Skip to content
The Daily Repo

Ontos-AI / knowhere

Knowhere extracts, parses, and outputs structured chunks ready for AI Agents and RAG.

Why this job: works in the areas we cover, but does not say which job it does

What it does

  • Dual-track Parsing. Vision and Text tracks handle different document conditions while producing the same downstream schema.
  • Vision Page Understanding. Frontier vision models make complex PDF and PowerPoint content recallable without requiring perfect element-by-element OCR or layout reconstruction.
  • Hierarchy-native Memory. Section nodes preserve document paths, page ranges, summaries, entities, and linked assets instead of returning disconnected chunks.
  • Cross-document Memory Graph. Page-derived typed entities and keywords connect related documents across a namespace.
  • Agent-native Retrieval. Built-in and MCP-connected agents explore the same corpus schema and hierarchy-aware tools; classic retrieval remains available for deterministic top-K search.

Get started

uv sync --all-packages

You need: Python 3.11+; Docker with docker compose

Maintenance
Active
Last commit today
Stars
3,942
+63 this week
Licence
Apache-2.0
Allows business use
Downloads for
None listed
No release files
Latest version
v1.2.49
Released today
Built with
Python
95% of the code

Is it looked after?

Contributors
2
Last 90 days
Issues
69% closed
25 still open
Pull requests
384 merged
24 waiting
Releases
105
30+ in the last year
More: languages, topics and project record

Languages

  • Python 95%
  • HTML 5%
  • Shell <1%
  • Makefile <1%

Topics

  • ai-agents
  • claude-code
  • cursor
  • langchain
  • rag-pipeline
  • skills
  • agent-harness
  • codex
  • document-intelligence
  • mutli-agent
  • vector-database

Project record

  • JobOther AI tools
  • StatusListed
  • Commits2,230
  • Forks339
  • Watching84
  • Stars in 28 days+337
  • CreatedApr 30, 2026
  • First seen by usNov 7, 2026
  • CheckedNov 9, 2026

Type to search.

Try