feat: persistent AI memory — chat history + knowledge store
agent-chat/route.ts: - Loads conversation history from chat_conversations before each turn - Passes history + knowledge context to agent runner - Saves returned history back to chat_conversations after each turn - Saves AI-generated memory updates to fs_knowledge_items knowledge/route.ts (new): - GET /api/projects/[id]/knowledge — list all knowledge items - POST /api/projects/[id]/knowledge — add/update item by key - DELETE /api/projects/[id]/knowledge?id=xxx — remove item OrchestratorChat.tsx: - Added "Saved to memory" label for save_memory tool calls Made-with: Cursor
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@@ -5,6 +5,84 @@ import { query } from "@/lib/db-postgres";
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const AGENT_RUNNER_URL = process.env.AGENT_RUNNER_URL ?? "http://localhost:3333";
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// ---------------------------------------------------------------------------
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// Helpers — chat_conversations + fs_knowledge_items
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// ---------------------------------------------------------------------------
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async function loadConversation(projectId: string): Promise<any[]> {
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try {
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const rows = await query<{ messages: any[] }>(
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`SELECT messages FROM chat_conversations WHERE project_id = $1`,
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[projectId]
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);
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return rows[0]?.messages ?? [];
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} catch {
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return [];
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}
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}
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async function saveConversation(projectId: string, messages: any[]): Promise<void> {
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try {
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await query(
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`INSERT INTO chat_conversations (project_id, messages, updated_at)
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VALUES ($1, $2::jsonb, NOW())
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ON CONFLICT (project_id) DO UPDATE
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SET messages = $2::jsonb, updated_at = NOW()`,
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[projectId, JSON.stringify(messages)]
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);
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} catch (e) {
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console.error("[agent-chat] Failed to save conversation:", e);
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}
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}
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async function loadKnowledge(projectId: string): Promise<string> {
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try {
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const rows = await query<{ data: any }>(
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`SELECT data FROM fs_knowledge_items WHERE project_id = $1 ORDER BY updated_at DESC LIMIT 50`,
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[projectId]
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);
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if (rows.length === 0) return "";
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return rows
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.map((r) => `[${r.data.type ?? "note"}] ${r.data.key}: ${r.data.value}`)
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.join("\n");
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} catch {
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return "";
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}
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}
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async function saveMemoryUpdates(
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projectId: string,
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updates: Array<{ key: string; type: string; value: string }>
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): Promise<void> {
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if (!updates?.length) return;
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try {
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for (const u of updates) {
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// Upsert by project_id + key
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const existing = await query<{ id: string }>(
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`SELECT id FROM fs_knowledge_items WHERE project_id = $1 AND data->>'key' = $2 LIMIT 1`,
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[projectId, u.key]
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);
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if (existing.length > 0) {
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await query(
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`UPDATE fs_knowledge_items SET data = $1::jsonb, updated_at = NOW() WHERE id = $2`,
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[JSON.stringify({ key: u.key, type: u.type, value: u.value, source: "ai" }), existing[0].id]
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);
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} else {
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await query(
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`INSERT INTO fs_knowledge_items (project_id, data) VALUES ($1, $2::jsonb)`,
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[projectId, JSON.stringify({ key: u.key, type: u.type, value: u.value, source: "ai" })]
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);
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}
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}
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} catch (e) {
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console.error("[agent-chat] Failed to save memory updates:", e);
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}
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}
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// ---------------------------------------------------------------------------
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// POST — send a message
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// ---------------------------------------------------------------------------
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export async function POST(
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req: NextRequest,
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{ params }: { params: Promise<{ projectId: string }> }
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@@ -21,7 +99,7 @@ export async function POST(
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return NextResponse.json({ error: '"message" is required' }, { status: 400 });
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}
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// Load project context to inject into the orchestrator session
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// Load project context
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let projectContext = "";
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try {
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const rows = await query<{ data: any }>(
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@@ -40,24 +118,34 @@ export async function POST(
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].filter(Boolean);
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projectContext = lines.join("\n");
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}
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} catch {
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// Non-fatal — orchestrator still works without extra context
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}
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} catch { /* non-fatal */ }
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// Use projectId as the session ID so each project has its own conversation
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const sessionId = `project_${projectId}`;
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// First message in a new session? Prepend project context
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const enrichedMessage = projectContext
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? `[Project context]\n${projectContext}\n\n[User message]\n${message}`
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: message;
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// Load persistent conversation history and knowledge from DB
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const [history, knowledgeContext] = await Promise.all([
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loadConversation(projectId),
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loadKnowledge(projectId),
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]);
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// Enrich user message with project context on the very first message
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const isFirstMessage = history.length === 0;
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const enrichedMessage =
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isFirstMessage && projectContext
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? `[Project context]\n${projectContext}\n\n[User message]\n${message}`
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: message;
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try {
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const res = await fetch(`${AGENT_RUNNER_URL}/orchestrator/chat`, {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({ message: enrichedMessage, session_id: sessionId }),
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signal: AbortSignal.timeout(120_000), // 2 min — agents can take time
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body: JSON.stringify({
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message: enrichedMessage,
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session_id: sessionId,
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history,
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knowledge_context: knowledgeContext || undefined,
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}),
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signal: AbortSignal.timeout(120_000),
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});
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if (!res.ok) {
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@@ -69,6 +157,13 @@ export async function POST(
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}
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const data = await res.json();
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// Persist conversation and any memory updates the AI generated
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await Promise.all([
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saveConversation(projectId, data.history ?? []),
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saveMemoryUpdates(projectId, data.memoryUpdates ?? []),
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]);
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return NextResponse.json({
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reply: data.reply,
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reasoning: data.reasoning ?? null,
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@@ -76,6 +171,7 @@ export async function POST(
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turns: data.turns ?? 0,
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model: data.model || null,
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sessionId,
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memoryUpdates: data.memoryUpdates ?? [],
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});
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} catch (err) {
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const msg = err instanceof Error ? err.message : String(err);
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@@ -86,7 +182,10 @@ export async function POST(
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}
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}
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// Clear session for this project
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// ---------------------------------------------------------------------------
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// DELETE — clear session + conversation history
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// ---------------------------------------------------------------------------
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export async function DELETE(
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_req: NextRequest,
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{ params }: { params: Promise<{ projectId: string }> }
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@@ -99,13 +198,12 @@ export async function DELETE(
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const { projectId } = await params;
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const sessionId = `project_${projectId}`;
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try {
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await fetch(`${AGENT_RUNNER_URL}/orchestrator/sessions/${sessionId}`, {
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method: "DELETE",
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});
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} catch {
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// Best-effort
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}
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await Promise.all([
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// Clear in-memory session from agent runner
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fetch(`${AGENT_RUNNER_URL}/orchestrator/sessions/${sessionId}`, { method: "DELETE" }).catch(() => {}),
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// Clear persisted conversation from DB
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query(`DELETE FROM chat_conversations WHERE project_id = $1`, [projectId]).catch(() => {}),
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]);
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return NextResponse.json({ cleared: true });
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}
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