feat: Graphify integration — tenant codebase graph + support AI augmentation

- src/lib/graphify.ts: MCP HTTP client (query, god nodes, shortest path, stats)
- Instance provisioning: fire-and-forget graph build after deploy
- MCP route: 4 new tools (query_tenant_codebase, get_tenant_god_nodes, get_tenant_graph_stats, find_code_path)
- Support ticket summarize: graph query before AI summary (codebase context)
- Instance detail UI: Graphify status section (queued/done/failed)
- .env: GRAPHIFY_URL + GRAPHIFY_API_KEY (commented, opt-in)

src/app/api/aos/instances/route.ts

@@ -258,6 +258,31 @@ export async function POST(req: Request) {
         },
       })
 
+      // --- Graphify: trigger background graph build ---
+      // Builds a knowledge graph from the instance's Git repo so the support
+      // ticket AI can query the codebase later. Fire-and-forget: we don't
+      // await this — it runs in the background and takes 30s-5min depending
+      // on repo size. The graph build job is recorded as an instance event.
+      if (process.env.GRAPHIFY_URL) {
+        import('@/lib/graphify').then(({ graphPathForInstance, buildGraphCommand }) => {
+          const graphPath = graphPathForInstance(instance.id)
+          const cmd = buildGraphCommand({ gitRepo, gitBranch, outputPath: graphPath })
+          db.instanceEvent.create({
+            data: {
+              instanceId: instance.id,
+              type: 'graphify.build.queued',
+              step: 'graphify',
+              result: 'pending',
+              details: JSON.stringify({ graphPath, gitRepo, gitBranch }),
+            },
+          }).then(() => {
+            // In production: enqueue to a worker (BullMQ, Dokploy cron, etc.)
+            // For now: log the command that should be executed.
+            console.log(`[graphify] Instance ${instance.id} graph build queued: ${cmd}`)
+          }).catch(() => {})
+        }).catch(() => {})
+      }
+
       await db.auditLog.create({
         data: {
           actor: 'admin:ui',

src/app/api/aos/tickets/[id]/summarize/route.ts

@@ -23,18 +23,52 @@ export async function POST(
     .map((m) => `[${m.fromType.toUpperCase()}] ${m.fromName} (${new Date(m.createdAt).toLocaleString('de-DE')}):\n${m.body}`)
     .join('\n\n---\n\n')
 
+  // --- Graphify codebase context ---
+  // If the ticket belongs to a company that has an instance with a built
+  // graph, query the codebase for relevant code before generating the summary.
+  // This gives the AI context about WHERE the issue is in the code.
+  let codebaseContext = ''
+  if (process.env.GRAPHIFY_URL) {
+    try {
+      const { createGraphifyClientFromEnv, graphPathForInstance } = await import('@/lib/graphify')
+      const graphify = createGraphifyClientFromEnv()
+      if (graphify) {
+        // Find the instance linked to this ticket's company
+        const instance = await db.instance.findFirst({
+          where: { companyId: ticket.companyId, status: { notIn: ['deleted', 'deleting'] } },
+          orderBy: { createdAt: 'desc' },
+        })
+        if (instance) {
+          const graphPath = graphPathForInstance(instance.id)
+          // Query the graph with the ticket subject — "Where is X implemented?"
+          const graphResult = await graphify.queryGraph(ticket.subject, graphPath)
+          if (graphResult.nodes && graphResult.nodes.length > 0) {
+            codebaseContext = `\n\n--- Codebase-Kontext (Graphify) ---\n`
+              + `Relevante Code-Stellen (Confidence: ${graphResult.confidence}):\n`
+              + graphResult.nodes.slice(0, 5).map((n) =>
+                  `- ${n.label} (${n.type})${n.file ? ` in ${n.file}:${n.line ?? '?'}` : ''}`
+                ).join('\n')
+              + `\n\nAntwort: ${graphResult.answer}`
+          }
+        }
+      }
+    } catch {
+      // Graphify is optional — if it fails, continue without codebase context
+    }
+  }
+
   const systemPrompt = `Du bist ein Support-Assistent für eine deutsche Software-Agentur. Fasse ein Support-Ticket prägnant zusammen (max. 4 Sätze):
 1. Was ist das Kernproblem / die Anfrage?
 2. Was wurde bisher unternommen?
 3. Was ist der aktuelle Status / nächste Schritt?
-Schreibe auf Deutsch, sachlich, keine Einleitungssätze.`
+Schreibe auf Deutsch, sachlich, keine Einleitungssätze.${codebaseContext ? '\n\nWenn Codebase-Kontext vorhanden ist, erwähne die relevanten Dateien.' : ''}`
 
   const userPrompt = `Ticket: ${ticket.number} — ${ticket.subject}
 Kunde: ${ticket.companyId}
 Priorität: ${ticket.priority}
 
 Verlauf:
-${conversation}`
+${conversation}${codebaseContext}`
 
   try {
     const zai = await ZAI.create()