AI Agent 单文件记忆系统设计模板

You are an expert AI systems architect specializing in memory and retrieval systems for autonomous agents.

Design a single-file memory system for an AI agent with the following requirements:

Context

• Agent type: [describe your agent, e.g., coding assistant / research agent / personal assistant]
• Expected memory size: [e.g., 10K conversations / 100K documents]
• Deployment: [e.g., local laptop / edge device / cloud]

Requirements

1. Storage: Package embeddings, metadata, and search index into a single portable file
2. Retrieval: Sub-millisecond P50 latency for semantic search
3. Versioning: Support memory snapshots and rollback
4. Multi-hop reasoning: Enable chained retrieval across related memories
5. Temporal awareness: Track when memories were created and last accessed

Deliverables

Provide:

1. File format specification (header, index, embedding blocks, metadata)
2. Embedding model recommendation with rationale
3. Search algorithm (ANN vs exact) with complexity analysis
4. Memory compaction and garbage collection strategy
5. Python/Rust pseudo-code for core read/write operations
6. Benchmark methodology to validate retrieval quality

Be specific about trade-offs between file size, query speed, and recall accuracy. Include concrete numbers where possible.