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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"""API routes for the AI Proactive plugin.
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Endpoints: context tracking, suggestions CRUD, SSE stream, settings, stats.
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"""
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from __future__ import annotations
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import asyncio
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import json
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import logging
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import uuid
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from typing import Any
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from fastapi import APIRouter, Depends, HTTPException, Query
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from fastapi.responses import StreamingResponse
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.db import get_db, set_tenant_context
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from app.core.event_bus import get_event_bus
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from app.deps import get_current_user, require_permission
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from app.plugins.builtins.ai_proactive.models import (
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ContextLog,
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ProactiveSettings,
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ProactiveSuggestion,
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)
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from app.plugins.builtins.ai_proactive.schemas import (
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ActRequest,
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ActResponse,
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ContextReport,
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SettingsResponse,
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SettingsUpdate,
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SuggestionListResponse,
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SuggestionResponse,
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StatsResponse,
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)
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from app.plugins.builtins.ai_proactive.services import (
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execute_suggested_action,
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get_active_suggestions,
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get_sse_queue,
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get_stats,
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get_user_settings,
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mark_dismissed,
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)
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/v1/ai-proactive", tags=["ai-proactive"])
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def _suggestion_to_response(s: ProactiveSuggestion) -> SuggestionResponse:
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"""Convert a ProactiveSuggestion model to SuggestionResponse."""
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return SuggestionResponse(
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id=str(s.id),
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entity_type=s.entity_type,
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entity_id=str(s.entity_id) if s.entity_id else None,
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suggestion_type=s.suggestion_type,
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title=s.title,
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content=s.content,
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confidence=s.confidence,
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actions=s.actions or [],
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created_at=s.created_at,
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is_dismissed=s.is_dismissed,
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is_acted_upon=s.is_acted_upon,
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)
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def _settings_to_response(s: ProactiveSettings) -> SettingsResponse:
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"""Convert ProactiveSettings model to SettingsResponse."""
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return SettingsResponse(
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enabled=s.enabled,
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suggestion_categories=s.suggestion_categories or [],
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confidence_threshold=s.confidence_threshold,
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rate_limit_seconds=s.rate_limit_seconds,
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model=s.model,
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)
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# ─── Context Tracking ───
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@router.post("/context", dependencies=[Depends(require_permission("ai_proactive:read"))])
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async def report_context(
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context: ContextReport,
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current_user: dict[str, Any] = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Frontend reports current context (page, entity).
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Stores context log entry and publishes event for proactive engine.
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"""
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tenant_id = uuid.UUID(current_user["tenant_id"])
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user_id = uuid.UUID(current_user["user_id"])
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# Parse entity_id if present
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entity_id: uuid.UUID | None = None
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if context.entity_id:
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try:
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entity_id = uuid.UUID(context.entity_id)
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except (ValueError, TypeError):
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entity_id = None
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# Store context log
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log_entry = ContextLog(
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tenant_id=tenant_id,
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user_id=user_id,
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page=context.page,
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entity_type=context.entity_type,
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entity_id=entity_id,
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entity_data=context.entity_data or {},
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)
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db.add(log_entry)
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await db.flush()
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# Publish event
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event_bus = get_event_bus()
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event_name = (
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"context.entity_selected"
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if context.entity_type and context.entity_id
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else "context.view_changed"
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)
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payload = {
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"user_id": str(user_id),
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"tenant_id": str(tenant_id),
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"page": context.page,
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"entity_type": context.entity_type,
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"entity_id": str(entity_id) if entity_id else None,
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"entity_data": context.entity_data or {},
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}
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await event_bus.publish(event_name, payload)
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return {"status": "ok"}
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# ─── Suggestions ───
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@router.get(
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"/suggestions",
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dependencies=[Depends(require_permission("ai_proactive:read"))],
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response_model=SuggestionListResponse,
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)
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async def get_suggestions(
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entity_type: str | None = Query(None),
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entity_id: str | None = Query(None),
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limit: int = Query(10, ge=1, le=100),
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current_user: dict[str, Any] = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Get active suggestions for the current user."""
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tenant_id = uuid.UUID(current_user["tenant_id"])
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user_id = uuid.UUID(current_user["user_id"])
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eid: uuid.UUID | None = None
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if entity_id:
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try:
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eid = uuid.UUID(entity_id)
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except (ValueError, TypeError):
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eid = None
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suggestions = await get_active_suggestions(
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db, tenant_id, user_id, entity_type=entity_type, entity_id=eid, limit=limit
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)
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items = [_suggestion_to_response(s) for s in suggestions]
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return SuggestionListResponse(items=items, total=len(items))
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@router.post(
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"/suggestions/{suggestion_id}/dismiss",
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dependencies=[Depends(require_permission("ai_proactive:write"))],
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)
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async def dismiss_suggestion(
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suggestion_id: str,
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current_user: dict[str, Any] = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Mark a suggestion as dismissed."""
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tenant_id = uuid.UUID(current_user["tenant_id"])
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user_id = uuid.UUID(current_user["user_id"])
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try:
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sid = uuid.UUID(suggestion_id)
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except (ValueError, TypeError):
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raise HTTPException(status_code=400, detail="Invalid suggestion ID")
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success = await mark_dismissed(db, sid, user_id, tenant_id)
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if not success:
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raise HTTPException(status_code=404, detail="Suggestion not found")
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return {"status": "ok"}
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@router.post(
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"/suggestions/{suggestion_id}/act",
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dependencies=[Depends(require_permission("ai_proactive:write"))],
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response_model=ActResponse,
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)
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async def act_on_suggestion(
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suggestion_id: str,
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action: ActRequest,
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current_user: dict[str, Any] = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Execute a suggested action."""
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tenant_id = uuid.UUID(current_user["tenant_id"])
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user_id = uuid.UUID(current_user["user_id"])
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try:
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sid = uuid.UUID(suggestion_id)
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except (ValueError, TypeError):
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raise HTTPException(status_code=400, detail="Invalid suggestion ID")
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result = await execute_suggested_action(
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db, sid, action.action_index, user_id, tenant_id, current_user
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)
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return ActResponse(
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success=result.get("success", False),
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data=result.get("data"),
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error=result.get("error"),
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)
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# ─── SSE Stream ───
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@router.get(
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"/suggestions/stream",
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dependencies=[Depends(require_permission("ai_proactive:read"))],
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)
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async def stream_suggestions(
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current_user: dict[str, Any] = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""SSE stream: push new suggestions in real-time.
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Uses an asyncio.Queue per user. Heartbeat every 30s.
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"""
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user_id = str(current_user["user_id"])
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async def event_generator():
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queue = get_sse_queue(user_id)
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while True:
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try:
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suggestion = await asyncio.wait_for(queue.get(), timeout=30)
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yield f"data: {json.dumps(suggestion, default=str)}\n\n"
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except asyncio.TimeoutError:
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yield ": keepalive\n\n"
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return StreamingResponse(
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event_generator(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no",
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},
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)
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# ─── Settings ───
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@router.get(
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"/settings",
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dependencies=[Depends(require_permission("ai_proactive:read"))],
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response_model=SettingsResponse,
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)
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async def get_settings(
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current_user: dict[str, Any] = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Get proactive AI settings for the current user."""
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tenant_id = uuid.UUID(current_user["tenant_id"])
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user_id = uuid.UUID(current_user["user_id"])
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settings = await get_user_settings(db, tenant_id, user_id)
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return _settings_to_response(settings)
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@router.put(
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"/settings",
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dependencies=[Depends(require_permission("ai_proactive:config"))],
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response_model=SettingsResponse,
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)
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async def update_settings(
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settings_update: SettingsUpdate,
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current_user: dict[str, Any] = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Update proactive AI settings for the current user."""
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tenant_id = uuid.UUID(current_user["tenant_id"])
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user_id = uuid.UUID(current_user["user_id"])
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settings = await get_user_settings(db, tenant_id, user_id)
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update_data = settings_update.model_dump(exclude_unset=True)
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for field, val in update_data.items():
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setattr(settings, field, val)
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await db.flush()
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return _settings_to_response(settings)
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# ─── Stats ───
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@router.get(
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"/stats",
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dependencies=[Depends(require_permission("ai_proactive:read"))],
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response_model=StatsResponse,
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)
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async def get_stats_endpoint(
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current_user: dict[str, Any] = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Get proactive AI usage statistics for the current user."""
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tenant_id = uuid.UUID(current_user["tenant_id"])
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user_id = uuid.UUID(current_user["user_id"])
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stats = await get_stats(db, tenant_id, user_id)
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return StatsResponse(**stats)
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