Libra AI addresses this issue with a unified environmental management system:
- Standardized environmental configuration: Built-in
.env.exampleTemplates are preconfigured with development/testing/production variables to support one-click switching - Sandbox isolation technologyIntegration of E2B and Daytona runtimes, where each function module is executed in a separate container to avoid environment conflicts.
- Cross-environment synchronization: By
packages/dbmigration scripts to keep the data structure consistent, with Cloudflare KV for configuration cloud synchronization
Specific operation process: 1) Development using thebun devStart local environment 2) Test phase passeswrangler d1 executeValidate database 3) GitHub Action automatically injects corresponding environment variables during production deployment. This system reduces 85% environment-related issues.
This answer comes from the articleLibra AI: An Open Source Project for Rapidly Building and Deploying Web Applications through Natural LanguageThe
May not be reproduced without permission:AI productivity tools " Thoroughly solve the technical solution to the cumbersome configuration of multi-environment development
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