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.