部署该项目需要分阶段完成环境配置，主要流程如下：
pre-positioning
- 基础环境：Python 3.8+、Node.js、Redis和PostgreSQL
- API密钥：必须的Gemini API Key(通过Google AI Studio获取)，可选的LangSmith调试密钥
Installation steps
- clone warehouse::
git clone https://github.com/google-gemini/gemini-fullstack-langgraph-quickstart.git - Configuration Keys：在backend目录创建.env文件写入API密钥
- Installation of dependencies::
- Rear end:
pip install . - Front End:
npm install
- Rear end:
运行方案
- development model::
npm run dev同时启动前后端 - Docker Deployment：通过docker-compose up构建容器化服务
特别注意：若使用数据持久化功能，需提前配置PostgreSQL连接字符串到.env文件。
This answer comes from the articleGemini Fullstack LangGraph: a full-stack application for intelligent research based on Gemini and LangGraphThe
May not be reproduced without permission:AI productivity tools " 如何安装部署gemini-fullstack-langgraph-quickstart项目？需要哪些前置条件？
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