import type { PodGraph, PodGraphNode, PodGraphEdge, PodGraphMetric, PodLearningLoop, PodGraphActivity, PodGraphNodeKind, PodGraphEdgeKind, PodGraphNodeStatus, } from '@podman/shared'; import { collections, getGitStates, getDb } from '../memory/db.js'; /** * Live materializer: build a pod's continual-learning graph from the real * collections the agent writes (pods, engineer_states, observations, collisions, * interventions, outcomes) — NOT the hardcoded demo. See docs/live-ui-spec.md §1. * * Pure-read and best-effort. Returns `null` when there is no real activity yet * (only bare roster), so `loadPodGraph` can fall back to the demo graph. */ const ACTIVE_WINDOW_MS = 90_000; const MAX_OBSERVATIONS = 250; /** Strip a `git status --short` XY code (and rename `old -> new`) to a clean path. */ export function parseGitStatusPath(line: string): string { let s = line.trim(); const arrow = s.indexOf(' -> '); if (arrow !== -1) s = s.slice(arrow + 4); else s = s.replace(/^[ACDMRTU?!]{1,2}\s+/, ''); return normalizeFile(s); } /** Normalize a file path so vision (`collisions.file`) and git paths match. */ export function normalizeFile(f: string): string { return f .trim() .replace(/^["']|["']$/g, '') .replace(/^[ACDMRTU?!]{1,2}\s+/, '') .replace(/^\.\//, ''); } const MAX_COLLISIONS = 8; /** Reject "file" values that aren't real source paths — vision/git noise such as * URLs, env vars, browser/app names, and scratch/test artifacts. */ const FILE_NOISE = /(:\/\/|^[#~]|\s|\.env\b|\btett\b|test-change|demo-scratch|podman-test|scratch|sslip)/i; export function isFilePath(f: string): boolean { if (!f || FILE_NOISE.test(f)) return false; return /\.[a-z0-9]{1,6}$/i.test(f); // must end in a real file extension } /** Engineer names that are test/verification artifacts, not real teammates. */ const ENGINEER_NOISE = /(^verify\b|^.$|testrepo|-?check\b|\d{4,})/i; const MAX_FILES = 9; /** Short, readable node label — last two path segments (full path goes in summary). */ function shortLabel(file: string): string { const parts = file.split('/').filter(Boolean); return parts.slice(-2).join('/') || file; } const STATUS_RANK: Record = { stable: 0, active: 1, learned: 2, risk: 3, }; interface Builder { nodes: Map; edges: Map; } function nodeKey(kind: PodGraphNodeKind, key: string): string { return `${kind}:${key}`; } function upsertNode( b: Builder, kind: PodGraphNodeKind, key: string, patch: Partial>, ): string { const id = nodeKey(kind, kind === 'engineer' ? key.toLowerCase() : key); const cur = b.nodes.get(id); if (!cur) { b.nodes.set(id, { id, kind, label: patch.label ?? key, summary: patch.summary ?? '', weight: patch.weight ?? 0.6, status: patch.status ?? 'stable', x: 0, y: 0, }); return id; } if (patch.label) cur.label = patch.label; if (patch.summary) cur.summary = patch.summary; if (patch.weight && patch.weight > cur.weight) cur.weight = patch.weight; if (patch.status && STATUS_RANK[patch.status] > STATUS_RANK[cur.status]) cur.status = patch.status; return id; } function upsertEdge( b: Builder, source: string, target: string, kind: PodGraphEdgeKind, label: string, strength: number, ): void { const id = `${kind}:${source}->${target}`; const cur = b.edges.get(id); if (!cur) b.edges.set(id, { id, source, target, kind, label, strength }); else if (strength > cur.strength) cur.strength = strength; } const COLUMN_X: Record = { engineer: 78, file: 300, feature: 360, collision: 470, intervention: 622, }; /** Deterministic column layout so the SVG renders stably across refreshes. */ function layout(nodes: PodGraphNode[]): void { const byKind = new Map(); for (const n of nodes) { const list = byKind.get(n.kind) ?? []; list.push(n); byKind.set(n.kind, list); } for (const [kind, list] of byKind) { list.sort((a, b) => a.id.localeCompare(b.id)); const n = list.length; list.forEach((node, i) => { node.x = COLUMN_X[kind]; node.y = Math.round(((i + 1) / (n + 1)) * 452) + 10; }); } } const SEVERITY_WEIGHT: Record = { info: 0.4, warn: 0.7, critical: 1 }; function buildLoop(input: { observations: number; gitStates: number; collisions: number; interventions: number; outcomes: number; acceptedReal: number; learnedEdges: number; }): PodLearningLoop { const stored = input.observations + input.gitStates + input.interventions + input.outcomes; return { activeStep: input.acceptedReal > 0 ? 'adapt' : input.outcomes > 0 ? 'outcome' : input.collisions > 0 ? 'predict' : input.observations + input.gitStates > 0 ? 'store' : 'observe', steps: [ { key: 'observe', label: 'Observe', value: String(input.observations + input.gitStates), detail: 'Recent vision observations plus local git-state reports.', status: input.observations + input.gitStates > 0 ? 'complete' : 'quiet', }, { key: 'store', label: 'Store', value: String(stored), detail: 'MongoDB records available to recall for this pod.', status: stored > 0 ? 'complete' : 'quiet', }, { key: 'predict', label: 'Predict', value: String(input.collisions), detail: 'Distinct collision signatures detected from live work.', status: input.collisions > 0 ? 'complete' : 'quiet', }, { key: 'outcome', label: 'Outcome', value: String(input.outcomes), detail: 'Accepted and dismissed intervention outcomes.', status: input.outcomes > 0 ? 'complete' : 'quiet', }, { key: 'adapt', label: 'Adapt', value: String(input.learnedEdges), detail: 'Learned graph edges created from accepted real outcomes.', status: input.acceptedReal > 0 ? 'complete' : 'planned', }, ], }; } function pushActivity( activity: PodGraphActivity[], item: PodGraphActivity, seen: Set, ): void { if (seen.has(item.id)) return; seen.add(item.id); activity.push(item); } export async function materializePodGraph(podId: string): Promise { const c = await collections(); const db = await getDb(); const [pod, observations, collisionDocs, interventionDocs, outcomeDocs, gitStates] = await Promise.all([ c.pods.findOne({ id: podId }), c.observations.find({ podId }).sort({ observedAt: -1 }).limit(MAX_OBSERVATIONS).toArray(), c.collisions.find({ podId }).sort({ detectedAt: -1 }).limit(100).toArray(), c.interventions.find({ podId }).toArray(), c.outcomes.find({ podId }).toArray(), getGitStates(podId), ]); // Optional supervised ownership map (team_model.ownership: file -> engineer). let ownership: Record = {}; try { const tm = await db .collection<{ podId: string; ownership?: Record }>('team_model') .findOne({ podId }); ownership = tm?.ownership ?? {}; } catch { /* ownership is optional */ } const b: Builder = { nodes: new Map(), edges: new Map() }; const activity: PodGraphActivity[] = []; const activityIds = new Set(); const now = Date.now(); // 1. Baseline engineer nodes from the roster. for (const name of pod?.members ?? []) { upsertNode(b, 'engineer', name, { label: name }); } // 2. Vision (observations): who is active and on which file, with confidence. for (const o of observations) { if (!o.engineerId) continue; const recent = o.observedAt && now - new Date(o.observedAt).getTime() < ACTIVE_WINDOW_MS; const eng = upsertNode(b, 'engineer', o.engineerId, { label: o.engineerId, status: recent ? 'active' : undefined, }); const file = o.currentFile ? normalizeFile(o.currentFile) : ''; if (isFilePath(file)) { const f = upsertNode(b, 'file', file, { label: shortLabel(file), summary: file }); upsertEdge(b, eng, f, 'editing', o.activity ?? 'edits', Math.max(0.4, o.confidence ?? 0.5)); pushActivity( activity, { id: `editing:${o.engineerId}:${file}:${String(o.observedAt ?? '')}`, at: String(o.observedAt ?? new Date().toISOString()), kind: 'editing', title: `${o.engineerId} editing ${shortLabel(file)}`, detail: o.activity ?? 'Vision observed active work.', nodeId: f, }, activityIds, ); } } // Collisions referenced by accepted outcomes are the "learned" money path — they // always survive the cap so the learned_from beat is never dropped. const priorityCol = new Set(); for (const out of outcomeDocs) { if (!out.accepted || !out.wasRealCollision) continue; if (out.collisionId) priorityCol.add(out.collisionId); const iv = interventionDocs.find((i) => i.id === out.interventionId); if (iv?.collisionId) priorityCol.add(iv.collisionId); } // 3. Collisions: collapse repeats by signature, keep the most recent, cap to // MAX_COLLISIONS, skip junk-file collisions. `collisionById` keeps every doc // (for the outcome join); `colNodeFor` maps each collisionId to its surviving // collision node (or null when collapsed / capped / filtered out). const collisionById = new Map(); const colNodeFor = new Map(); const sigToNode = new Map(); let distinctCollisions = 0; for (const col of collisionDocs) { collisionById.set(col.id, col); const file = normalizeFile(col.file); const sig = (col as { memorySignature?: string }).memorySignature ?? `${file}#${col.symbol ?? ''}`; const existing = sigToNode.get(sig); if (existing) { colNodeFor.set(col.id, existing); continue; } if (!isFilePath(file)) { colNodeFor.set(col.id, null); continue; } const isPriority = priorityCol.has(col.id); if (!isPriority && distinctCollisions >= MAX_COLLISIONS) { colNodeFor.set(col.id, null); continue; } const cNode = upsertNode(b, 'collision', col.id, { label: shortLabel(file), status: 'risk', weight: SEVERITY_WEIGHT[col.severity] ?? 0.7, summary: `${col.engineers.join(' + ')} on ${file}${ (col as { memorySignature?: string }).memorySignature ? ' · seen before' : '' }`, }); const fNode = upsertNode(b, 'file', file, { label: shortLabel(file), summary: file, status: 'risk', }); upsertEdge(b, fNode, cNode, 'touches', 'hot', 0.6); for (const name of col.engineers) { const eng = upsertNode(b, 'engineer', name, { label: name }); upsertEdge(b, eng, cNode, 'collides', 'in', SEVERITY_WEIGHT[col.severity] ?? 0.7); } pushActivity( activity, { id: `collision:${col.id}`, at: col.detectedAt, kind: 'collision', title: `Collision risk on ${shortLabel(file)}`, detail: `${col.engineers.join(' + ')} converged on ${file}.`, nodeId: cNode, }, activityIds, ); sigToNode.set(sig, cNode); colNodeFor.set(col.id, cNode); if (!isPriority) distinctCollisions++; } // 4. Git truth (engineer_states): mark unpushed work and confirm editing on // files vision/collisions already surfaced — not the whole repo diff. for (const [name, git] of gitStates) { const files = git.changedFiles.map(parseGitStatusPath).filter(Boolean); const eng = upsertNode(b, 'engineer', name, { label: name, status: files.length > 0 ? 'risk' : 'active', summary: files.length ? `${files.length} changed file(s) on ${git.branch ?? 'detached'}` : `on ${git.branch ?? 'detached'}`, weight: 0.7, }); for (const file of files) { const fid = nodeKey('file', file); if (b.nodes.has(fid)) upsertEdge(b, eng, fid, 'editing', 'edits', 0.6); } } // 5. Interventions: collapse to one (most recent) per surviving collision. const interventionById = new Map(); const ivNodeForCol = new Map(); const sortedIvs = [...interventionDocs].sort((a, b) => String(b.createdAt ?? '').localeCompare(String(a.createdAt ?? '')), ); for (const iv of sortedIvs) { interventionById.set(iv.id, iv); const colNode = colNodeFor.get(iv.collisionId); if (!colNode || ivNodeForCol.has(colNode)) continue; const ivNode = upsertNode(b, 'intervention', iv.id, { label: iv.suggestedAction?.kind === 'open_sync_pr' ? 'sync PR' : iv.suggestedAction?.kind === 'ping_teammate' ? 'ping' : 'watch', summary: iv.message, }); upsertEdge(b, colNode, ivNode, 'warns', 'routes', 0.85); pushActivity( activity, { id: `intervention:${iv.id}`, at: iv.createdAt, kind: 'intervention', title: `Intervention: ${b.nodes.get(ivNode)?.label ?? iv.kind}`, detail: iv.message, nodeId: ivNode, }, activityIds, ); ivNodeForCol.set(colNode, ivNode); } // 6. Outcomes: the supervised learning signal -> learned_from edges + owns. for (const out of outcomeDocs) { if (!out.accepted || !out.wasRealCollision) continue; const iv = interventionById.get(out.interventionId); const col = iv ? collisionById.get(iv.collisionId) : collisionById.get(out.collisionId); if (!col) continue; const file = normalizeFile(col.file); if (!isFilePath(file)) continue; const owner = (out as { learnedOwner?: string }).learnedOwner ?? ownership[file] ?? col.engineers[0]; if (!owner) continue; const engNode = upsertNode(b, 'engineer', owner, { label: owner, status: 'learned' }); const fNode = upsertNode(b, 'file', file, { label: file }); upsertEdge(b, engNode, fNode, 'owns', 'owns', 0.85); const cNode = colNodeFor.get(col.id); const ivNode = cNode ? ivNodeForCol.get(cNode) : undefined; if (ivNode) { const ivObj = b.nodes.get(ivNode); if (ivObj) ivObj.status = 'learned'; const before = b.edges.size; upsertEdge(b, ivNode, engNode, 'learned_from', `learned: owns ${file}`, 0.6); const edgeId = `${'learned_from'}:${ivNode}->${engNode}`; pushActivity( activity, { id: `learned:${out.interventionId}:${owner}:${file}`, at: out.recordedAt, kind: 'learned', title: `Learned ${owner} owns ${shortLabel(file)}`, detail: 'Accepted real outcome created a durable learned_from path.', nodeId: engNode, edgeId: before === b.edges.size ? undefined : edgeId, }, activityIds, ); } pushActivity( activity, { id: `outcome:${out.interventionId}:${out.recordedAt}`, at: out.recordedAt, kind: 'outcome', title: out.accepted ? 'Outcome accepted' : 'Outcome dismissed', detail: out.wasRealCollision ? 'Marked as a real collision.' : 'Marked as noise.', }, activityIds, ); } // 7. Suppressed repeats: PodMan stayed quiet on a recurring collision because // the signature was dismissed before — the negative-feedback loop made visible // (Feature A). Stamped at repeat time, so it sorts as recent activity. const suppressionDocs = await c.suppressions .find({ podId }) .sort({ suppressedAt: -1 }) .limit(50) .toArray(); // Collapse to one beat per file (keep the most recent — docs are sorted desc) // so pre-fix duplicate rows never render as spam. The stable per-file id also // dedupes through pushActivity's `seen` set. const seenSuppressedFiles = new Set(); for (const s of suppressionDocs) { const sFile = normalizeFile(s.file); if (!isFilePath(sFile)) continue; const fileKey = sFile.toLowerCase(); if (seenSuppressedFiles.has(fileKey)) continue; seenSuppressedFiles.add(fileKey); const sEngs = (s.engineers ?? []).join(' + ') || 'teammates'; pushActivity( activity, { id: `suppressed:${fileKey}`, at: s.suppressedAt, kind: 'suppressed', title: `Suppressed — ${shortLabel(sFile)} repeat silenced`, detail: `${sEngs} on ${sFile} recurred, but it was dismissed before — PodMan stayed quiet.`, }, activityIds, ); } // Prune test-artifact engineers, then anything left orphaned by that. const dropNode = (id: string) => { b.nodes.delete(id); for (const [eid, e] of [...b.edges]) if (e.source === id || e.target === id) b.edges.delete(eid); }; for (const [id, n] of [...b.nodes]) { if (n.kind === 'engineer' && ENGINEER_NOISE.test(n.label)) dropNode(id); } // Collisions with no remaining engineer = test/orphan -> drop. for (const [id, n] of [...b.nodes]) { if (n.kind !== 'collision') continue; if (![...b.edges.values()].some((e) => e.kind === 'collides' && e.target === id)) dropNode(id); } // Cap file nodes to the most-connected (collision files first). const fileNodes = [...b.nodes.values()].filter((n) => n.kind === 'file'); if (fileNodes.length > MAX_FILES) { const inCollision = (id: string) => [...b.edges.values()].some((e) => e.kind === 'touches' && e.source === id); const degree = (id: string) => [...b.edges.values()].filter((e) => e.source === id || e.target === id).length; fileNodes.sort( (a, z) => Number(inCollision(z.id)) - Number(inCollision(a.id)) || degree(z.id) - degree(a.id), ); for (const n of fileNodes.slice(MAX_FILES)) dropNode(n.id); } // Files / interventions left with no edges -> drop. for (const [id, n] of [...b.nodes]) { if (n.kind === 'file' || n.kind === 'intervention') { if (![...b.edges.values()].some((e) => e.source === id || e.target === id)) b.nodes.delete(id); } } const nodes = [...b.nodes.values()]; // No real activity beyond the bare roster -> let the caller fall back to demo. // Suppression beats are real negative-feedback proof even when they add no // nodes/edges, so they satisfy the gate too — a clean pod with preserved // suppressions must not fall back to the demo graph and hide the proof. const hasSuppressed = activity.some((a) => a.kind === 'suppressed'); const hasActivity = hasSuppressed || nodes.some((n) => n.kind !== 'engineer'); if (!hasActivity) return null; layout(nodes); const acceptedReal = outcomeDocs.filter((o) => o.accepted && o.wasRealCollision).length; const totalOutcomes = outcomeDocs.length; // Raw distinct collision signatures — kept for the learning-loop throughput view. const riskPaths = new Set( collisionDocs.map( (col) => (col as { memorySignature?: string }).memorySignature ?? `${normalizeFile(col.file)}#${col.symbol ?? ''}`, ), ).size; // Headline metric cards are derived from the FINAL de-noised graph so they match // what's drawn. Counting raw collision signatures / accepted-outcome rows inflates // them with test churn (e.g. 50 "risk paths" for 4 files), which reads as fake. const finalEdges = [...b.edges.values()]; const riskFiles = new Set(); for (const e of finalEdges) { if (e.kind === 'touches' && b.nodes.get(e.source)?.kind === 'file') riskFiles.add(e.source); } const openRiskPaths = riskFiles.size || nodes.filter((n) => n.kind === 'collision').length; const ownerSet = new Set(); for (const e of finalEdges) { if (e.kind === 'learned_from') ownerSet.add(e.target); if (e.kind === 'owns') ownerSet.add(e.source); } const learnedOwners = [...ownerSet].filter((id) => b.nodes.get(id)?.kind === 'engineer').length; const metrics: PodGraphMetric[] = [ { label: 'Learned owners', value: String(learnedOwners), detail: 'Distinct owners retained from accepted interventions.', }, { label: 'Open risk paths', value: String(openRiskPaths), detail: `${openRiskPaths === 1 ? 'File' : 'Files'} with two or more converging editors.`, }, { label: 'Accept rate', value: totalOutcomes ? `${Math.round((acceptedReal / totalOutcomes) * 100)}%` : '—', detail: 'Interventions accepted vs total this session.', }, ]; const learnedEdges = [...b.edges.values()].filter((e) => e.kind === 'learned_from').length; activity.sort((a, z) => String(z.at).localeCompare(String(a.at))); return { podId, generatedAt: new Date().toISOString(), nodes, edges: [...b.edges.values()], metrics, loop: buildLoop({ observations: observations.length, gitStates: gitStates.size, collisions: riskPaths, interventions: interventionDocs.length, outcomes: totalOutcomes, acceptedReal, learnedEdges, }), activity: activity.slice(0, 12), }; }