m llmengine.m2m -p 8883 /share/models/facebook/m2m100_1.2B
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```
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## neo4j.service
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知识图谱数据库
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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Type=forking
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WorkingDirectory=/share/run/neo4j
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ExecStart=/share/run/neo4j/start.sh
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ExecStop=/share/run/neo4j/stop.sh
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StandardOutput=append:/var/log/neo4j/neo4j.log
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StandardError=append:/var/log/neo4j/neo4j.log
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SyslogIdentifier=/share/run/neo4j
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TimeoutStartSec=300
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://graphdb.opencomputing.net:10443
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### 模型路径
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* 路径
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### 软件仓库
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https://git.opencomputing.cn/yumoqing/llmengine
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### 运行脚本
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```
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#!/bin/bash
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CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.neo4j -p 8885 Neo4j &
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```
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## nvidia-asr.service
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英伟达的ASR模型
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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User=ymq
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Group=ymq
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Type=forking
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WorkingDirectory=/share/ymq/run/nvidia-asr
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ExecStart=/share/ymq/run/nvidia-asr/start.sh
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ExecStop=/share/ymq/run/nvidia-asr/stop.sh
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StandardOutput=append:/var/log/asr/asr.log
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StandardError=append:/var/log/asr/asr.log
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SyslogIdentifier=asr
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://asr.opencomputing.net:10443
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### 模型
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* 路径
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/share/models/nvidia/parakeet-tdt-0.6b-v2/parakeet-tdt-0.6b-v2.nemo
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### 软件仓库
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https://git.opencomputing.cn/yumoqing/nvidia-asr.git
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### 执行脚本
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```
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#!/usr/bin/bash
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rundir=/share/ymq/run/nvidia-asr
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cd $rundir
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CUDA_VISIBLE_DEVICES=6 $rundir/nvidia-asr.env/bin/python app/asr.py -p 9992 &
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# CUDA_VISIBLE_DEVICES=6 $rundir/nvidia-asr.env/bin/python app/asr.py -p 9992 &
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```
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## ollama.service
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```
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[Unit]
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Description=Ollama Service
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After=network-online.target
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[Service]
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ExecStart=/d/ollama/start.sh
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# CUDA_VISIBLE_DEVICES=2,3 /usr/local/bin/ollama serve
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User=ollama
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Group=ollama
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Restart=always
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RestartSec=3
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Environment="PATH=/d/ymq/.local/bin:/d/ymq/bin:/d/ymq/bin:/usr/l
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ocal/cuda-12/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/b
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in:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin"
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[Install]
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WantedBy=default.target
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```
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### http服务
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https://ollama.opencomputing.net:10443
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## qwen3.service
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qwen3-0.6b模型
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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WorkingDirectory=/share/run/qwen3
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Type=forking
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ExecStart=/share/run/qwen3/start.sh
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ExecStop=/share/run/qwen3/stop.sh
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StandardOutput=append:/var/log/qwen3/qwen3.log
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StandardError=append:/var/log/qwen3/qwen3.log
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SyslogIdentifier=qwen3
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[Install]
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```
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### http服务
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https://t2t.opencomputing.net:10443/qwen3-6b
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### 模型
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* 路径
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/d/models/Qwen/Qwen3-0.6B
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### 执行脚本
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```
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#!/usr/bin/bash
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rundir=/share/run/qwen3
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CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.server -w ${rundir} -p 9089 /d/models/Qwen/Qwen3-0.6B &
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exit 0
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```
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## qwen3coder.service
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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WorkingDirectory=/share/run/qwen3coder
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Type=forking
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ExecStart=/share/run/qwen3coder/start.sh
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ExecStop=/share/run/qwen3coder/stop.sh
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StandardOutput=append:/var/log/qwen3coder/qwen3coder.log
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StandardError=append:/var/log/qwen3coder/qwen3coder.log
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SyslogIdentifier=qwen3coder
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://t2t.opencomputing.net:10443
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### 模型
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* 路径
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/d/models/Qwen/Qwen3-Coder-30B-A3B-Instruct
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### 执行脚本
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```
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#!/usr/bin/bash
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rundir=/share/run/qwen3coder
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CUDA_VISIBLE_DEVICES=0 /share/vllm-0.8.5/bin/python -m llmengine.server -w ${rundir} -p 9088 /d/models/Qwen/Qwen3-Coder-30B-A3B-Instruct &
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exit 0
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```
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## reranker.service
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```
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[Unit]
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Description=A Rerank Service using Qwen3-Reranker-0.6B
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# After=network.target DeepSeek70B-kyyds671b-ray.service
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# Requires=DeepSeek70B-kyyds671b-ray.service
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StartLimitIntervalSec=60
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StartLimitBurst=5
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[Service]
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# 核心启动参数（保持原有配置）
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WorkingDirectory=/share/run/reranker
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#定义环境变量，所有节点的启动脚本与服务需一致
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#Environment="NCCL_SOCKET_IFNAME=enp196s0f0np0"
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#ExecStartPre=/data/kyyds671b/ray_check.sh
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ExecStart=/share/run/reranker/start.sh
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ExecStop=/share/run/reranker/stop.sh
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# 超时与停止控制（新增部分）
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# 启动超时延长至 120 秒
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# TimeoutStartSec=120
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# 停止等待时间 30 秒
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# TimeoutStopSec=30
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# 优先发送 SIGINT 信号（更适合 Python 程序）
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# KillSignal=SIGINT
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# 最终强制终止信号
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# RestartKillSignal=SIGKILL
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# 混合终止模式
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# KillMode=mixed
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# 重启策略
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# Restart=on-failure
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# RestartSec=10s
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# 服务管理（保持原有配置+增强）
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#Restart=always
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#RestartSec=10 # 重启间隔从 5 秒调整为 10 秒
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#append 是继续写入相当于>> file是从新写入 相当于>
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StandardOutput=append:/var/log/rerank/rerank.log
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StandardError=append:/var/log/rerank/error.log
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SyslogIdentifier=rerank
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# 资源限制（保持可选配置）
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#LimitNOFILE=65536
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#LimitNPROC=65536
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# GPU 支持
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#Environment=CUDA_VISIBLE_DEVICES=0,1
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://reranker.opencomputing.net:10443
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### 模型
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* 路径
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/share/models/BAAI/bge-reranker-v2-m3
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### 脚本
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```
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#!/bin/bash
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# CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.rerank -p 9997 /d/ymq/models/Qwen/Qwen3-Reranker-0___6B
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CUDA_VISIBLE_DEVICES=4 /share/vllm-0.8.5/bin/python -m llmengine.rerank -p 9997 /share/models/BAAI/bge-reranker-v2-m3
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```
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## subtitler.service
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歌曲歌词对齐服务
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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User=ymq
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Group=ymq
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Type=forking
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WorkingDirectory=/d/ymq/py/subtitle
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ExecStart=/d/ymq/py/subtitle/start.sh
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ExecStop=/d/ymq/py/subtitle/stop.sh
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StandardOutput=append:/var/log/subtitler/subtitler.log
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StandardError=append:/var/log/subtitler/subtitler.log
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SyslogIdentifier=subtitler
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[Install]
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WantedBy=multi-user.target
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```
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### 模型
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* 路径
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1 /data/ymq/models/MahmoudAshraf/mms-300m-1130-forced-aligner
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对齐模型
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2 /data/ymq/models/mdx_models/UVR-MDX-NET-Voc_FT.onnx 分割人声和伴奏
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### 仓库
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https://git.opencomputing.cn/yumoqing/subtitle
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### 脚本
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```
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#!/usr/bin/bash
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cd /d/ymq/py/subtitle
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/d/ymq/py/subtitle/py3/bin/python /d/ymq/py/subtitle/app/subtitler.py -p 9901 -w /d/ymq/py/subtitle &
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exit 0
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```
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## triples.service
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获取三元组
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```
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[Unit]
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Wants=systemd-networkd.service
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[Service]
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Type=forking
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WorkingDirectory=/share/run/triples
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ExecStart=/share/run/triples/start.sh
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ExecStop=/share/run/triples/stop.sh
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StandardOutput=append:/var/log/triples/triples.log
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StandardError=append:/var/log/triples/triples.log
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SyslogIdentifier=/share/run/triples
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[Install]
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WantedBy=multi-user.target
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```
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### http服务
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https://triples.opencomputing.net:10443
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### 模型
|
||
* 路径
|
||
/share/models/Babelscape/mrebel-large
|
||
|
||
### 脚本
|
||
```
|
||
#!/bin/bash
|
||
|
||
CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.triple -p 9991 /share/models/Babelscape/mrebel-large &
|
||
CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.triple -p 9991 /share/models/Babelscape/mrebel-large &
|
||
CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.triple -p 9991 /share/models/Babelscape/mrebel-large &
|
||
```
|
||
|
||
## vdb.service
|
||
milvus向量数据库
|
||
|
||
```
|
||
[Unit]
|
||
Wants=systemd-networkd.service
|
||
|
||
[Service]
|
||
User=wangmeihua
|
||
Group=wangmeihua
|
||
Type=forking
|
||
WorkingDirectory=/d/wangmeihua/vdbtest/vdb
|
||
ExecStart=/d/wangmeihua/vdbtest/vdb/start.sh
|
||
ExecStop=/d/wangmeihua/vdbtest/vdb/stop.sh
|
||
StandardOutput=append:/var/log/vdb/vdb.log
|
||
StandardError=append:/var/log/vdb/vdb.log
|
||
SyslogIdentifier=vdb
|
||
|
||
[Install]
|
||
WantedBy=multi-user.target
|
||
```
|
||
### http服务
|
||
https://vectordb.opencomputing.net:10443/milvus
|
||
|
||
### 仓库
|
||
https://git.opencomputing.cn/yumoqing/vdb
|
||
### 脚本
|
||
```
|
||
#!/usr/bin/bash
|
||
|
||
# 检查是否有 vdb 进程正在运行
|
||
PID=$(ps aux | grep "vdbapp.py" | grep -v grep | awk '{print $2}' | head -1)
|
||
|
||
if [ -n "$PID" ]; then
|
||
echo "错误：VDB 服务已在运行 (PID: $PID)"
|
||
echo "请先停止现有服务：kill $PID"
|
||
exit 1
|
||
fi
|
||
|
||
cd /share/wangmeihua/vdbtest/vdb
|
||
/share/wangmeihua/vdbtest/vdb/vdbvenv/bin/python /d/wangmeihua/vdbtest/vdb/app/vdbapp.py -p 8887 -w /d/wangmeihua/vdbtest/vdb &
|
||
echo "VDB 服务已启动 (PID: $!)"
|
||
exit 0
|
||
```
|