Files
leocrm/app/plugins/builtins/ai_proactive/frontend/api.ts
T
Agent Zero 8cebb4f4e9 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
2026-07-18 11:21:51 +02:00

73 lines
2.2 KiB
TypeScript

import { useState, useEffect, useCallback } from 'react';
import { apiClient } from '@/api/client';
export interface Suggestion {
id: string;
entity_type: string;
entity_id: string | null;
suggestion_type: 'info' | 'warning' | 'action' | 'insight';
title: string;
content: string;
confidence: number;
actions: Array<{ method: string; path: string; body: any; description: string }>;
created_at: string;
is_dismissed: boolean;
is_acted_upon: boolean;
}
export function useSuggestions() {
const [suggestions, setSuggestions] = useState<Suggestion[]>([]);
const [connected, setConnected] = useState(false);
useEffect(() => {
// Initial load
apiClient.get('/api/v1/ai-proactive/suggestions').then(r => {
setSuggestions(r.data.items);
}).catch(() => {});
// SSE Stream
const eventSource = new EventSource('/api/v1/ai-proactive/suggestions/stream');
eventSource.onopen = () => setConnected(true);
eventSource.onerror = () => setConnected(false);
eventSource.onmessage = (e) => {
try {
const suggestion = JSON.parse(e.data);
setSuggestions(prev => [suggestion, ...prev].slice(0, 50));
} catch {}
};
return () => eventSource.close();
}, []);
const dismiss = useCallback(async (id: string) => {
setSuggestions(prev => prev.filter(s => s.id !== id));
await apiClient.post(`/api/v1/ai-proactive/suggestions/${id}/dismiss`).catch(() => {});
}, []);
const act = useCallback(async (id: string, actionIndex: number) => {
const result = await apiClient.post(`/api/v1/ai-proactive/suggestions/${id}/act`, {
action_index: actionIndex
});
setSuggestions(prev => prev.map(s => s.id === id ? { ...s, is_acted_upon: true } : s));
return result.data;
}, []);
return { suggestions, connected, dismiss, act };
}
export function useProactiveSettings() {
const [settings, setSettings] = useState<any>(null);
useEffect(() => {
apiClient.get('/api/v1/ai-proactive/settings').then(r => setSettings(r.data));
}, []);
const update = useCallback(async (updates: any) => {
const r = await apiClient.put('/api/v1/ai-proactive/settings', updates);
setSettings(r.data);
return r.data;
}, []);
return { settings, update };
}