ae228bb484
feat(B-HOOK): Lifecycle Hooks + Outbox Events — 55 neue Hooks, 10 Domain Events
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B-HOOK-CORE: Company Hooks (6: before/after create/update/delete)
B-HOOK-MAIL: Mail Hooks (5: after_receive, before/after_delete, before/after_move)
B-HOOK-DMS: DMS Hooks (10: after_upload, before/after_update/delete/restore, folder CRUD)
B-HOOK-CAL: Calendar Hooks (4: before/after update/delete)
B-HOOK-TASK: Task Hooks (6: before/after create/update/delete)
B-HOOK-COMM: Communication Hooks (8: conversation create, message/edit/delete)
B-HOOK-AI: Agent Hooks (2: before/after_run)
B-HOOK-WF: Workflow Hooks (4: before/after_start, after_complete/cancel)
B-HOOK-TAG: Tag Hooks (8: create/assign/unassign/delete)
B-HOOK-SEARCH: Search Filters (2: before/after_search)
B-EVT-OUTBOX: 10 Domain Events (task.completed, file.created/deleted/restored, mail.received, workflow.started/completed/cancelled, agent.run_started/completed)
B-HOOK-TEST: 79 Tests in test_lifecycle_hooks.py — alle grün
B-HOOK-DOC: Plugin-Dev-Guide Kapitel 8 aktualisiert (Hook-Liste + Outbox Event-Liste)
2026-08-13 20:54:15 +02:00
211242a807
feat(B-VEC): pgvector HNSW Optimierung — ef_construction=128, m=16, ef_search=40
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B-VEC: Migration 0118 — HNSW-Indizes mit optimierten Parametern (ef_construction=128, m=16)
- 5 Tabellen: contacts, mails, files, calendar_entries, tags
- config.py: hnsw_ef_construction, hnsw_m, hnsw_ef_search, vector_index_type Settings
- base_provider.py + search_engine.py: SET LOCAL hnsw.ef_search vor Vector-Queries
B-VEC-IVF: IVFFlat als Alternative dokumentiert (vector_index_type Setting)
B-VEC-BATCH: Batch-Embedding verifiziert (generate_embeddings_batch nutzt llm_embed())
B-VEC-TEST: Performance-Tests auf Coolify-Instanz verschoben (benötigt 10k+ Datensätze)
2026-08-13 16:28:55 +02:00
517e1b6d8b
sprint2+3: remaining services visibility filter + search provider permission-aware + dashboard route
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2026-07-29 02:05:14 +02:00
879106c4eb
Phase 1C: Frontend unified contact UI
2026-07-23 17:17:32 +02:00
4a43745b50
fix: unified_search + ai_proactive get API key from DB, fix model names for Ollama Cloud
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- query_understanding.py: get API key/base_url/provider_type from ai_providers DB
- embedding.py: get API key from DB, pass db+tenant_id through call chain
- routes.py: pass db+tenant_id to llm_analyze_query and llm_aggregate_results
- search_engine.py: pass db+tenant_id to generate_embedding
- unified_search/jobs.py: pass db+tenant_id to generate_embedding
- Fix all default model names: ollama/deepseek-v4 -> ollama/deepseek-v4-flash
- Ollama Cloud has no embedding endpoint; embedding calls fail gracefully
2026-07-19 02:22:25 +02:00
8cebb4f4e9
feat: unified_search + ai_proactive plugins with Ollama Cloud DeepSeek V4
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- 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
Agent Zero