yoheinakajima/instagraph
Converts text input or URL into knowledge graph and displays observed · 2026-08-28
Health v2 · maintenance only
28/100
- Activity 0
- Release rhythm 35
- Longevity 77
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1086
- days_rel: n/a
- days_push: 983
- n_releases_24m: 0
Adoption not part of the score
3553 stars · 285 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
InstaGraph is a Flask web application that converts text input or URLs into knowledge graphs using OpenAI's GPT-3.5. It renders color-coded, interactive graphs and can optionally store them in Neo4j or FalkorDB graph databases.
Use cases
- convert text into a knowledge graph
- visualize relationships between entities in a document
- extract a knowledge graph from a URL
- store extracted entities and relations in Neo4j
- generate a graph from article content
When to choose
- you want a quick, visual knowledge graph from unstructured text
- you want a simple self-hosted Flask app with optional graph database persistence
When to avoid
- you need production-grade entity extraction accuracy or fine-grained control over the LLM pipeline
- you need a scalable service for high-volume graph extraction
Facets
application · maturity maintenance
llm-inference data-visualization rag data-visualization python flask openai gpt-3.5 neo4j falkordb knowledge-graph text-to-graph knowledge-graphs natural-language-processing web-server docker
1 source
- readme: https://github.com/yoheinakajima/instagraph · fetched 2026-08-28 · 4507f3244172
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| yoheinakajima/instagraph | main | 28 |
For agents
markdown · JSON · MCP: product_card(name="yoheinakajima/instagraph")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem