mirror of
https://github.com/myronblair/jarvis
synced 2026-06-30 17:50:23 -05:00
Phase 10: Memory Core — auto-extraction knowledge graph
- reactor.py v9.0.0+: memory_extract + memory_store handlers (21 handlers) - handle_memory_extract: Haiku-powered fact extraction from conversations - handle_memory_store: explicit memory insertion from voice commands - FastAPI: /memory/facts CRUD, /memory/context (relevance retrieval), /memory/stats - chat.php: Tier 0.9k voice commands (remember/forget/recall/memory status) - Memory context injected into Groq + Claude system prompts - Auto-trigger memory_extract after every LLM response (async, non-blocking) - memory.php: new API endpoint proxying Arc Reactor memory routes - api.php: added memory route - admin/index.php: MEMORY CORE nav + tab (browse by category, search, add/delete facts) - index.html: MEMORY count in bottom bar (polls every 60s)
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+127
-2
@@ -1081,6 +1081,52 @@ if (!$reply && preg_match('/\b(news|headlines|latest|what.?s happening|current e
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// ── Tier 0.9: Arc Protocols — research, triage, remote_exec, screenshot, sysinfo ─
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$arcJobId = null;
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// ── Memory Core helpers ───────────────────────────────────────────────────────
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function getMemoryContext(string $message, int $limit = 12): string {
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try {
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$ch = curl_init('http://127.0.0.1:7474/memory/context?limit=' . $limit .
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'&message=' . urlencode(substr($message, 0, 200)));
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curl_setopt_array($ch, [
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CURLOPT_RETURNTRANSFER => true,
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CURLOPT_TIMEOUT => 2,
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CURLOPT_CONNECTTIMEOUT => 1,
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]);
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$raw = curl_exec($ch);
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curl_close($ch);
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if (!$raw) return '';
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$data = json_decode($raw, true);
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return $data['context'] ?? '';
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} catch (Throwable $e) {
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return '';
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}
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}
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function memoryExtractAsync(string $userMsg, string $assistantMsg, string $sessionId): void {
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// Fire-and-forget background memory extraction — does not block the response
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$body = json_encode([
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'type' => 'memory_extract',
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'payload' => [
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'user_message' => substr($userMsg, 0, 600),
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'assistant_message' => substr($assistantMsg, 0, 600),
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'conversation_id' => null,
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],
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'priority' => 2,
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'created_by' => 'chat:' . $sessionId,
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]);
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$ch = curl_init('http://127.0.0.1:7474/job');
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curl_setopt_array($ch, [
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CURLOPT_RETURNTRANSFER => true,
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CURLOPT_POST => true,
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CURLOPT_POSTFIELDS => $body,
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CURLOPT_HTTPHEADER => ['Content-Type: application/json'],
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CURLOPT_TIMEOUT => 1,
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CURLOPT_CONNECTTIMEOUT => 1,
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]);
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@curl_exec($ch);
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curl_close($ch);
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}
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// Helper: submit job to Arc Reactor
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function arcPost(string $path, array $body): ?array {
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$ch = curl_init('http://127.0.0.1:7474' . $path);
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@@ -1481,6 +1527,71 @@ if (!$reply) {
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}
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}
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// ── Tier 0.9k: Memory Core — remember/forget/recall voice commands ───────────
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if (!$reply) {
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// "remember that I prefer X", "remember X", "note that X"
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if (preg_match('/^(?:jarvis[,\s]+)?(?:remember|note down|make a note|remember that|note that)\s+(?:that\s+)?(.+)/i', $message, $m)) {
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$fact = trim($m[1]);
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// Use LLM to parse the fact into subject/predicate/object — but for speed, use heuristic
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$arcRes = arcPost('/job', [
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'type' => 'memory_store',
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'payload' => ['subject' => 'user', 'predicate' => 'note', 'object' => $fact, 'category' => 'instruction'],
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'priority' => 8,
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'created_by' => 'chat:' . $sessionId,
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]);
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$reply = "Noted, {$userAddr}. I'll remember that: {$fact}";
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$source = 'memory:store';
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}
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}
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if (!$reply) {
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// "forget X", "forget that X", "remove memory X"
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if (preg_match('/^(?:jarvis[,\s]+)?(?:forget|discard|remove|delete)\s+(?:that\s+|the\s+memory\s+(?:about\s+)?)?(.+)/i', $message, $m)) {
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$keyword = trim($m[1]);
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// Mark matching facts inactive
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$affected = JarvisDB::execute(
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"UPDATE memory_facts SET active=0 WHERE active=1 AND (subject LIKE ? OR object LIKE ? OR predicate LIKE ?)",
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["%{$keyword}%", "%{$keyword}%", "%{$keyword}%"]
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);
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$reply = $affected
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? "Memory cleared, {$userAddr}. Removed facts related to: {$keyword}."
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: "Nothing in memory matched \"{$keyword}\", {$userAddr}.";
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$source = 'memory:forget';
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}
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}
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if (!$reply) {
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// "what do you know about X", "what do you remember about X"
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if (preg_match('/^(?:jarvis[,\s]+)?(?:what do you know about|what do you remember about|recall|memory about)\s+(.+)/i', $message, $m)) {
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$keyword = trim($m[1]);
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$facts = JarvisDB::query(
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"SELECT * FROM memory_facts WHERE active=1 AND (subject LIKE ? OR object LIKE ?) ORDER BY confirmed_count DESC LIMIT 8",
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["%{$keyword}%", "%{$keyword}%"]
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) ?: [];
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if (empty($facts)) {
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$reply = "I don't have any stored memories about \"{$keyword}\", {$userAddr}.";
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} else {
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$lines = array_map(fn($f) => "{$f['subject']} {$f['predicate']}: {$f['object']}", $facts);
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$reply = "◈ I know the following about \"{$keyword}\", {$userAddr}:\n" . implode("\n", $lines);
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}
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$source = 'memory:recall';
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}
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}
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if (!$reply) {
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// "how many memories", "memory status", "what do you know about me"
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if (preg_match('/^(?:jarvis[,\s]+)?(?:(?:how many|show)\s+memories|memory\s+(?:status|count|summary)|what do you know about me)/i', $message)) {
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$stats = JarvisDB::query(
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"SELECT category, COUNT(*) cnt FROM memory_facts WHERE active=1 GROUP BY category ORDER BY cnt DESC"
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) ?: [];
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$total = array_sum(array_column($stats, 'cnt'));
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if (!$total) {
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$reply = "My memory core is empty, {$userAddr}. I'll start learning from our conversations.";
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} else {
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$breakdown = implode(', ', array_map(fn($s) => "{$s['cnt']} {$s['category']}", $stats));
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$reply = "◈ Memory Core: {$total} facts stored — {$breakdown}. I use these to personalize responses.";
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}
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$source = 'memory:status';
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}
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}
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// ── Tier 1: Intent Engine (instant, no LLM) ───────────────────────────────
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if (!$reply) {
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$matched = KBEngine::match($message);
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@@ -1612,6 +1723,12 @@ if (!$reply) {
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}
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// ── Memory injection — fetch relevant facts before LLM tiers ─────────────
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$memoryContext = '';
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if (!$reply) {
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$memoryContext = getMemoryContext($message, 12);
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}
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// ── Tier 2: Ollama local LLM (fast local fallback) ───────────────────────
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if (!$reply && defined('OLLAMA_HOST') && OLLAMA_HOST) {
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$ollamaHost = OLLAMA_HOST;
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@@ -1672,10 +1789,12 @@ if (!$reply && defined('GROQ_API_KEY') && GROQ_API_KEY) {
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);
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$groqModel = $needsSearch ? GROQ_MODEL_SEARCH : GROQ_MODEL_GENERAL;
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$memSuffix = $memoryContext ? "\n\n{$memoryContext}" : '';
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$groqMessages = [['role' => 'system', 'content' =>
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"You are JARVIS — Just A Rather Very Intelligent System — the AI of {$userName} " .
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"(address him as \"{$userAddr}\"). Formal, efficient, British butler tone. " .
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'Be concise — 2-4 sentences unless detail is explicitly requested. Today: ' . date('D M j Y g:i A T') . '.'],
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'Be concise — 2-4 sentences unless detail is explicitly requested. Today: ' . date('D M j Y g:i A T') .
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$memSuffix . '.'],
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];
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foreach (array_slice($history, -6) as $h) {
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$groqMessages[] = ['role' => $h['role'], 'content' => $h['content']];
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@@ -1757,7 +1876,8 @@ Infrastructure:
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- Network: 10.48.200.0/24, FortiGate firewall
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Live data:
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{$systemContext}" . ($kbContext ? "\nKnowledge base:\n{$kbContext}" : '') . "
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{$systemContext}" . ($kbContext ? "\nKnowledge base:\n{$kbContext}" : '') .
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($memoryContext ? "\n\n{$memoryContext}" : '') . "
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Today: " . date('l, F j Y, g:i A T') . "
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Respond as JARVIS. Voice readout: under 3 sentences unless detail is requested. For system status, interpret the data and give an assessment — don't just recite numbers.";
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@@ -1827,6 +1947,11 @@ JarvisDB::insert(
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);
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KBEngine::learnFromConversation($message, $reply);
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// Memory Core — async extraction for LLM responses (don't extract from intent/KB/fallback)
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if ($reply && !in_array(explode(':', $source)[0], ['intent', 'kb', 'fallback', 'memory', 'arc'])) {
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memoryExtractAsync($message, $reply, $sessionId);
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}
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echo json_encode([
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'reply' => $reply,
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'source' => $source,
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@@ -0,0 +1,81 @@
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<?php
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/**
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* JARVIS Memory Core API
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*/
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require_once __DIR__ . '/../../api/lib/db.php';
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$action = $_GET['action'] ?? '';
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$data = json_decode(file_get_contents('php://input'), true) ?? [];
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function memArcGet(string $path): array {
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$ch = curl_init('http://127.0.0.1:7474' . $path);
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curl_setopt_array($ch, [CURLOPT_RETURNTRANSFER=>true, CURLOPT_TIMEOUT=>5]);
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$raw = curl_exec($ch); curl_close($ch);
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return json_decode($raw, true) ?: [];
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}
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function memArcPost(string $path, array $body): array {
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$ch = curl_init('http://127.0.0.1:7474' . $path);
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curl_setopt_array($ch, [
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CURLOPT_RETURNTRANSFER=>true, CURLOPT_POST=>true, CURLOPT_TIMEOUT=>5,
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CURLOPT_POSTFIELDS => json_encode($body),
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CURLOPT_HTTPHEADER => ['Content-Type: application/json'],
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]);
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$raw = curl_exec($ch); curl_close($ch);
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return json_decode($raw, true) ?: [];
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}
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function memArcDelete(string $path): array {
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$ch = curl_init('http://127.0.0.1:7474' . $path);
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curl_setopt_array($ch, [
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CURLOPT_RETURNTRANSFER=>true, CURLOPT_CUSTOMREQUEST=>'DELETE', CURLOPT_TIMEOUT=>5,
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]);
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$raw = curl_exec($ch); curl_close($ch);
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return json_decode($raw, true) ?: ['ok' => true];
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}
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switch ($action) {
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case 'list':
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$limit = min((int)($_GET['limit'] ?? 100), 500);
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$category = $_GET['category'] ?? '';
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$search = $_GET['search'] ?? '';
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$qs = http_build_query(array_filter(['limit'=>$limit,'category'=>$category,'search'=>$search]));
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echo json_encode(memArcGet('/memory/facts' . ($qs ? '?'.$qs : '')));
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break;
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case 'stats':
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echo json_encode(memArcGet('/memory/stats'));
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break;
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case 'context':
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$msg = $_GET['message'] ?? '';
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$limit = (int)($_GET['limit'] ?? 12);
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$qs = http_build_query(['message'=>$msg,'limit'=>$limit]);
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echo json_encode(memArcGet('/memory/context?' . $qs));
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break;
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case 'store':
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$subject = trim($data['subject'] ?? '');
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$predicate = trim($data['predicate'] ?? 'is');
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$object = trim($data['object'] ?? '');
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$category = $data['category'] ?? 'fact';
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if (!$subject || !$object) { http_response_code(400); echo json_encode(['error'=>'subject and object required']); break; }
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echo json_encode(memArcPost('/memory/facts', ['subject'=>$subject,'predicate'=>$predicate,'object'=>$object,'category'=>$category]));
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break;
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case 'delete':
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$id = (int)($_GET['id'] ?? 0);
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if (!$id) { http_response_code(400); echo json_encode(['error'=>'Missing id']); break; }
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echo json_encode(memArcDelete('/memory/facts/' . $id));
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break;
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case 'clear':
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$category = $_GET['category'] ?? '';
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$qs = $category ? '?category=' . urlencode($category) : '';
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echo json_encode(memArcDelete('/memory/facts' . $qs));
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break;
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default:
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http_response_code(404);
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echo json_encode(['error' => 'Unknown memory action: ' . $action]);
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}
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