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FAQ
- Admin URL:
/geo_admin/ - Default admin username:
admin - Default admin password:
password
After first login, change the admin password immediately. For source deployments, make sure Laravel APP_KEY has been generated with php artisan key:generate or by the Docker init service.
No.
You can:
- use Docker Compose for
postgres + redis + init + app + queue + scheduler + reverb - or run PHP and PostgreSQL locally
If the goal is to get started quickly and predictably, Docker is the safer option.
Yes.
The current public runtime database is PostgreSQL.
The repository does not include production databases or sample business data.
Because those are runtime or business assets, such as:
- image-library contents
- raw knowledge-base files
- generated articles
- logs and backups
The public repository only includes source code and configuration templates.
Go to:
AI Configurator -> AI Model Settings
Then fill in:
- API URL
- Model ID
- Bearer Token
The system supports OpenAI-style interfaces and handles provider base URLs as well as full endpoint URLs. It also adapts non-/v1 versioned providers such as Zhipu /api/paas/v4 and Volcengine Ark /api/v3.
For knowledge-base RAG, also configure an embedding model and set it as the default embedding model.
The core flow is:
- Configure models and prompts
- Prepare knowledge, title, keyword, image, and author libraries
- Create a task with generation limits and publishing cadence
- Let the scheduler enqueue it
- Let the worker execute generation
- Route content through draft / review / publish
- Deliver the result to the frontend
Yes.
- CLI docs are available in the project documentation
- Companion skill repository: yaojingang/yao-geo-skills
- Public skills currently include:
geoflow-cli-opsgeoflow-template
It is a good fit for:
- independent GEO websites
- GEO sub-channels inside official sites
- internal GEO content operations
- knowledge-base-driven content production
- multi-section or multi-site content operations
This usually means no usable embedding model has been configured yet.
GEOFlow can still split the knowledge document into chunks, but vector writing requires:
- an enabled model whose type is
embedding - a valid API key
- a provider endpoint that supports embeddings
- the model set as the default embedding model
After configuring it, re-save or re-upload the knowledge base so vectors can be written.
Older records may store paths like /uploads/...; the Laravel rewrite serves uploaded public files through /storage/uploads/....
Current code normalizes these paths at render time, but the actual files must still exist under storage/app/public/uploads/... and php artisan storage:link must be valid.
Use the dashboard quick-start path:
- configure API
- configure materials, including authors
- create a task
Start with draft or review mode before enabling full automatic publishing.
- GEO source sites
- internal GEO content backends
- multi-site or multi-channel content operations
It is not a good fit if the goal is mass-producing low-value pages.
Because GEOFlow is only as trustworthy as the knowledge assets behind it.
If the knowledge layer is weak, automation only scales noise.
Recommended order:
- 首页
- 快速上手
- 常见问题
- 部署指南
- 部署脚本使用指南
- 部署检查清单
- 模板与主题工作流
- 模型接入指南
- AI 知识库教程
- 知识库切片与 RAG
- 分发管理与目标站点
- 数据分析与日志
- 什么是 GEOFlow
- GEOFlow 方法论
- 使用边界与内容底线
- 适用场景
- 场景部署与使用方式
- 核心能力总览
- 推荐采用路径
- Skill / CLI / API 生态
- 路线图
- 作者与项目
- Home
- Getting Started
- FAQ
- Deployment Guide
- Deployment Scripts Guide
- Deployment Checklist
- Theme and Template Workflow
- Model Setup Guide
- AI Knowledge Base Tutorial
- Knowledge Chunking and RAG
- Distribution Management and Target Sites
- Analytics and Logs
- What Is GEOFlow
- GEOFlow Methodology
- Principles and Content Boundaries
- Use Cases
- Deployment Patterns by Scenario
- Core Capabilities
- Recommended Adoption Path
- Skill / CLI / API Ecosystem
- Roadmap
- Author and Project