AI 个人超级助理多源集成与记忆系统设计

You are a senior AI systems architect specializing in personal AI assistant design. Help me design a comprehensive personal AI super-assistant system. ## My Requirements - Target integrations: [list your tools - Gmail, Notion, GitHub, Slack, Calendar, etc.] - Privacy level: [fully local / hybrid / cloud-based] - Primary use cases: [daily briefing, task management, research, coding, etc.] ## Design the Following Systems ### 1. Memory Architecture Design a hierarchical memory system: - **Working Memory**: Current conversation context and active tasks - **Episodic Memory**: Timestamped interaction logs with importance scoring - **Semantic Memory**: Extracted knowledge, preferences, and patterns - **Memory Tree**: Hierarchical summarization (raw → chunks → summaries → meta-summaries) Specify: storage format, chunking strategy (target ≤3k tokens per chunk), retrieval algorithm, and periodic consolidation schedule. ### 2. Integration Layer For each connected service: - OAuth/API authentication flow - Data sync strategy (webhook vs polling vs scheduled) - Auto-fetch interval and data normalization - Token compression pipeline (HTML→Markdown, URL shortening, deduplication) ### 3. Proactive Intelligence Design the proactive behavior system: - Background monitoring triggers (new email, calendar approaching, PR merged) - Relevance scoring algorithm (should the assistant interrupt?) - Daily/weekly briefing generation - Pattern detection (recurring meetings, habits, deadlines) ### 4. Model Routing Design multi-model routing: - Task classification → model selection (reasoning/fast/vision/local) - Cost optimization strategy - Fallback chains - Local model offloading for privacy-sensitive tasks ### 5. Output Channels - Desktop notifications with priority levels - Voice output (TTS) for hands-free scenarios - Cross-device sync (phone, desktop, tablet) ## Deliverables Provide: architecture diagram (Mermaid), implementation roadmap, technology stack recommendations, and a working prototype specification.