weknora-rag-search

name weknora-rag-search description Use when retrieving from or asking questions against a WeKnora knowledge base via the `weknora` CLI — and especially when unsure whether to use `chat`, `session ask`, or `search chunks` for a given goal. metadata {"tested_against":"v0.10"} WeKnora — retrieval & RAG queries REQUIRED BACKGROUND: read the weknora-shared skill first (auth, --kb resolution, the JSON envelope, exit codes, streaming/NDJSON output). WeKnora gives you several ways to "ask about a knowledge base." Picking the wrong one wastes turns or returns the wrong shape. Use the decision table. Pick the command by your goal Your goal Command LLM synthesis? Returns Natural-language answer grounded in a KB chat "<q>" --kb <kb> yes bounded answer events; --reference adds citations; --verbose adds execution detail Answer via a custom agent (its own KB scope, tools, web search) session ask --agent <id> "<q>" yes (+ tools) bounded answer events; --reference adds citations; --verbose adds execution detail Raw context chunks to reason over yourself (no answer) search chunks "<q>" --kb <kb> no ranked chunk list Which documents match a keyword (title/filename) search docs "<q>" --kb <kb> no document list Find a knowledge base by name search kb "<q>" no KB list Find a past session by title search sessions "<q>" no session list The three decisions that matter Answer vs raw context. Want a written answer → chat / session ask . Want chunks to feed into your own reasoning (e.g. you'll synthesize across sources) → search chunks . Don't call chat just to read source text. chat vs session ask . chat = plain KB RAG Q&A. session ask --agent <id> = invoke a configured custom agent (it may scope its own KBs, call tools, do web search). If the user set up an agent for this, prefer it ( weknora agent list to find ids); otherwise chat . One-shot vs multi-turn. Both chat and session ask return a data.session_id in default JSON output. Pass --session <id> on the next call to continue the conversation. In NDJSON mode, read it from init . Safety / Gotchas chat , search chunks , search docs need a KB: pass --kb <id-or-name> , or set WEKNORA_KB_ID , or weknora link the directory (resolved in that order). If none resolves it's exit 1 ( local.kb_id_required ); a bad name is exit 1 ( local.kb_not_found ). Resolve names with weknora kb list / search kb . ( search kb / search sessions are tenant-wide and take no --kb .) chat / session ask return one buffered JSON envelope with answer events by default. Add --reference for indexed citations and --verbose for execution detail; use --format ndjson for raw events or --format text for the live human-readable projection. A stalled stream is not stopped by Ctrl-C (that just drops your local connection; the server keeps generating + billing). Stop it server-side: weknora session stop <session-id> --message <message-id> (session_id from data.session_id , or from init under --format ndjson ). Re-attach to a stream with weknora session resume <session-id> --message <message-id> . search chunks --limit defaults to 8 (tuned for an LLM context window); the search docs/kb/sessions lists default to 30. Tune retrieval with --vector-threshold / --keyword-threshold , or --no-vector / --no-keyword to disable a channel. Details: references/search-chunks.md . Quick examples # raw retrieval to reason over weknora search chunks "retry backoff policy" --kb engineering -- limit 12 # grounded answer (human transcript) weknora chat "How do we handle retries?" --kb engineering --format text # continue the conversation (session id from data.session_id above) weknora chat "And the max attempts?" --kb engineering --session sess_abc # answer via a custom agent weknora session ask --agent ag_123 "Summarize this quarter's incidents"