{ "cells": [ { "cell_type": "raw", "metadata": { "vscode": { "languageId": "raw" } }, "source": [ "# Vanna Chainlit ChromaDB 测试 Notebook\n", "\n", "这个 Notebook 用于测试项目的各种功能和 API。\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# 导入必要的模块\n", "import sys\n", "import os\n", "\n", "# 添加项目根目录到 Python 路径\n", "sys.path.append(os.path.join(os.path.dirname(os.getcwd())))\n", "\n", "print(\"项目路径已添加到 Python 路径\")\n" ] }, { "cell_type": "raw", "metadata": { "vscode": { "languageId": "raw" } }, "source": [ "## 1. 测试配置加载\n", "\n", "测试项目的各种配置是否能正常加载。\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# 测试配置加载\n", "try:\n", " import app_config\n", " print(\"配置加载成功!\")\n", " print(f\"LLM模型类型: {app_config.LLM_MODEL_TYPE}\")\n", " print(f\"API LLM模型: {app_config.API_LLM_MODEL}\")\n", " print(f\"向量数据库类型: {app_config.VECTOR_DB_TYPE}\")\n", "except Exception as e:\n", " print(f\"配置加载失败: {e}\")\n" ] }, { "cell_type": "raw", "metadata": { "vscode": { "languageId": "raw" } }, "source": [ "## 2. 测试数据管道工具\n", "\n", "测试数据管道模块的配置和功能。\n", "ceshi \n", "ceshi " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# 测试数据管道模块\n", "try:\n", " from data_pipeline.config import SCHEMA_TOOLS_CONFIG\n", " print(\"数据管道配置加载成功!\")\n", " print(f\"输出目录: {SCHEMA_TOOLS_CONFIG['output_directory']}\")\n", " print(f\"最大表数量: {SCHEMA_TOOLS_CONFIG['qs_generation']['max_tables']}\")\n", "except Exception as e:\n", " print(f\"数据管道配置加载失败: {e}\")\n" ] }, { "cell_type": "raw", "metadata": { "vscode": { "languageId": "raw" } }, "source": [ "## 总结\n", "\n", "这个 Notebook 用于测试项目的各个组件,包括:\n", "- 配置加载\n", "- 数据管道工具\n", "- Vanna 实例创建\n", "- 工具函数\n", "- 日志系统\n", "\n", "可以根据需要添加更多的测试用例。\n", "\n", "### 使用说明\n", "\n", "1. 确保已激活项目的虚拟环境:\n", " ```bash\n", " .\\.venv\\Scripts\\Activate.ps1\n", " ```\n", "\n", "2. 安装 Jupyter(如果尚未安装):\n", " ```bash\n", " pip install jupyter\n", " ```\n", "\n", "3. 启动 Jupyter:\n", " ```bash\n", " jupyter notebook\n", " ```\n" ] } ], "metadata": { "language_info": { "name": "python" } }, "nbformat": 4, "nbformat_minor": 2 }