# ── Stage 1: 依赖安装 ──────────────────────────────────────
FROM python:3.12-slim AS builder

WORKDIR /build

# 先拷贝依赖文件，利用 Docker 缓存
COPY requirements.lock.txt .

RUN pip install --no-cache-dir -r requirements.lock.txt

# ── Stage 2: 运行时 ────────────────────────────────────────
FROM python:3.12-slim

LABEL maintainer="LLM Compass"
LABEL description="智能LLM路由服务，为请求指引最优模型"

WORKDIR /app

# 安装运行时系统依赖（sentencepiece 等）
RUN apt-get update && \
    apt-get install -y --no-install-recommends libgomp1 && \
    rm -rf /var/lib/apt/lists/*

# 从 builder 拷贝 Python 包
COPY --from=builder /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages
COPY --from=builder /usr/local/bin /usr/local/bin

# 拷贝应用代码
COPY config.py main.py nvidia_router.py ./

# 创建数据目录
RUN mkdir -p /app/data

# 预下载 NVIDIA 模型（构建时缓存，避免每次启动下载）
RUN python -c "from nvidia_router import get_nvidia_router; r = get_nvidia_router(); r.initialize(); print('Model preloaded successfully')" || echo "Model preload failed, will download on first request"

# 环境变量（敏感信息通过 docker-compose / --env-file 注入）
ENV PYTHONUNBUFFERED=1

# 暴露端口
EXPOSE 8000

# 数据持久化
VOLUME ["/app/data"]

# 启动命令
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "1"]
