Knowledge bases ingest documents asynchronously (parse → chunk → embed) and let you search the result:Documentation Index
Fetch the complete documentation index at: https://docs.noxus.ai/llms.txt
Use this file to discover all available pages before exploring further.
- Upload —
POST /v1/knowledge-bases/{kb_id}/upload_train(multipart). Returns run ids you can poll. - Search —
POST /v1/knowledge-bases/{kb_id}/search.
kb_id and your_api_key. Use the prefix parameter to organise and
scope documents into folders.
Upload documents and wait for ingestion
Upload returns immediately with run ids; ingestion runs in the background.
Poll the training runs (SDK
get_runs, or the
running jobs endpoint) until
they complete before searching. Don’t set Content-Type yourself on the
upload — let your HTTP client set the multipart boundary.Search the knowledge base
Runs a semantic / hybrid query (depending on the KB’s retrieval settings) over
the ingested content and returns the matching chunks with their source
documents. Scope the search with
prefix.Async / await with the SDK
Use the
a-prefixed coroutines (aget, aupload_document, aget_runs,
asearch) from async code so the event loop stays responsive.Python SDK