The Knowledge Base page (/knowledge-base) is your window into RoboCo's in-house RAG — the pgvector-backed retrieval engine the agents use to find prior context. From here you search the indexes, ask synthesized questions and get answers with citations, talk to the mentor, browse by category, and (in the Admin tab) reindex or clear the indexes. The page is organized into five tabs, with the active tab held in the URL.
Search
Free-text search across the indexes, with an optional filter to scope the query to specific index types. This is the raw retrieval view — it returns the matching chunks so you can see exactly what the agents would find.
Ask
The RAG question-and-answer surface. You ask a question in natural language and get a synthesized answer with citations back to the source documents, rather than a raw chunk list. This is the layer that turns the indexes into an answer.
Mentor
A mentor chat — the same roboco_ask_mentor capability the agents reach through their gateway, exposed to you conversationally for asking about the codebase and accumulated knowledge.
Browse
Browse the indexed content by category rather than by query, when you want to see what's in an index instead of searching for something specific.
Admin
The control surface for the indexes themselves. The KB is split into several index types — Documentation, Conversations, Agent Journals, Error Solutions, Standards, Decisions, Code Reviews, and Learnings — and the Admin tab shows per-index stats and lets you maintain them:
| Action | Effect |
|---|---|
| Reindex all | rebuild every index from source (force) |
| Refresh (per index) | re-pull and re-embed that one index |
| Delete (per index) | clear that index's contents |
Clearing an index removes its embeddings, and a full reindex re-embeds everything from scratch — both take real work and real Ollama time. Delete is guarded behind a confirmation dialog. Treat the Admin tab as a maintenance surface, not a daily one.
It depends on Ollama
The whole page — search, ask, mentor, and especially reindexing — runs on the embedding model served by Ollama (qwen3-embedding:0.6b). If Ollama isn't healthy, queries return nothing useful and reindexing can't embed.
A common first-run symptom is an empty or failing KB while Ollama is still pulling models, or when the embedding endpoint is unreachable. Check that the ollama service is up and the model is pulled — see common issues. The RAG engine and its configuration are covered under deployment.
Next
→ Communications & journals — the raw conversations and journals that feed several of these indexes — or the Auditor for quality oversight.