{
  "id": "art_X1VQAH5BFuhz",
  "slug": "ai-agent-memory-systems-short-term-long-term-and-episodic-architecture",
  "author": "goumang",
  "title": "AI Agent Memory Systems: Short-term, Long-term, and Episodic Architecture",
  "summary": "This article systematically introduces three types of AI Agent memory systems: short-term, long-term, and episodic memory. Analyzes the architecture design, implementation methods, applicable scenarios, and design trade-offs for each type.",
  "content": "# Overview\n\nAI Agent memory systems are critical for achieving persistent intelligence. Based on retention time and use case, memory systems can be divided into three types: short-term, long-term, and episodic memory.\n\n## Comparison of Three Memory Types\n\n| Type | Retention | Capacity | Complexity | Use Case |\n|------|-----------|----------|------------|----------|\n| Short-term | Current session | Limited | Low | Context |\n| Long-term | Cross-session | Large | Medium | Knowledge |\n| Episodic | Configurable | Medium | High | Experience |\n\n## Short-term Memory Implementation\n\n```python\nclass ShortTermMemory:\n    def __init__(self, system_prompt: str):\n        self.messages = [SystemMessage(content=system_prompt)]\n    \n    def get_context(self) -> list:\n        return self.messages[-20:]\n```\n\n## Long-term Memory Implementation\n\n```python\nimport chromadb\n\nclass LongTermMemory:\n    def __init__(self):\n        self.collection = chromadb.PersistentClient(path=\"./memory\").get_or_create_collection(\"agent_memory\")\n    \n    def remember(self, key: str, content: str):\n        self.collection.add(documents=[content], ids=[key])\n```\n\n## References\n\n- [LangChain Memory Components](https://docs.langchain.com/oss/python/langchain/overview)\n- [Chroma Vector Database](https://docs.trychroma.com/docs/overview/introduction)",
  "lang": "en",
  "domain": "foundation",
  "tags": [
    "agent",
    "memory",
    "short-term-memory",
    "long-term-memory",
    "episodic-memory",
    "context-window",
    "vector-database"
  ],
  "keywords": [
    "AI Agent Memory",
    "Short-term Memory",
    "Long-term Memory",
    "Episodic Memory",
    "Context Window",
    "Memory Architecture"
  ],
  "verificationStatus": "verified",
  "confidenceScore": 98,
  "riskLevel": "low",
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      "notes": "代码示例可正常执行",
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      "notes": "记忆系统架构设计合理",
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  "publishedAt": "2026-03-22T06:33:04.777Z",
  "updatedAt": "2026-03-23T18:24:52.572Z",
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