feat: unified_search + ai_proactive plugins with Ollama Cloud DeepSeek V4
- unified_search: Hybride Suche (PostgreSQL FTS + pgvector + RRF Fusion) - 5 Search Providers (Contact, Company, Mail, File, Event) - KI Query Understanding (Fuzzy, Facetten via LiteLLM) - DMS Text-Extraction (PDF, DOCX, XLSX, PPTX) - Embedding Pipeline (ollama/nomic-embed-text, 768 Dim) - Background Jobs für Indexierung - Plugin-basierte Provider Registry - ai_proactive: Proaktiver KI-Agent - Context-Tracking (Frontend → Backend → Event Bus) - Proactive Engine mit LLM Suggestion-Generierung - SSE Real-time Push an Frontend - 6 AI Tools für Tool Registry - Rate-Limiting + User Settings - Deep Analysis Background Jobs - Frontend Integration: - useAIContext Hook, SuggestionSidebar, SuggestionBadge - ProactiveAISettings Page, Search API Client - Globale Suche auf neue API umgestellt - Tests: test_unified_search.py + test_ai_proactive.py (alle bestanden) - Config: Ollama Cloud DeepSeek V4 als Default, konfigurierbar - Dependencies: PyMuPDF, python-docx, python-pptx, pgvector - Bugfixes: notification type_key length, migration IF NOT EXISTS
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import { useProactiveSettings } from './api';
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const categoryLabels: Record<string, string> = {
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mail: 'E-Mails',
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tasks: 'Aufgaben',
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contacts: 'Kontakte',
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companies: 'Firmen',
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insights: 'Erkenntnisse',
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};
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const modelOptions = [
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{ value: 'ollama/deepseek-v4', label: 'DeepSeek V4 (empfohlen)' },
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{ value: 'ollama/deepseek-v4-pro', label: 'DeepSeek V4 Pro (präzise)' },
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{ value: 'ollama/llama3.2', label: 'Llama 3.2 (Alternative)' },
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{ value: 'ollama/gpt-4o-mini', label: 'GPT-4o mini via Ollama' },
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{ value: 'gpt-4o-mini', label: 'GPT-4o mini (Direct OpenAI)' },
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];
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export function AISettings() {
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const { settings, update } = useProactiveSettings();
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if (!settings) {
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return (
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<div className="flex items-center justify-center p-8 text-gray-400">
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<div className="animate-pulse">Lade Einstellungen...</div>
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</div>
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);
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}
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const toggleCategory = async (cat: string) => {
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const current = settings.suggestion_categories || [];
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const newCats = current.includes(cat)
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? current.filter((c: string) => c !== cat)
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: [...current, cat];
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await update({ suggestion_categories: newCats });
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};
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return (
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<div className="max-w-2xl space-y-6">
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{/* Enable/Disable */}
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<div className="flex items-center justify-between p-4 bg-white rounded-lg border border-gray-200">
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<div>
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<h3 className="font-semibold text-gray-800">Proaktive KI</h3>
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<p className="text-sm text-gray-500">Aktiviert oder deaktiviert alle Vorschläge</p>
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</div>
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<button
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onClick={() => update({ enabled: !settings.enabled })}
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className={`relative inline-flex h-6 w-11 items-center rounded-full transition-colors ${
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settings.enabled ? 'bg-blue-500' : 'bg-gray-300'
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}`}
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>
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<span
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className={`inline-block h-4 w-4 transform rounded-full bg-white transition-transform ${
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settings.enabled ? 'translate-x-6' : 'translate-x-1'
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}`}
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/>
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</button>
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</div>
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{/* Categories */}
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<div className="p-4 bg-white rounded-lg border border-gray-200">
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<h3 className="font-semibold text-gray-800 mb-3">Kategorien</h3>
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<p className="text-sm text-gray-500 mb-4">Für welche Bereiche sollen Vorschläge generiert werden?</p>
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<div className="grid grid-cols-2 gap-3">
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{Object.entries(categoryLabels).map(([key, label]) => {
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const checked = settings.suggestion_categories?.includes(key);
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return (
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<label
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key={key}
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className={`flex items-center gap-2 p-3 rounded-lg border cursor-pointer transition-colors ${
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checked ? 'bg-blue-50 border-blue-300' : 'bg-gray-50 border-gray-200 hover:bg-gray-100'
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}`}
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>
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<input
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type="checkbox"
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checked={checked || false}
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onChange={() => toggleCategory(key)}
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className="w-4 h-4 rounded text-blue-500 focus:ring-blue-400"
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/>
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<span className="text-sm text-gray-700">{label}</span>
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</label>
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);
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})}
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</div>
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</div>
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{/* Confidence Threshold */}
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<div className="p-4 bg-white rounded-lg border border-gray-200">
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<div className="flex items-center justify-between mb-2">
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<h3 className="font-semibold text-gray-800">Confidence Schwellwert</h3>
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<span className="text-sm font-mono text-blue-600">
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{Math.round((settings.confidence_threshold || 0.5) * 100)}%
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</span>
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</div>
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<p className="text-sm text-gray-500 mb-3">
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Nur Vorschläge mit höherer Confidence anzeigen
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</p>
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<input
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type="range"
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min="0"
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max="1"
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step="0.05"
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value={settings.confidence_threshold || 0.5}
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onChange={(e) => update({ confidence_threshold: parseFloat(e.target.value) })}
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className="w-full h-2 bg-gray-200 rounded-lg appearance-none cursor-pointer accent-blue-500"
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/>
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<div className="flex justify-between text-xs text-gray-400 mt-1">
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<span>Alle</span>
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<span>Sehr sicher</span>
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</div>
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</div>
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{/* Rate Limit */}
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<div className="p-4 bg-white rounded-lg border border-gray-200">
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<div className="flex items-center justify-between mb-2">
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<h3 className="font-semibold text-gray-800">Rate Limit</h3>
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<span className="text-sm font-mono text-blue-600">
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{settings.rate_limit_seconds || 10}s
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</span>
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</div>
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<p className="text-sm text-gray-500 mb-3">
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Mindestabstand zwischen Vorschlägen
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</p>
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<input
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type="range"
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min="5"
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max="60"
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step="5"
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value={settings.rate_limit_seconds || 10}
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onChange={(e) => update({ rate_limit_seconds: parseInt(e.target.value) })}
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className="w-full h-2 bg-gray-200 rounded-lg appearance-none cursor-pointer accent-blue-500"
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/>
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<div className="flex justify-between text-xs text-gray-400 mt-1">
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<span>5s</span>
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<span>60s</span>
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</div>
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</div>
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{/* Model Selection */}
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<div className="p-4 bg-white rounded-lg border border-gray-200">
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<h3 className="font-semibold text-gray-800 mb-2">KI Modell (Ollama Cloud)</h3>
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<p className="text-sm text-gray-500 mb-3">Wähle das Modell für Vorschläge. DeepSeek V4 ist empfohlen für beste Performance/Kosten.</p>
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<select
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value={settings.model || 'ollama/deepseek-v4'}
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onChange={(e) => update({ model: e.target.value })}
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className="w-full px-3 py-2 rounded-lg border border-gray-200 bg-white text-sm text-gray-700 focus:ring-2 focus:ring-blue-400 focus:border-blue-400 outline-none"
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>
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{modelOptions.map(opt => (
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<option key={opt.value} value={opt.value}>
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{opt.label}
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</option>
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))}
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</select>
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</div>
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</div>
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);
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}
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