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Functionalities

Per-feature reference, split by topic under docs/features/. The table below is the authoritative routing index — start here.

Per feature

Page Covers
Infrastructure & quality Compose, tests, error handling, code splitting, typecheck
Documents Document channels, upload, parsing pipeline (PaddleOCR-VL, Baidu Cloud), openkms-cli
Articles Article channels, CRUD, relationships, lifecycle, attachments, bulk import
Media library Media channels, image/video assets, metadata, upload, Zhipu AI generation ( media toggle, default off)
Comments User comments and 0–5 ratings on articles, documents, KBs, wiki spaces, agent projects
Knowledge bases KB CRUD, FAQs, chunks, semantic search, QA proxy, kb-index
Wiki spaces Wiki content (path-addressed pages, files, vault), import, graph view
Evaluation Evaluations, items, runs, compare (experimental toggle; quality-improvement workflows still evolving)
Glossaries Bilingual terms, AI suggestion, import/export
Knowledge map & home Knowledge Map terms, resource links, home hub graph
Global search /search page: documents, articles, wiki spaces, knowledge bases, media (name, channel, updated filters)
Ontology — objects, links, datasets Object/link types, instances, data sources, datasets
Data layer (Datasets · Semantic Model · Data Insights) Catalog + semantic model: datasets, relationships (FK edges), quality rules, metrics, file ingest, profile/schema, row editing (data:*); Data Insights stories of findings, each with its own source (explorer:*)
Ontology Functions Three Suite Apps (Manager, Object Explorer, Function Editor), PG-backed functions, ofs runtime
Apps (hosted modules) Register Kubernetes Services as Apps; API-server proxy + identity headers; gallery / run / registry settings
Ontology Function Client openkms_functions Client / @function / edits; string api names
Object Explorer Cypher exploration, list view, instance graph layout and rendering
Pipelines, jobs & models Pipeline templates, procrastinate jobs, provider/model registry (multimodal image/video models planned)
Data security Two-layer model (operation RBAC + resource ACL), groups, sharing, inheritance, enforcement
Console & authentication Permission catalog, Console UX, OIDC/local auth, system settings, user Settings (API keys), feature toggles
Kubernetes clusters Console BYO cluster: browse Deployments/Services/Pods, logs, apply/delete; register a Service in Apps
Connectors /connectors sync & search_tool kinds, dataset outputs, Tushare sync jobs, schedules, Agents web_search
Agents (project workspaces) Deep Agents chat, files, local/remote git, plan mode, openKMS research tools
openkms-skill Agent Skill + CLI (openkms-skill/); openKMS Agents, Claude Code, OpenCode, etc. — not a substitute for domain in-app assistants
Tutorial: Understanding the ontology (Kanban lab) Learn ontology by building a mini Kanban (Project / WorkItem / Person + decision FoO)
Tutorial: Tushare market ontology (DIY) Domain case study: sync → Stock → FoO (requires ontology intro)

Cross-cutting reference

Page Covers
Knowledge types Taxonomy (artifacts, indexes, dimensions); insect-research workflow table; when to add a Recordings/Video functionality (anchor)
API reference One table of every HTTP endpoint, grouped by area
Data models Schema for every persisted table
Configuration Backend deps, pgvector, S3/MinIO, contributor rules

Where to add new content

When something changes in code, edit the most specific page in the table above:

  • New endpoint → matching feature page and API reference.
  • New schema column → Data models and the feature page that uses it.
  • New feature surface → its dedicated feature page; if no page fits, add a new file under docs/features/, link it here, and add a nav: entry in mkdocs.yml.

See Doc conventions for AI agents for the full editing checklist.