crypto_predictor
9320b79730
主要更改： - 修正 TTM 模型包名: tsfm_public -> granite-tsfm - 添加缺失依赖: httpx, schedule, pytorch-lightning, torchmetrics - 移除过时依赖: darts, u8darts - 按功能分类组织依赖 - 添加 Windows/macOS 安装说明注释 - 更新安装脚本和文档中的包名
63 lines
1.7 KiB
Batchfile
63 lines
1.7 KiB
Batchfile
@echo off
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chcp 65001 >nul
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REM ============================================
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REM Windows 环境安装脚本
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REM 安装所有依赖和模型
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REM ============================================
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echo ==========================================
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echo 加密货币预测系统 - Windows 安装脚本
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echo ==========================================
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echo.
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REM 检查 conda
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where conda >nul 2>&1
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if %errorlevel% neq 0 (
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echo [错误] 未找到 conda
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echo 请先安装 Miniconda: https://docs.conda.io/en/latest/miniconda.html
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pause
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exit /b 1
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)
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echo [1/6] 创建 conda 环境...
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call conda create -n crypto_pred_312 python=3.12 -y
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if %errorlevel% neq 0 (
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echo [警告] 环境可能已存在，继续...
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)
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echo.
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echo [2/6] 激活环境...
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call conda activate crypto_pred_312
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echo.
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echo [3/6] 安装 PyTorch (CPU 版本)...
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pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
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echo.
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echo [4/6] 安装项目依赖...
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pip install -r requirements.txt
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echo.
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echo [5/6] 安装 IBM TTM-R2 模型库...
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echo 包名: granite-tsfm (导入时用 tsfm_public)
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pip install granite-tsfm
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echo.
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echo [6/6] 验证安装...
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python -c "import torch; print(f'PyTorch: {torch.__version__}')"
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python -c "import tsfm_public; print('tsfm_public: 已安装')"
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python -c "from training.config import TrainingConfig; c=TrainingConfig(); print(f'设备: {c.get_device()}')"
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echo.
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echo ==========================================
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echo 安装完成!
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echo ==========================================
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echo.
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echo 下一步:
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echo 1. 复制 .env.example 为 .env 并配置数据库
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echo 2. 双击 start_system.bat 启动系统
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echo 3. 访问 http://localhost:8000
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echo.
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pause
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