"use client"; import { type Edge, type EdgeProps, getSmoothStepPath, Handle, MarkerType, type Node, type NodeProps, Position, } from "@xyflow/react"; import { useEffect, useMemo, useState } from "react"; import { FlowCanvas } from "./flow-canvas"; type SourceNodeData = { accent: string; body: string; items: string[]; title: string; }; type StageNodeData = { body: string; index: number; title: string; }; type OutputNodeData = { accent: string; body: string; path: string; tags: string[]; title: string; }; type SourceNode = Node; type StageNode = Node; type OutputNode = Node; type FlowNode = SourceNode | StageNode | OutputNode; const SOURCE_W = 210; const SOURCE_H = 220; const STAGE_W = 360; const STAGE_H = 120; const OUTPUT_W = 340; const OUTPUT_H = 248; const ROW_SOURCES_Y = 80; const ROW_STAGE_START_Y = 380; const STAGE_GAP = 30; const ROW_OUTPUTS_Y = 1030; const STAGE_CENTER_X = 460; const STAGE_X = STAGE_CENTER_X - STAGE_W / 2; const SOURCE_GAP_X = 24; const SOURCES_TOTAL = SOURCE_W * 4 + SOURCE_GAP_X * 3; const SOURCES_START_X = STAGE_CENTER_X - SOURCES_TOTAL / 2; const OUTPUT_GAP_X = 180; const OUTPUTS_TOTAL = OUTPUT_W * 2 + OUTPUT_GAP_X; const OUTPUTS_START_X = STAGE_CENTER_X - OUTPUTS_TOTAL / 2; const EDGE_STROKE = "#94a3b8"; const sourceData: SourceNodeData[] = [ { title: "Databases", body: "Schemas, columns, keys, row counts, and query history.", items: ["PostgreSQL", "Snowflake", "BigQuery", "SQLite"], accent: "#3b82f6", }, { title: "BI tools", body: "Dashboards, questions, explores, usage, and trusted examples.", items: ["Metabase", "Looker"], accent: "#f97316", }, { title: "Modeling code", body: "Existing metrics, dimensions, models, joins, and entities.", items: ["dbt", "LookML", "MetricFlow"], accent: "#f59e0b", }, { title: "Docs and notes", body: "Policies, caveats, team definitions, and analyst context.", items: ["Notion", "Any text"], accent: "#10b981", }, ]; const stageData: Omit[] = [ { title: "Source connectors", body: "Read each configured system in its native shape.", }, { title: "Context builder", body: "Turn source evidence into proposed context updates.", }, { title: "Reconciliation", body: "Reconcile new evidence with the context that already exists.", }, { title: "Validation", body: "Check references and semantics before agents rely on them.", }, ]; const outputData: OutputNodeData[] = [ { title: "Wiki", path: "wiki/*.md", tags: ["free-form", "auto-maintained"], body: "Definitions, caveats, policies, analyst notes, and business language that agents can search.", accent: "#10b981", }, { title: "Semantic layer", path: "semantic-layer/*.yaml", tags: ["structured", "executable", "auto-maintained"], body: "Metrics, joins, tables, dimensions, filters, and segments that ktx can validate and compile into SQL.", accent: "#3b82f6", }, ]; const nodes: FlowNode[] = [ ...sourceData.map((source, index) => ({ id: `source-${index}`, type: "source", position: { x: SOURCES_START_X + index * (SOURCE_W + SOURCE_GAP_X), y: ROW_SOURCES_Y, }, data: source, draggable: false, selectable: false, })), ...stageData.map((stage, index) => ({ id: `stage-${index}`, type: "stage", position: { x: STAGE_X, y: ROW_STAGE_START_Y + index * (STAGE_H + STAGE_GAP), }, data: { ...stage, index: index + 1 }, draggable: false, selectable: false, })), ...outputData.map((output, index) => ({ id: `output-${index}`, type: "output", position: { x: OUTPUTS_START_X + index * (OUTPUT_W + OUTPUT_GAP_X), y: ROW_OUTPUTS_Y, }, data: output, draggable: false, selectable: false, })), ]; const REF_EDGE_STROKE = "#64748b"; const flowEdges = [ ...sourceData.map((_, index) => ({ id: `e-source-${index}-stage-0`, source: `source-${index}`, target: "stage-0", })), ...stageData.slice(0, -1).map((_, index) => ({ id: `e-stage-${index}-stage-${index + 1}`, source: `stage-${index}`, target: `stage-${index + 1}`, })), ...outputData.map((_, index) => ({ id: `e-stage-3-output-${index}`, source: "stage-3", target: `output-${index}`, })), ].map((edge) => ({ ...edge, type: "smoothstep" as const, style: { stroke: EDGE_STROKE, strokeWidth: 1.5 }, markerEnd: { type: MarkerType.ArrowClosed, color: EDGE_STROKE, width: 16, height: 16, }, })); const refsEdge = { id: "e-output-refs", source: "output-0", sourceHandle: "right", target: "output-1", targetHandle: "left", type: "straight" as const, label: "references", labelBgPadding: [6, 3] as [number, number], labelBgBorderRadius: 4, labelStyle: { fontSize: 15, fontWeight: 500, fill: "var(--color-fd-muted-foreground)", }, labelBgStyle: { fill: "var(--color-fd-background)", stroke: "var(--color-fd-border)", strokeWidth: 1, }, style: { stroke: REF_EDGE_STROKE, strokeWidth: 1.25, strokeDasharray: "4 4", }, markerStart: { type: MarkerType.ArrowClosed, color: REF_EDGE_STROKE, width: 14, height: 14, }, markerEnd: { type: MarkerType.ArrowClosed, color: REF_EDGE_STROKE, width: 14, height: 14, }, }; function SourceNodeView({ data }: NodeProps) { return (

{data.title}

{data.body}

{data.items.map((item) => ( {item} ))}
); } function StageNodeView({ data }: NodeProps) { return (
{data.index}

{data.title}

{data.body}

); } function OutputNodeView({ data }: NodeProps) { return (

{data.path}

{data.title}

{data.tags.map((tag) => ( {tag} ))}

{data.body}

); } const PARTICLES_PER_SOURCE = 2; const PARTICLE_SPEED_PX_PER_SEC = 130; const PARTICLE_MIN_DURATION_SEC = 4; const stageTopY = (i: number) => ROW_STAGE_START_Y + i * (STAGE_H + STAGE_GAP); const stageBottomY = (i: number) => stageTopY(i) + STAGE_H; function buildParticlePath( sourceIndex: number, outputIndex: number, ): { d: string; length: number } { const sourceCenterX = SOURCES_START_X + sourceIndex * (SOURCE_W + SOURCE_GAP_X) + SOURCE_W / 2; const sourceBottomYVal = ROW_SOURCES_Y + SOURCE_H; const outputCenterX = OUTPUTS_START_X + outputIndex * (OUTPUT_W + OUTPUT_GAP_X) + OUTPUT_W / 2; const legs: Array<[number, number, number, number]> = [ [sourceCenterX, sourceBottomYVal, STAGE_CENTER_X, stageTopY(0)], [STAGE_CENTER_X, stageBottomY(0), STAGE_CENTER_X, stageTopY(1)], [STAGE_CENTER_X, stageBottomY(1), STAGE_CENTER_X, stageTopY(2)], [STAGE_CENTER_X, stageBottomY(2), STAGE_CENTER_X, stageTopY(3)], [STAGE_CENTER_X, stageBottomY(3), outputCenterX, ROW_OUTPUTS_Y], ]; const segments = legs.map(([sx, sy, tx, ty]) => { const [segment] = getSmoothStepPath({ sourceX: sx, sourceY: sy, sourcePosition: Position.Bottom, targetX: tx, targetY: ty, targetPosition: Position.Top, }); return segment; }); let d = segments[0]; for (let i = 1; i < segments.length; i += 1) { d += ` ${segments[i].replace(/^M/, "L")}`; } const length = legs.reduce( (sum, [sx, sy, tx, ty]) => sum + Math.abs(tx - sx) + Math.abs(ty - sy), 0, ); return { d, length }; } type ParticleEdgeData = { d: string; duration: number; beginOffset: number; color: string; }; type ParticleEdge = Edge; function ParticleEdgeView({ id, data }: EdgeProps) { if (!data) return null; const pathId = `mechanics-particle-path-${id}`; return ( <> ); } const nodeTypes = { source: SourceNodeView, stage: StageNodeView, output: OutputNodeView, }; const edgeTypes = { particle: ParticleEdgeView, }; const staticEdges = [...flowEdges, refsEdge]; type ParticleSpec = { id: string; sourceIndex: number; outputIndex: number; }; function makeRandomParticles(perSource: number): ParticleSpec[] { const specs: ParticleSpec[] = []; for (let sourceIndex = 0; sourceIndex < sourceData.length; sourceIndex += 1) { for (let n = 0; n < perSource; n += 1) { specs.push({ id: `particle-${sourceIndex}-${n}`, sourceIndex, outputIndex: Math.floor(Math.random() * outputData.length), }); } } return specs; } function specToEdge(spec: ParticleSpec): { id: string; source: string; target: string; type: "particle"; data: ParticleEdgeData; } { const { d, length } = buildParticlePath(spec.sourceIndex, spec.outputIndex); const duration = Math.max( PARTICLE_MIN_DURATION_SEC, length / PARTICLE_SPEED_PX_PER_SEC, ); return { id: spec.id, source: `source-${spec.sourceIndex}`, target: `output-${spec.outputIndex}`, type: "particle", data: { d, duration, beginOffset: Math.random() * duration, color: sourceData[spec.sourceIndex].accent, }, }; } export function ProductMechanics() { const [particles, setParticles] = useState([]); useEffect(() => { setParticles(makeRandomParticles(PARTICLES_PER_SOURCE)); }, []); const edges = useMemo( () => [...staticEdges, ...particles.map(specToEdge)], [particles], ); return (

How ingestion works

ktx ingests source evidence, reconciles it with your existing project, and produces durable context that agents can search, review, and execute.

Ingestion flow

From scattered source systems to agent-ready context

The inputs can be structured systems or loose team knowledge. The outputs are the two files agents need: a readable wiki and an executable semantic layer.

); }