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升级sglang 和 vllm 版本
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.dockerignore

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logs/
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outputs/
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data/
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.env
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.env
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*.db

.gitignore

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.venv/
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config.yaml
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.env
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*_test.yaml
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*_test.yaml
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*.db

Dockerfile

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# FROM docker.1ms.run/506610466/cuda:12.2.2-runtime-ubuntu20.04-uv
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FROM 506610466/cuda:12.2.2-devel-ubuntu20.04-uv
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# 从基础镜像开始构建,加快构建速度
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# FROM 506610466/gpt_server:base
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RUN apt-get update -y && apt-get install -y numactl build-essential && rm -rf /var/lib/apt/lists/*
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RUN apt-get update -y && apt-get install -y ffmpeg numactl build-essential && rm -rf /var/lib/apt/lists/*
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COPY ./ /gpt_server
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WORKDIR /gpt_server
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# RUN uv sync && uv cache clean

README.md

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source .venv/bin/activate # 激活 uv 环境
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```
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#### 1.2 conda 方式 安装(后期将弃用,可选)
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```bash
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# 1. 创建conda 环境
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conda create -n gpt_server python=3.11
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# 2. 激活conda 环境
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conda activate gpt_server
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# 3. 安装仓库(一定要使用 install.sh 安装,否则无法解决依赖冲突)
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bash install.sh
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```
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### 2. 修改启动配置文件
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install.sh

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pyproject.toml

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[project]
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name = "gpt_server"
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version = "0.6.7"
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version = "0.6.8"
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description = "gpt_server是一个用于生产级部署LLMs、Embedding、Reranker、ASR和TTS的开源框架。"
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readme = "README.md"
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license = { text = "Apache 2.0" }
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"openai==2.6.1",
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"setuptools==75.2.0",
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"streamlit>=1.50.0",
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"torch==2.8.0",
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"torchvision==0.23.0",
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"vllm==0.11.0",
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"torch==2.9.0",
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"torchvision==0.24.0",
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"vllm==0.11.2",
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"qwen_vl_utils",
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"evalscope[perf,rag]>=1.1.1",
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"modelscope>=1.31.0",
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"edge-tts>=7.0.0",
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"funasr>=1.2.6",
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"sglang[all]>=0.5.5",
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"funasr>=1.2.7",
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"sglang[all]>=0.5.5.post3",
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"flashinfer-python",
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"flashtts>=0.1.7",
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"diffusers>=0.35.2",
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"sqlmodel>=0.0.27",
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"autoawq>=0.2.9",
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"lmcache>=0.3.9.post1",
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"lmcache>=0.3.9.post2",
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]
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[tool.uv]
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"soundfile==0.13.1", # infinity
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"outlines-core==0.2.11", # sglang 和 vllm 的冲突
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"peft>=0.17.0", # 和 lmdeloy 冲突
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"torchvision==0.24.0",
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"torch==2.9.0",
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"llguidance>=1.3.0",
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"torchaudio==2.9.0",
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"triton==3.5.0",
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]
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[project.scripts]

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