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GraphForge v0.4.0: Three-Surface API

GraphForge v0.4.0 completed the three-surface architecture: Cypher execution, graph algorithms, and hybrid search.

GraphForge v0.4.0: Three-Surface API visual summary

Open Source release

GraphForge is Curate Labs work, released through the DecisionNerd open-source organization. This post is a release note for embedded graph tooling and analytical Python workflows.

GraphForge v0.4.0 completes the three-surface API: `db.execute`, `db.gds`, and `db.search`.

That is the release where GraphForge becomes less like a query engine alone and more like an embedded graph workbench for Python.

What Shipped

  • `db.gds` graph algorithms backed by igraph or NetworkX

  • PageRank, centrality, Louvain, connected components, clustering coefficient, and triangle count

  • `db.search` with FTS5 text search, vector cosine similarity, and reciprocal-rank-fusion hybrid retrieval

  • Bring-your-own vectors for text embeddings, geo coordinates, temporal features, or numeric arrays

  • `graphforge.recipes`, including neighbourhood context helpers

  • Bulk property write-back and improved export parameters

  • Benchmark suite and integration tests for three-surface interoperability

Why it matters

This release expresses the larger GraphForge idea: graph work is not only storage and query. Analysts need query, algorithms, retrieval, recipes, and export to fit together in one local workflow.

Source