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yaojingang edited this page Jun 26, 2026 · 11 revisions

GEOFlow Wiki Home

Welcome to the GEOFlow Wiki.

GEOFlow is an open-source system for GEO content engineering, AI-search-ready publishing, multi-site distribution, and automated content operations. It is not just a CMS and not just an AI writing tool. It is closer to a content operating system that connects models, Enterprise Knowledge, materials, tasks, review, publishing, analytics, GEOFlow Agent / WordPress REST / Generic HTTP API distribution, and Skill / CLI / API collaboration into one workflow.

Current public version: v2.1.0, released on 2026-06-26. See the Changelog.

UI Preview

GEOFlow analytics preview
Analytics
GEOFlow site settings preview
Site Settings
GEOFlow admin dashboard preview
Admin Dashboard
GEOFlow task management preview
Task Management
GEOFlow AI model configuration preview
AI Model Configuration
GEOFlow materials preview
Materials

This wiki is meant to answer six questions:

  • What GEOFlow actually is
  • Which teams and scenarios it fits
  • What its methodology is
  • What its content boundaries and operating principles are
  • How it should be deployed, distributed, and adopted
  • Where it is heading next

Recommended reading order:

  1. What Is GEOFlow
  2. GEOFlow Methodology
  3. Principles and Content Boundaries
  4. Use Cases
  5. Deployment Patterns by Scenario
  6. Core Capabilities
  7. Model Setup Guide
  8. AI Knowledge Base Tutorial
  9. Knowledge Chunking and RAG
  10. Distribution Management and Target Sites
  11. Analytics and Logs
  12. Theme and Template Workflow
  13. Changelog
  14. Recommended Adoption Path
  15. Skill / CLI / API Ecosystem
  16. Roadmap
  17. Author and Project
  18. Getting Started
  19. FAQ
  20. Deployment Guide
  21. Deployment Scripts Guide
  22. Deployment Checklist

If there is one line that best describes GEOFlow:

It turns knowledge assets, AI content generation, review, publishing, analytics, multi-site distribution, and automation into an engineered operating workflow.

Its current strengths include:

  • Multi-model integration with OpenAI-compatible providers and native Gemini endpoints
  • chat / embedding model types, provider URL adaptation, and connection tests
  • Centralized material libraries
  • author libraries, semantic knowledge chunk planning, Enterprise Knowledge draft generation, and vectorization status preview
  • Task scheduling, queueing, and worker execution
  • Draft, review, and publish workflows, including local / channel / local-plus-channel publication scope
  • Search- and AI-citation-ready frontend output
  • GFM Markdown article rendering and legacy image path normalization
  • Theme preview, activation, live editing, and theme packages
  • Distribution Management, GEOFlow Agent target-site packages, WordPress REST channels, and Generic HTTP API channels
  • Static homepages, article pages, sitemap, llms.txt, and TXT map generation
  • Analytics for system overview, single-site operations, multi-site distribution, access logs, and AI crawlers
  • admin i18n, GitHub version update reminders, and admin account management
  • Skill / CLI / API collaboration

The system is meant to amplify the value of real knowledge assets, not to amplify noise.

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