Create a new tenant in WeKnora

List all tenants

Create a new knowledge base

List all knowledge bases

Get knowledge base details

Delete a knowledge base

Perform hybrid search in knowledge base

Create knowledge from a local file on the server filesystem

Create knowledge from URL

List knowledge in a knowledge base

Get knowledge details

Delete knowledge

Create a new model

List all models

Get model details

Create a new chat session with conversation strategy for a knowledge base

Get session details

List chat sessions

Delete a session

RAG pipeline chat: retrieve relevant chunks from knowledge bases, then summarise with LLM. ALWAYS provide knowledge_base_ids (names like 'my-knowledge-base' or UUIDs) so retrieval can run — without them the answer is based on LLM knowledge only. Use list_knowledge_bases to discover available knowledge bases. For multi-step reasoning or tool-calling use agent_chat instead.

Agentic pipeline chat: the agent autonomously calls tools (knowledge_search, web_search, SQL, etc.) to answer the query. Use this for complex multi-step questions or comparative analysis. REQUIRED: agent_id (name or UUID) — use list_agents to discover agents. IMPORTANT: many agents have KBSelectionMode=none and NO built-in knowledge bases. In that case you MUST pass knowledge_base_ids, otherwise the agent will fail with 'no search targets available'. Use get_agent to inspect an agent's kb_selection_mode and knowledge_bases before calling. If kb_selection_mode is 'none' or 'selected' with an empty list, always provide knowledge_base_ids.

List all custom agents available to the current tenant. Use this to discover agent IDs, names, and their KB selection mode before calling agent_chat.

Get full configuration of a single agent by UUID or name. Check kb_selection_mode and knowledge_bases fields: if kb_selection_mode is 'none' or 'selected' with an empty knowledge_bases list, you MUST pass knowledge_base_ids when calling agent_chat.

List chunks of knowledge

Delete a chunk

Search wiki pages by full-text query. Returns matching wiki pages with title, slug, summary, and content snippets.

Read a wiki page by its slug. Returns full markdown content, metadata, inbound/outbound links, and source references.

Get a structured wiki index with per-type directory groups. Returns an overview of all wiki pages organized by type (entity, concept, summary, etc.).