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NEW: - /learning-dashboard.html (8.2KB) · UX premium dashboard - /api/learning-analytics.php (3.3KB) · PG aggregator - dashboards-index enriched · section Learning & Analytics METRICS LIVE (24h window): - Hero: total_learned, success_pct, bots_count, conversations, sessions, avg_ms - Per chatbot: total queries, success rate, progress bar colored - Intents distribution: count, success rate per intent - Latest 10 learnings: time, chatbot, intent, outcome badge AUTO-REFRESH 15s · fetch /api/learning-analytics.php Color-coded cards: excellent (>=90pct green), good (>=70 blue), ok (>=50 orange), low (<50 red) Data sources: - ai_learning_log (table v20) avec experience jsonb + outcome_success - wevia_conversations (table v18) conversations count + sessions distinct Validation LIVE: - HTTP 200 on /learning-dashboard.html (9870b served) - API returns structured JSON in <200ms - 6 rows learned · 83pct success · 2 bots used (wevia-master 100pct, blade-ai 0pct) - 10 conversations · 9 sessions Doctrine: - Point verite unique (1 dashboard = tout apprentissage) - UX PREMIUM (gradients, badges colorés, progress bars, refresh pulse) - RELIER toutes pages (dashboards-index -> learning-dashboard) - Zero regression - Additif pur
90 lines
3.2 KiB
PHP
90 lines
3.2 KiB
PHP
<?php
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header('Content-Type: application/json; charset=utf-8');
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header('Cache-Control: no-store');
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try {
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$pg = @pg_connect("host=127.0.0.1 dbname=adx_system user=admin password=admin123 connect_timeout=3");
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if (!$pg) throw new Exception("PG connect failed");
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// Summary
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$r = pg_query($pg, "SELECT
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COUNT(*)::int as total_learned,
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SUM(CASE WHEN outcome_success THEN 1 ELSE 0 END)::int as success_total,
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COUNT(DISTINCT (experience->>'chatbot'))::int as bots_count,
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COALESCE(ROUND(AVG((experience->>'total_ms')::int))::int, 0) as avg_ms
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FROM ai_learning_log
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WHERE learned_at > NOW() - interval '24 hours'");
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$summary = pg_fetch_assoc($r);
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$summary['success_pct'] = $summary['total_learned'] > 0
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? round(100.0 * $summary['success_total'] / $summary['total_learned'])
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: 0;
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// Conversations count
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$r = pg_query($pg, "SELECT COUNT(*)::int as total, COUNT(DISTINCT session_id)::int as sessions FROM wevia_conversations");
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$c = pg_fetch_assoc($r);
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$summary['conversations'] = (int)$c['total'];
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$summary['sessions'] = (int)$c['sessions'];
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// Per chatbot (24h)
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$r = pg_query($pg, "SELECT
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experience->>'chatbot' as chatbot,
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COUNT(*)::int as total,
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SUM(CASE WHEN outcome_success THEN 1 ELSE 0 END)::int as success
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FROM ai_learning_log
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WHERE learned_at > NOW() - interval '24 hours' AND experience->>'chatbot' IS NOT NULL
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GROUP BY experience->>'chatbot'
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ORDER BY total DESC");
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$chatbots = [];
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while ($row = pg_fetch_assoc($r)) {
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$row['total'] = (int)$row['total'];
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$row['success'] = (int)$row['success'];
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$row['success_pct'] = $row['total'] > 0 ? round(100.0 * $row['success'] / $row['total']) : 0;
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$chatbots[] = $row;
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}
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// Intents distribution
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$r = pg_query($pg, "SELECT
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experience->>'intent' as intent,
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COUNT(*)::int as count,
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SUM(CASE WHEN outcome_success THEN 1 ELSE 0 END)::int as success
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FROM ai_learning_log
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WHERE learned_at > NOW() - interval '24 hours'
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GROUP BY experience->>'intent'
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ORDER BY count DESC");
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$intents = [];
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while ($row = pg_fetch_assoc($r)) {
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$row['count'] = (int)$row['count'];
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$row['success'] = (int)$row['success'];
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$row['rate'] = $row['count'] > 0 ? round(100.0 * $row['success'] / $row['count']) : 0;
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$intents[] = $row;
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}
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// Latest 10
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$r = pg_query($pg, "SELECT
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learned_at,
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experience->>'chatbot' as chatbot,
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experience->>'intent' as intent,
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outcome_success as outcome
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FROM ai_learning_log
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ORDER BY learned_at DESC LIMIT 10");
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$latest = [];
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while ($row = pg_fetch_assoc($r)) {
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$row['outcome'] = $row['outcome'] === 't';
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$latest[] = $row;
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}
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pg_close($pg);
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echo json_encode([
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'ts' => date('c'),
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'window' => '24h',
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'summary' => $summary,
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'chatbots' => $chatbots,
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'intents' => $intents,
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'latest' => $latest,
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], JSON_PRETTY_PRINT | JSON_UNESCAPED_UNICODE);
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} catch (Throwable $e) {
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http_response_code(500);
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echo json_encode(['error' => $e->getMessage()]);
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}
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