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Hypabase

Hypabase is a Python library for storing and querying relationships between entities. A single edge connects two or more nodes, every edge tracks where it came from (source and confidence), and the whole graph lives in a local SQLite file with no server or configuration.

Use it to build knowledge graphs, retrieval-augmented generation pipelines, and structured agent memory. Recent research explores hypergraph representations for these tasks:

Install

uv add hypabase

Quick example

from hypabase import Hypabase

hb = Hypabase("my.db")  # local SQLite, zero config

# One edge connecting five entities
hb.edge(
    ["dr_smith", "patient_123", "aspirin", "headache", "mercy_hospital"],
    type="treatment",
    source="clinical_records",
    confidence=0.95,
)

# Query edges involving a node
hb.edges(containing=["patient_123"])

# Find paths between entities
hb.paths("dr_smith", "mercy_hospital")

See Getting Started for the full walkthrough.

Features

  • N-ary hyperedges — an edge connects 2+ nodes in a single relationship
  • O(1) vertex-set lookup — find edges by their exact node set
  • Provenance — every edge carries source and confidence
  • Provenance queries — filter by source and min_confidence, summarize with sources()
  • SQLite persistence — local-first, zero-config
  • CLI — hypabase init, hypabase node, hypabase edge, hypabase query
  • Python SDK — keyword args, method names read like English

Limitations

  • No semantic similarity or fuzzy search — pair with a vector database for that (hybrid pattern)
  • No declarative query language (e.g., Cypher, SPARQL) — use the Python SDK, CLI, or MCP tools
  • No built-in visualization
  • Early project — small community

Next steps