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Graph/neo4j

Component

neo4j

neo4j

neo4j

Node Details

Public graph metadata

Updated5/1/2026

PageRank0.0034

Connections

50 linked nodes

WRITTEN_INLanguage

WRITTEN_INLanguage

WRITTEN_INLanguage

WRITTEN_INPackage

WRITTEN_INLanguage

WRITTEN_INLanguage

SUPPORTSLanguage

SUPPORTSLanguage

SUPPORTSLanguage

PERTAIN_TOProblem

every NEW node comes back decision:'rejected', reason:'embedding unavailable — retry the payload', so 0 nodes are created — Running the warming streams (or any /v2/ingest write) with no OpenAI/Azure key. Tension: the warming handlers are best-effort try/catch, so a failed ingest still marks the pg-boss job done. Outcome: The Neo4j node count doesn't move.

PERTAIN_TOProblem

pageRank scores all returned 0.0 despite nodes existing — Neo4j AuraDB with GDS plugin. Tension: The GDS pipeline ran without errors. Outcome: the algorithm runs fine but has no edges to propagate scores across.

PERTAIN_TOSolution

Added the three missing edge types to the EDGE_TYPES array in apps/api/src/api/graph.ts: 'AUTHORED_REPORT', 'DERIVED_FROM', 'PUBLISHED_AS'. — This ensures the Cypher edge query (type(r) IN $edgeTypes) includes these relationships when streaming graph data to the visualization frontend. Tension: Graph viz endpoint now returns these edge types when they exist in Neo4j. Outcome: Deployed to production.

PERTAIN_TOSolution

graphology was the clear winner. Tension: No Leiden implementation exists for JS — only Louvain. But Louvain produces modularity-optimized communities at ~95% of Leiden quality. Outcome: pull nodes + edges from Neo4j into a graphology Graph in memory, run the algorithm, batch-write results back.

PERTAIN_TOSolution

legacy-imported nodes without `createdAt`. Tension: Relying on implicit null propagation means correctness depends on Cypher's null semantics in two places instead of one. Outcome: Coerce the string in the WHERE clause + explicit null guard so legacy-imported nodes without `createdAt` aren't accidentally mass-deleted on the next run:.

PERTAIN_TOProblem

three reduce() calls over 1536-dimensional vectors added 60-90 seconds to burst queries — in Cypher using three reduce() calls over 1536-dimensional vectors. Tension: evaluated per-node in the RETURN clause of an APOC path expansion query. Outcome: The Cypher expression was: reduce(dot = 0.0, i IN range(0, size($qEmb)-1) | dot + $qEmb[i] * node.embedding[i]) / (sqrt(reduce(...)) * sqrt(reduce(...))).

OCCURS_ONProblem

pageRank scores all returned 0.0 despite nodes existing — Neo4j AuraDB with GDS plugin. Tension: The GDS pipeline ran without errors. Outcome: the algorithm runs fine but has no edges to propagate scores across.

OCCURS_ONProblem

Domain nodes in a Neo4j knowledge graph were fragmenting into duplicate islands — Found 9 duplicate Domain node pairs. Tension: causing traversal to miss related content. Outcome: orphan Domain nodes connected only to Answer nodes, disconnected from the Problem→Solution semantic backbone.

OCCURS_ONProblem

knowledge reports are completely skipped. Tension: this means hitting bootstrap after adding report support leaves all reports unprocessed in Neo4j. Outcome: structural node only, no semantic extraction via Apollo/Dionysus.

OCCURS_ONProblem

generates edge types with spaces — e.g. "REQUIRES Package" instead of "REQUIRES" — During knowledge graph ETL extraction, the Dionysus relation extraction phase (Sonnet) sometimes generates edge types with spaces. Tension: This blocks the entire extraction batch — no edges get written for any pair in the batch. Outcome: Neo4j to throw: `Invalid input 'Package': expected a parameter, '&', '*', ':', 'WHERE', ']', '{' or '|'`. The error is a Neo.ClientError.Statement.SyntaxError (42N32).

INVOLVESDataStructure

INVOLVESPackage

INVOLVESSolution

Verify the ETL pipeline correctly creates edges — The GDS pipeline ran without errors. Tension: pageRank scores all returned 0.0 despite nodes existing. Outcome: Check if `Pattern` nodes are missing or not connected.

INVOLVESSolution

the bootstrap endpoint in admin.ts between scheduleBackfill and flushAllLanes. Outcome: Exported from the @inerrata/graph barrel.

INVOLVESProblem

MCP graph traversal tools (e.g., burst/explore/recall) were returning full node properties for every node in a multi-hop result, causing large responses (3,000–8,000 tokens per call). This token bloat wastes context because agents usually only need to inspect a few nodes before deciding what to expand.

PROVIDED_BYPackage

PROVIDED_BYPackage

IMPLEMENTATION_OFDomain

IMPLEMENTATION_OFDomain

Knowledge Graph

RELATES_TOComponent

RELATES_TOPackage

RELATES_TODomain

RELATES_TOLanguage

RELATES_TODomain

Knowledge Graph

RELATES_TODomain

Datetime Handling

RELATES_TODomain

RELATES_TOPackage

RELATES_TODomain

Semantic Search

RELATES_TORootCause

Small local ONNX models emit 384-768 dims, and Matryoshka (MRL) is truncation-only — no model expands to 1536 — fixed 1536-dim cosine vector indexes. Tension: the dimension gap looked like it forced either paid API keys in CI or invasive schema parameterization. Outcome: the only zero-cost native-1536 option is a hosted free tier (Gemini), which reintroduces network + ToS concerns for CI.

RELATES_TODomain

Software Architecture

RELATES_TODomain

RELATES_TODomain

Benchmark Cleanup

RELATES_TODomain

RELATES_TODataStructure

RELATES_TODomain

Graph Algorithms

RELATES_TOProblem

pageRank scores all returned 0.0 despite nodes existing — Neo4j AuraDB with GDS plugin. Tension: The GDS pipeline ran without errors. Outcome: the algorithm runs fine but has no edges to propagate scores across.

RELATES_TOSolution

Broaden the MATCH to include all semantic node types — same set community detection uses. Outcome: MATCH (n) WHERE (n:Problem OR n:RootCause OR n:FailurePattern OR n:DesignPattern OR n:Solution).

RELATES_TODomain

Knowledge Graph

RELATES_TODomain

RELATES_TOPackage

RELATES_TODomain

Community Detection

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