Hypabase

Name: hypabase
Author: hypabase

PyPI Python License Downloads

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:

HyperGraphRAG — n-ary knowledge retrieval across medicine, agriculture, CS, and law
Cog-RAG — dual-hypergraph retrieval with theme-level and entity-level recall
Hypergraph Memory for Multi-step RAG — hypergraph-based memory for long-context relational modeling

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")

Provenance

Every edge carries source and confidence:

hb.edge( ["patient_123", "aspirin", "ibuprofen"], type="drug_interaction", source="clinical_decision_support_v3", confidence=0.92, ) # Bulk provenance with hb.context(source="schema_analysis", confidence=0.9): hb.edge(["a", "b"], type="fk") hb.edge(["b", "c"], type="fk") # Query by provenance hb.edges(source="clinical_decision_support_v3") hb.edges(min_confidence=0.9) # Overview of all sources hb.sources()

Namespace isolation

Isolate data into separate namespaces within a single database file:

hb = Hypabase("knowledge.db") drugs = hb.database("drugs") sessions = hb.database("sessions") drugs.node("aspirin", type="drug") sessions.node("s1", type="session") drugs.nodes() # → [aspirin] sessions.nodes() # → [s1]

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
Namespace isolation — .database("name") for scoped views in a single file
MCP server — 14 tools + 2 resources for AI agent integration
CLI — hypabase init, hypabase node, hypabase edge, hypabase query