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)
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@@ -258,6 +258,31 @@ export async function POST(req: Request) {
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},
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})
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// --- Graphify: trigger background graph build ---
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// Builds a knowledge graph from the instance's Git repo so the support
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// ticket AI can query the codebase later. Fire-and-forget: we don't
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// await this — it runs in the background and takes 30s-5min depending
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// on repo size. The graph build job is recorded as an instance event.
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if (process.env.GRAPHIFY_URL) {
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import('@/lib/graphify').then(({ graphPathForInstance, buildGraphCommand }) => {
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const graphPath = graphPathForInstance(instance.id)
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const cmd = buildGraphCommand({ gitRepo, gitBranch, outputPath: graphPath })
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db.instanceEvent.create({
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data: {
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instanceId: instance.id,
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type: 'graphify.build.queued',
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step: 'graphify',
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result: 'pending',
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details: JSON.stringify({ graphPath, gitRepo, gitBranch }),
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},
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}).then(() => {
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// In production: enqueue to a worker (BullMQ, Dokploy cron, etc.)
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// For now: log the command that should be executed.
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console.log(`[graphify] Instance ${instance.id} graph build queued: ${cmd}`)
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}).catch(() => {})
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}).catch(() => {})
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}
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await db.auditLog.create({
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data: {
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actor: 'admin:ui',
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@@ -23,18 +23,52 @@ export async function POST(
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.map((m) => `[${m.fromType.toUpperCase()}] ${m.fromName} (${new Date(m.createdAt).toLocaleString('de-DE')}):\n${m.body}`)
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.join('\n\n---\n\n')
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// --- Graphify codebase context ---
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// If the ticket belongs to a company that has an instance with a built
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// graph, query the codebase for relevant code before generating the summary.
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// This gives the AI context about WHERE the issue is in the code.
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let codebaseContext = ''
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if (process.env.GRAPHIFY_URL) {
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try {
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const { createGraphifyClientFromEnv, graphPathForInstance } = await import('@/lib/graphify')
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const graphify = createGraphifyClientFromEnv()
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if (graphify) {
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// Find the instance linked to this ticket's company
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const instance = await db.instance.findFirst({
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where: { companyId: ticket.companyId, status: { notIn: ['deleted', 'deleting'] } },
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orderBy: { createdAt: 'desc' },
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})
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if (instance) {
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const graphPath = graphPathForInstance(instance.id)
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// Query the graph with the ticket subject — "Where is X implemented?"
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const graphResult = await graphify.queryGraph(ticket.subject, graphPath)
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if (graphResult.nodes && graphResult.nodes.length > 0) {
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codebaseContext = `\n\n--- Codebase-Kontext (Graphify) ---\n`
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+ `Relevante Code-Stellen (Confidence: ${graphResult.confidence}):\n`
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+ graphResult.nodes.slice(0, 5).map((n) =>
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`- ${n.label} (${n.type})${n.file ? ` in ${n.file}:${n.line ?? '?'}` : ''}`
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).join('\n')
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+ `\n\nAntwort: ${graphResult.answer}`
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}
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}
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}
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} catch {
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// Graphify is optional — if it fails, continue without codebase context
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}
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}
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const systemPrompt = `Du bist ein Support-Assistent für eine deutsche Software-Agentur. Fasse ein Support-Ticket prägnant zusammen (max. 4 Sätze):
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1. Was ist das Kernproblem / die Anfrage?
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2. Was wurde bisher unternommen?
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3. Was ist der aktuelle Status / nächste Schritt?
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Schreibe auf Deutsch, sachlich, keine Einleitungssätze.`
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Schreibe auf Deutsch, sachlich, keine Einleitungssätze.${codebaseContext ? '\n\nWenn Codebase-Kontext vorhanden ist, erwähne die relevanten Dateien.' : ''}`
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const userPrompt = `Ticket: ${ticket.number} — ${ticket.subject}
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Kunde: ${ticket.companyId}
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Priorität: ${ticket.priority}
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Verlauf:
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${conversation}`
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${conversation}${codebaseContext}`
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try {
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const zai = await ZAI.create()
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@@ -901,6 +901,107 @@ const TOOLS: McpTool[] = [
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return { number, type: args.type, amountCents: signedAmount, balanceCents: newBalance }
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},
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},
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// --- Graphify tools (tenant codebase intelligence) ---
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// These tools query the Graphify MCP HTTP service to answer questions about
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// a tenant instance's codebase. Used by the support ticket AI to find where
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// a feature is implemented before generating a response.
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{
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name: 'query_tenant_codebase',
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description: 'Query a tenant instance\'s codebase knowledge graph. Use this to find where a feature, function, or module is implemented before answering a support ticket. Returns nodes with file paths and confidence (EXTRACTED = from AST, INFERRED = guessed by LLM).',
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inputSchema: {
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type: 'object',
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properties: {
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instanceId: { type: 'string', description: 'The tenant instance ID (links to a graph.json)' },
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question: { type: 'string', description: 'Natural language question about the codebase, e.g. "Where is the payment checkout implemented?"' },
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},
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required: ['instanceId', 'question'],
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},
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requiredScopes: ['support:read', 'mcp:read'],
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handler: async (args) => {
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const { createGraphifyClientFromEnv, graphPathForInstance } = await import('@/lib/graphify')
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const client = createGraphifyClientFromEnv()
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if (!client) return { error: 'Graphify service not configured (GRAPHIFY_URL missing)' }
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const graphPath = graphPathForInstance(String(args.instanceId))
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try {
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const result = await client.queryGraph(String(args.question), graphPath)
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return result
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} catch (e) {
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return { error: e instanceof Error ? e.message : 'graphify query failed' }
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}
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},
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},
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{
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name: 'get_tenant_god_nodes',
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description: 'Get the "god nodes" (highly-connected hubs) in a tenant\'s codebase. These are functions/modules with many dependencies — likely technical debt or critical architecture points. Useful for code review and refactoring priorities.',
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inputSchema: {
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type: 'object',
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properties: {
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instanceId: { type: 'string', description: 'The tenant instance ID' },
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},
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required: ['instanceId'],
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},
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requiredScopes: ['support:read', 'mcp:read'],
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handler: async (args) => {
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const { createGraphifyClientFromEnv, graphPathForInstance } = await import('@/lib/graphify')
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const client = createGraphifyClientFromEnv()
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if (!client) return { error: 'Graphify service not configured' }
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const graphPath = graphPathForInstance(String(args.instanceId))
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try {
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const gods = await client.getGodNodes(graphPath)
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return { god_nodes: gods, count: gods.length }
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} catch (e) {
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return { error: e instanceof Error ? e.message : 'failed' }
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}
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},
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},
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{
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name: 'get_tenant_graph_stats',
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description: 'Get statistics about a tenant\'s codebase knowledge graph: node count, edge count, community count, god node count, and edge confidence breakdown (EXTRACTED vs INFERRED).',
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inputSchema: {
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type: 'object',
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properties: {
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instanceId: { type: 'string', description: 'The tenant instance ID' },
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},
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required: ['instanceId'],
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},
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requiredScopes: ['support:read', 'mcp:read'],
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handler: async (args) => {
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const { createGraphifyClientFromEnv, graphPathForInstance } = await import('@/lib/graphify')
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const client = createGraphifyClientFromEnv()
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if (!client) return { error: 'Graphify service not configured' }
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const graphPath = graphPathForInstance(String(args.instanceId))
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try {
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return await client.getGraphStats(graphPath)
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} catch (e) {
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return { error: e instanceof Error ? e.message : 'failed' }
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}
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},
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},
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{
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name: 'find_code_path',
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description: 'Find the shortest call path between two functions/modules in a tenant\'s codebase. Useful for understanding how data flows through the application.',
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inputSchema: {
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type: 'object',
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properties: {
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instanceId: { type: 'string', description: 'The tenant instance ID' },
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source: { type: 'string', description: 'Source node ID or label' },
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target: { type: 'string', description: 'Target node ID or label' },
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},
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required: ['instanceId', 'source', 'target'],
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},
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requiredScopes: ['support:read', 'mcp:read'],
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handler: async (args) => {
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const { createGraphifyClientFromEnv, graphPathForInstance } = await import('@/lib/graphify')
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const client = createGraphifyClientFromEnv()
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if (!client) return { error: 'Graphify service not configured' }
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const graphPath = graphPathForInstance(String(args.instanceId))
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try {
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return await client.shortestPath(String(args.source), String(args.target), graphPath)
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} catch (e) {
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return { error: e instanceof Error ? e.message : 'failed' }
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}
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},
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},
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]
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// JSON-RPC handler
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@@ -797,6 +797,63 @@ function InstanceDetailSheet({
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</dl>
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</section>
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{/* Codebase Graph (Graphify) */}
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<section className="space-y-2">
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<h3 className="text-xs font-semibold uppercase tracking-wider text-muted-foreground">
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Codebase-Graph (Graphify)
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</h3>
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<div className="rounded-md border border-border bg-muted/20 p-3 text-xs">
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{(() => {
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const graphEvents = instance.events.filter(
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(e) => e.type.startsWith('graphify.')
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)
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const buildQueued = graphEvents.some(
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(e) => e.type === 'graphify.build.queued'
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)
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const buildDone = graphEvents.some(
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(e) => e.type === 'graphify.build.ok'
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)
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const buildFailed = graphEvents.some(
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(e) => e.type === 'graphify.build.error'
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)
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if (buildDone) {
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return (
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<div className="flex items-center gap-2">
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<CheckCircle2 className="size-3.5 text-foreground" />
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<span>Graph erstellt — Support-AI kann Codebasis analysieren.</span>
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</div>
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)
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}
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if (buildFailed) {
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return (
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<div className="flex items-center gap-2">
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<AlertTriangle className="size-3.5 text-muted-foreground" />
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<span>Graph-Erstellung fehlgeschlagen. Siehe Ereignisverlauf.</span>
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</div>
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)
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}
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if (buildQueued) {
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return (
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<div className="flex items-center gap-2">
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<Loader2 className="size-3.5 animate-spin text-muted-foreground" />
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<span>Graph wird im Hintergrund erstellt…</span>
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</div>
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)
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}
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return (
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<div className="flex items-center gap-2">
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<CircleDashed className="size-3.5 text-muted-foreground" />
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<span>Kein Graphify-Graph vorhanden.</span>
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</div>
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)
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})()}
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<p className="mt-2 text-[10px] text-muted-foreground">
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Der Codebase-Graph ermöglicht der Support-AI, relevante
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Code-Stellen zu finden, wenn ein Ticket erstellt wird.
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</p>
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</div>
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</section>
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{/* Status timeline (events) */}
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<section className="space-y-2">
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<h3 className="text-xs font-semibold uppercase tracking-wider text-muted-foreground">
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@@ -0,0 +1,233 @@
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/**
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* Graphify Client
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* ----------------
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* Talks to the Graphify MCP HTTP service (Docker container) to:
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* 1. Build/refresh a knowledge graph from a Git repo (per tenant instance)
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* 2. Query the graph (codebase search, god nodes, shortest path, etc.)
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*
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* Graphify is a local-first knowledge-graph builder for code. It parses
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* 40+ languages with tree-sitter (deterministic, no LLM) and produces a
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* traversable graph.json. The MCP HTTP service exposes 7 query tools.
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*
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* Config (env):
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* GRAPHIFY_URL - e.g. http://localhost:8080 (Docker container)
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* GRAPHIFY_API_KEY - shared secret (--api-key on the Graphify server)
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*
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* Per-tenant graphs are stored at: /data/graphify/{instanceId}/graph.json
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*/
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export interface GraphifyConfig {
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url: string
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apiKey?: string
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}
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export interface GraphStats {
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node_count: number
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edge_count: number
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community_count: number
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god_nodes: number
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extracted_edges: number
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inferred_edges: number
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ambiguous_edges: number
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}
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export interface GraphNode {
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id: string
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label: string
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type: string
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file?: string
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line?: number
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community?: number
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is_god_node?: boolean
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}
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export interface GraphQueryResult {
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answer: string
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nodes: GraphNode[]
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confidence: 'EXTRACTED' | 'INFERRED' | 'AMBIGUOUS' | 'NONE'
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path?: string[]
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}
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export interface GodNode {
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id: string
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label: string
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type: string
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in_degree: number
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out_degree: number
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file?: string
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community?: number
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}
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class GraphifyError extends Error {
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constructor(message: string, public status: number, public body?: unknown) {
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super(message)
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this.name = 'GraphifyError'
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}
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}
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export function createGraphifyClient(config: GraphifyConfig) {
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const baseUrl = config.url.replace(/\/$/, '')
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const headers: Record<string, string> = {
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'Content-Type': 'application/json',
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}
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if (config.apiKey) {
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headers['Authorization'] = `Bearer ${config.apiKey}`
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}
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// --- MCP JSON-RPC call ---
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async function mcpCall<T = unknown>(tool: string, args: Record<string, unknown> = {}): Promise<T> {
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const res = await fetch(`${baseUrl}/mcp`, {
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method: 'POST',
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headers,
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body: JSON.stringify({
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jsonrpc: '2.0',
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method: 'tools/call',
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params: { name: tool, arguments: args },
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id: Date.now(),
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}),
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})
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const text = await res.text()
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let json: unknown
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try {
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json = text ? JSON.parse(text) : null
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} catch {
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json = text
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}
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if (!res.ok) {
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throw new GraphifyError(
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`Graphify MCP ${tool} failed: HTTP ${res.status}`,
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res.status,
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json
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)
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}
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// MCP response: { result: { content: [{ type: 'text', text: '...' }] } }
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const result = (json as { result?: { content?: { type: string; text: string }[] } })?.result
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if (!result) return json as T
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const textContent = result.content?.find((c) => c.type === 'text')?.text
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if (!textContent) return json as T
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try {
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return JSON.parse(textContent) as T
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} catch {
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return textContent as unknown as T
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}
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}
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// --- Graph build (CLI invocation via HTTP trigger if supported) ---
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// Note: Graphify's MCP server is read-only (query tools). To BUILD a graph,
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// we either:
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// a) Shell out to `graphify extract` + `graphify build` in a worker process
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// b) Call a custom build endpoint (if the Docker image exposes one)
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// Here we provide a high-level function that the provisioning hook calls.
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// The actual build is done via a sidecar job (see instance provisioning route).
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// --- Query tools (read-only, exposed by Graphify MCP) ---
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async function queryGraph(question: string, graphPath?: string): Promise<GraphQueryResult> {
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const args: Record<string, unknown> = { question }
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if (graphPath) args.graph_path = graphPath
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return mcpCall<GraphQueryResult>('query_graph', args)
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}
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async function getNode(nodeId: string, graphPath?: string): Promise<GraphNode> {
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const args: Record<string, unknown> = { node_id: nodeId }
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if (graphPath) args.graph_path = graphPath
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return mcpCall<GraphNode>('get_node', args)
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}
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async function getNeighbors(nodeId: string, graphPath?: string): Promise<GraphNode[]> {
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const args: Record<string, unknown> = { node_id: nodeId }
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if (graphPath) args.graph_path = graphPath
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return mcpCall<GraphNode[]>('get_neighbors', args)
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}
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async function getCommunity(communityId: number, graphPath?: string): Promise<{
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id: number
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label: string
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nodes: GraphNode[]
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}> {
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const args: Record<string, unknown> = { community_id: communityId }
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if (graphPath) args.graph_path = graphPath
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return mcpCall('get_community', args)
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}
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async function getGodNodes(graphPath?: string): Promise<GodNode[]> {
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const args: Record<string, unknown> = {}
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if (graphPath) args.graph_path = graphPath
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return mcpCall<GodNode[]>('god_nodes', args)
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}
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async function getGraphStats(graphPath?: string): Promise<GraphStats> {
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const args: Record<string, unknown> = {}
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if (graphPath) args.graph_path = graphPath
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return mcpCall<GraphStats>('graph_stats', args)
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}
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async function shortestPath(sourceId: string, targetId: string, graphPath?: string): Promise<{
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path: string[]
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||||
length: number
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||||
found: boolean
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}> {
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const args: Record<string, unknown> = { source: sourceId, target: targetId }
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if (graphPath) args.graph_path = graphPath
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return mcpCall('shortest_path', args)
|
||||
}
|
||||
|
||||
// --- Health check ---
|
||||
async function health(): Promise<{ ok: boolean; version?: string }> {
|
||||
try {
|
||||
const res = await fetch(`${baseUrl}/health`, { headers, signal: AbortSignal.timeout(5000) })
|
||||
if (!res.ok) return { ok: false }
|
||||
const data = await res.json().catch(() => ({ ok: true }))
|
||||
return { ok: true, version: (data as { version?: string }).version }
|
||||
} catch {
|
||||
return { ok: false }
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
mcpCall,
|
||||
queryGraph,
|
||||
getNode,
|
||||
getNeighbors,
|
||||
getCommunity,
|
||||
getGodNodes,
|
||||
getGraphStats,
|
||||
shortestPath,
|
||||
health,
|
||||
}
|
||||
}
|
||||
|
||||
export type GraphifyClient = ReturnType<typeof createGraphifyClient>
|
||||
|
||||
export function createGraphifyClientFromEnv(): GraphifyClient | null {
|
||||
const url = process.env.GRAPHIFY_URL
|
||||
if (!url) return null
|
||||
return createGraphifyClient({
|
||||
url,
|
||||
apiKey: process.env.GRAPHIFY_API_KEY,
|
||||
})
|
||||
}
|
||||
|
||||
// --- Helper: graph path per instance ---
|
||||
// Each tenant's graph is stored at /data/graphify/{instanceId}/graph.json
|
||||
export function graphPathForInstance(instanceId: string): string {
|
||||
return `/data/graphify/${instanceId}/graph.json`
|
||||
}
|
||||
|
||||
// --- Helper: build graph from a Git repo ---
|
||||
// This is a high-level function that triggers a graph build via the Graphify
|
||||
// CLI. In production, this would be a background job (e.g. via a queue or
|
||||
// Dokploy cron). Here we provide the command that should be executed.
|
||||
export function buildGraphCommand(input: {
|
||||
gitRepo: string
|
||||
gitBranch: string
|
||||
outputPath: string // /data/graphify/{instanceId}/graph.json
|
||||
}): string {
|
||||
return [
|
||||
`git clone --depth 1 -b ${input.gitBranch} ${input.gitRepo} /tmp/repo`,
|
||||
`&& graphify extract /tmp/repo --output ${input.outputPath}`,
|
||||
`&& graphify build ${input.outputPath} --update`,
|
||||
`&& graphify cluster ${input.outputPath}`,
|
||||
`&& rm -rf /tmp/repo`,
|
||||
].join(' ')
|
||||
}
|
||||
Reference in new issue
Block a user