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

app/plugins/builtins/unified_search/schemas.py

@@ -0,0 +1,71 @@
+"""Pydantic schemas for the Unified Search plugin."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from pydantic import BaseModel, Field
+
+
+# ─── Search ───
+
+class SearchRequest(BaseModel):
+    query: str = Field(..., min_length=1, max_length=500)
+    entity_types: list[str] | None = None
+    limit: int = Field(default=20, ge=1, le=100)
+    offset: int = Field(default=0, ge=0)
+
+
+class SearchResult(BaseModel):
+    entity_type: str
+    entity_id: str
+    title: str
+    snippet: str
+    score: float
+    data: dict[str, Any] = Field(default_factory=dict)
+
+
+class SearchResponse(BaseModel):
+    query: str
+    normalized_query: str
+    results: list[SearchResult]
+    facets: dict[str, Any]
+    summary: str
+    suggestions: list[str]
+
+
+# ─── Similar ───
+
+class SimilarRequest(BaseModel):
+    entity_type: str
+    entity_id: str
+    limit: int = Field(default=5, ge=1, le=50)
+
+
+class SimilarResponse(BaseModel):
+    similar: dict[str, list[SearchResult]]
+
+
+# ─── Suggest ───
+
+class SuggestRequest(BaseModel):
+    q: str = Field(..., min_length=1, max_length=200)
+    limit: int = Field(default=10, ge=1, le=50)
+
+
+class SuggestResponse(BaseModel):
+    suggestions: list[str]
+
+
+# ─── Reindex ───
+
+class ReindexRequest(BaseModel):
+    entity_types: list[str] = Field(default_factory=list)
+
+
+# ─── Provider ───
+
+class ProviderResponse(BaseModel):
+    entity_type: str
+    plugin_name: str
+    is_active: bool